Patent Grant
12001295
Computers have become an integral part of business operations such that many banks, insurance companies, brokerage firms, financial service providers, and a variety of other businesses rely on computer networks to store, manipulate, and display information that is constantly subject to change. Oftentimes, the success or failure of an important transaction may turn on the availability of information that is both accurate and current. Accordingly, businesses worldwide recognize the commercial value of their data and seek reliable, cost-effective ways to protect the information stored on their computer networks.
To protect this stored data, network administrators can create backup copies of the stored information so that if the original data is destroyed or corrupted, the backup copy can be restored and used in place of the original data. One drawback, however, with conventional backup systems is that an interruption of the backup process can require the entire process to be restarted, thereby resulting in a loss of valuable time and resources, especially for large backup operations.
In view of the foregoing, a need exists for improved systems and methods for performing backup operations. For example, there is a need for failover systems and methods for backing up data in a storage environment. In yet other embodiments, a need exists for load balancing between modules tasked with performing the backup operations and/or indexing the data such that when one module fails or is overloaded, another module can continue the process in place of the failed module. Load balancing features enable a smooth allocation and transition of resources that can reduce the chance of failure during backups.
In certain embodiments of the invention, a tiered storage system (hereinafter “backup system” or “storage system”) is disclosed that provides for failover protection during data backup operations. In certain embodiments, the backup system provides for an index, or catalog, (hereinafter “index/catalog”) for identifying and enabling restoration of backup data located on a storage device. Because there is no limitation on the number of index/catalogs provided, some embodiments include different index/catalogs that are generated and maintained by different indexing technologies and/or methodologies in the backup system. The backup system further maintains a set of transaction logs (or “action logs” or “log files” or “transaction log files”) generated by media agent modules; the transaction logs comprise metadata with respect to individual data chunks of a backup file on the storage device and/or other metadata associated with storage operations such as backup and restore. The transaction logs are generated by the storage operation and thereafter are processed into the index/catalog(s), thereby removing a dependency between completion of the storage operation and indexing of the transaction logs. The transaction logs reduce system latency, as they are generated faster than indexing operations. A copy of the index/catalog and transaction logs can be stored at location(s) accessible by each of the media agent modules. In this manner, in case of a failure of one media agent module during backup, the transaction logs and existing index/catalog can be used by a second media agent module to resume the backup operation without requiring a restart of the backup process.
Heterogeneous Indexing. Indexing is key to managing data, including managing data protection as well as storing, searching, restoring, and purging data. Multiple indexing modules are implemented in the illustrative backup system, using various indexing technologies and methodologies for tracking backed up data of different kinds. Any number of transaction logs can be generated from a given storage operation, such as backup and/or restore. In some embodiments, transaction logs are stored locally at the media agent host for use as working copies. In some embodiments, these transaction logs are preserved in backup by being stored to the storage device(s) that comprise corresponding backup data. Additionally, load balancing features optimize performance among indexing modules and/or their computing hosts without administrative intervention. Some embodiments exploit the ability of the illustrative backup system to employ multiple indexing modules as a use case for index/catalog replication.
Each illustrative index/catalog comprises information from various transaction logs generated in the backup system, e.g., generated from multiple storage operations, generated by multiple media agents, and/or generated by multiple backup systems (e.g., storage operation cells). In addition to facilitating transitions during failovers, the index/catalog enables backed up data to be found, browsed, restored, and/or further processed. Moreover, the index/catalog provides a certain level of granularity, such as identifying individual files within a backup copy based on content and/or metadata searches.
In some embodiments, transaction logs are collected and stored “as is” into a repository from which they can be recalled and processed as needed, but they are not incorporated and/or organized into an index/catalog. An association between each storage job and corresponding transaction logs enables all backup data in the storage job to be recovered. This approach does not offer the granularity of an index/catalog, but is useful for avoiding the relatively high cost of implementing indexing hosts when source data is not suitable for granular indexing, and/or when recovering all backup data together from a given job meets the customer's needs. In some embodiments, transaction logs in the repository are recovered later and incorporated into one or more index/catalogs.
Index/catalog data structures are, in some embodiments, managed and stored separately within the illustrative backup system and are not necessarily stored with the backed up data, though the invention is not so limited. One or more index/catalogs in the illustrative backup system reside on computing devices that are specially configured for performing indexing functions (“indexing hosts”), e.g., they are equipped with powerful processors, a relatively large main memory, and relatively high-speed cache/mass storage. These indexing hosts operate separately from computing devices that host media agent modules, which handle storage operations, but the invention is not so limited and in some embodiments, an indexing host comprises both indexing capabilities and media agent module(s), e.g., a “media agent/indexing host.”
Multiple Index/Catalogs of Different Types. Heterogeneous indexing involves the use of multiple diverse index/catalogs in the illustrative backup systems. In some embodiments, an indexing host comprises multiple types of indexing technologies for generating and maintaining respective index/catalogs. When the indexing is performed by software that executes on the indexing host, the software may be referred to herein as an “indexing module.” Different indexing modules execute on the same and/or on distinct indexing hosts, without limitation. Examples of indexing technologies include ctree, Apache solr, elasticsearch, etc., without limitation. The resulting index/catalog is illustratively referred to as a ctree index/catalog, solr index/catalog, elasticsearch index/catalog, respectively. In some embodiments, the indexing technology is a database management system, such as Microsoft SQL, MySQL, SQLite, etc., without limitation, resulting in an index/catalog that is organized around a database schema, e.g., SQL index/catalog, MySQL index/catalog, SQLite index/catalog, respectively, without limitation. Illustratively, structured database index/catalogs are used for tracking backups of database data and, in some embodiments, are organized according to a schema that is compatible with and/or mimics in whole or in part the schema in the source data being backed up.
Thus, the illustrative backup system uses any number of indexing hosts, each indexing host generating and maintaining one or more diverse index/catalogs and/or in the case of a media agent/indexing host, also performing storage operations by a resident media agent. Illustratively, indexing preferences such as a policy or other criteria govern when an index/catalog is to be backed up and where the backed up index/catalog is to be stored.
Indexing preferences are part of system preferences and are stored at one or more of: a storage manager, a management database associated with the storage manager, the indexing host, and/or another component of the backup system, without limitation. Backup schedules for indexes generally operate independently, e.g., asynchronously, at different times, autonomously, etc., of when storage operations generate backup data, even when a media agent co-resides with indexing module(s) on the same media agent/indexing host. For example, the backup system may perform a first storage operation generating backup data at a first time, update one or more index/catalogs using transaction log data associated with the storage operation at a second time, and, at a later third time, may perform a second storage operation to back up the one or more index/catalogs; data and index/catalogs backed up during the first and second storage operations may be stored on the same or on different storage devices according to preferences. In some embodiments, preferences indicate which storage operations should trigger an index/catalog backup operation, e.g., after a full backup, after a synthetic full backup, after a reference copy is created, after a data restore operation, etc. The illustrative backup system is configured to recover index/catalogs from index/catalog backup copies and/or by recovering transaction logs that were stored with backup data. For example, an index/catalog may be restored from a backup copy of the index/catalog made at a first point-in-time and then further updated by parsing data from and/or “playing back” stored copies of transaction logs from storage operations performed after the first point-in-time.
Illustratively, transaction logs are stored to backup storage along with a corresponding identifier of the storage operations and/or storage job (e.g., backup job, archive job, etc.) from which the transaction logs were generated. Typically, a storage job comprises a plurality of storage operations such as when a plurality of data files or a backup set of data are backed up. The illustrative index/catalogs also store an association between the storage job and the information in the transaction logs. Accordingly, all backup data generated in a certain storage job can be retrieved as needed using an index/catalog.
Preferably, transaction logs are generated in a format that is not specific to a particular type of index/catalog or indexing technology, so that one or more index/catalogs can incorporate the information in the transaction logs. For example, XML is used in some embodiments of the transaction logs. XML is then consumed and interpreted by an appropriate indexing host(s) and indexing module(s) when incorporating the transaction log information into each respective index/catalog.
Selecting a Suitable Index Among Diverse Index/Catalogs. Indexing preferences generally associate each data source with a type of indexing technology and/or with an index/catalog and/or with a computing device that hosts the target index/catalog for tracking backup data generated from the source data. The illustrative backup system comprises rules that are used in storage operations for selecting which index/catalog receives transaction logs. The rules are included in system preferences, illustratively in the management database associated with the storage manager. The storage manager instructs the media agent assigned to the storage operation where to transmit transaction logs, e.g., to one or more indexing hosts and/or their respective index/catalogs. In other embodiments, rules for choosing which index will track a particular data subclient and/or backup set are stored in each media agent. In other embodiments, the rules reside at the data agents and/or in databases associated therewith that initially process data for backup before the data reaches the media agent, and the data agent illustratively instructs the media agent. Thus, indexing destinations are defined granularly and flexibly in reference to the source data, for example at the subclient level or as associated with other sets of data under management by the system such as backup sets.
Preferably, rules for determining which type of index/catalog tracks a given data source favor choosing solr technology (alternatively, elasticsearch) for data sources that are relatively rich in metadata, such as Microsoft OneDrive web-based file hosting and synchronization, Microsoft SharePoint web-based collaborative platform incorporating Microsoft Office applications, Microsoft Exchange mail server and calendaring service, Google Drive web-based file storage and synchronization service, and/or other like applications, etc. When the data source is a file system or network attached storage, which is relatively metadata-poor compared to the above-mentioned sources, the illustrative rules favor choosing ctree indexing technology. When the data source is a structured database (e.g., managed by a database management system, such as an Oracle database), the illustrative rules favor SQL database technology or the like. For example, file system data from a certain source device (e.g., storage device 102, client computing device, etc.) is assigned to a first ctree index/catalog on a first indexing server, whereas database data from the same source is assigned to an SQL index/catalog on the first indexing server or on a second indexing server, without limitation. These examples are merely illustrative, and the invention is not so limited. Accordingly, diverse types of source data are indexed to diverse index/catalogs.
The illustrative architecture of the backup system contemplates not only the use of multiple index/catalogs and different kinds of indexing technology associated with different data sources, but further contemplates tiered or multi-step indexing applied to the same data source. For example, a given subclient (grouping of data) and/or backup set (grouping of subclients) is backed up at a first time, thus generating a first set of transaction logs that are incorporated into a first index of a first kind, e.g., file system data indexed into a ctree index, without limitation. Further backups of the same data source are updated into the same index/catalog comprising metadata from the transaction logs. A separate round of content indexing is applied to all or part of the backup data, which results in a separate content index of a second kind, e.g., a solr index, without limitation. Thus, the indexing technology is tailored to the kinds of data being indexed.
When a user searches for backup data in the illustrative backup system, the searching infrastructure directs the search to a metadata index/catalog when the sought-after information is in the nature of metadata. When the sought-after information is in the nature of data contents (e.g., words, phrases, specially formatted alphanumeric strings such as Social Security numbers, image content, etc.), the searching infrastructure directs the search to a second (content) index/catalog. Thus, in some embodiments, multiple indexes cover the same underlying data at different levels of granularity; and in other embodiments indexes do not overlap, because different data types are tracked by distinct index/catalogs.
Load Balancing of Backup and Indexing Resources—Migration Jobs. In some embodiments, the backup system includes features for load balancing among the computing devices that host media agents and/or index/catalogs. Illustratively, so-called “catalog migration jobs” transfer all or part of an index/catalog from one host to another. Illustrative “media agent migration jobs” transfer media agent modules from one host to another, e.g., to offload a host for indexing. Catalog migration jobs are not necessarily used for failover, i.e., when a component fails and/or when a backup job is interrupted, and are used at other times to ensure a smooth re-allocation of resources and to provide improved performance in the backup system on an ongoing basis without administrator intervention. For simplicity, catalog migration jobs and media agent migration jobs are referred to hereinafter as “migration jobs.”
The illustrative backup system determines usage patterns of media agent modules, indexing modules, and/or their host computing devices. Trending analysis predicts growth in usage, e.g., using time series analysis from past history. Each host computing device receives a usage rating based on historical analysis and further based on predicted future usage, e.g., optimal, light, warning, or overload rating. The illustrative migration job re-associates data sources with a different destination media agent and/or index/catalog, including transferring some or all relevant transaction logs and/or indexing information from the old host to the new host. When a next storage operation is initiated, the new associations are applied so that the new host performs the duties formerly assigned to the old host, e.g., data backups performed by a new media agent and/or indexing performed by a new indexing module. In some embodiments, existing storage operations are suspended to allow for the migration job to complete and are then resumed at the new host. Later, if the new host becomes overloaded, another migration job load balances again among components. When no suitable host can be found to take on re-assignments from an overloaded host, alarms raised to administrators indicate that additional resources are needed.
The illustrative migration job runs at a suitable time, e.g., daily, weekly, based on trigger criteria/thresholds, etc., without limitation, and preferably runs separately from and independently of any schedules for data backup. Illustratively, the storage manager manages data collection and analysis for triggering migration jobs, and the collected data are stored in the management database associated with the storage manager and/or at a separate metrics server. This approach enables global analysis and management across the backup system, and even across storage operation cells, triggering migration jobs as needed. In some embodiments, some of the historical data is collected and stored at the host of the media agent and/or index/catalog and obtained from there by the storage manager.
For purposes of summarizing the disclosure, certain aspects, advantages and novel features of the inventions have been described herein. It is to be understood that not necessarily all such advantages may be achieved in accordance with any particular embodiment of the invention. Thus, the invention may be embodied or carried out in a manner that achieves or optimizes one advantage or group of advantages as taught herein without necessarily achieving other advantages as may be taught or suggested herein.
As will be seen from the disclosure herein, certain embodiments of systems and methods are provided for enabling failover during a backup operation. In particular, embodiments of the invention include creating a catalog, or index, of individual objects or files within backup data on a storage device. Inventive systems can also include media agent modules, or other backup components, that further generate a set of transaction logs that identify metadata with respect to new data objects being stored to the backup data. A copy of the index/catalog and transaction logs can be stored at a location accessible by multiple media agent modules. As a result, if one media agent fails during a backup operation, a second media agent can access the transaction logs and the existing index/catalog to resume the backup operation without requiring a restart of the backup process. Such embodiments can also provide means for enabling load balancing or like rotation of media agent modules in completing a common backup operation.
The features of the systems and methods will now be described with reference to the drawings summarized above. Throughout the drawings, reference numbers are re-used to indicate correspondence between referenced elements. The drawings, associated descriptions, and specific implementation are provided to illustrate embodiments of the invention and not to limit the scope of the disclosure.
In addition, methods and functions described herein are not limited to any particular sequence, and the acts or blocks relating thereto can be performed in other sequences that are appropriate. For example, described acts or blocks may be performed in an order other than that specifically disclosed, or multiple acts or blocks may be combined in a single act or block.
As shown, the backup system 100 comprises at least one storage device 102 for storing backup data 104. The storage device 102 may include any type of media capable of storing electronic data, such as, for example, magnetic storage (such as a disk or a tape drive), optical media, or other type of mass storage. In certain embodiments, the storage device 102 can be part of a storage area network (SAN), a Network Attached Storage (NAS), a virtual machine disk, combinations of the same or the like.
In certain embodiments, the storage device(s) 102 may be implemented as one or more storage “volumes” that include physical storage disks defining an overall logical arrangement of storage space. For instance, disks within a particular volume may be organized as one or more groups of redundant arrays of independent (or inexpensive) disks (RAID). In certain embodiments, the storage device(s) 102 may include multiple storage devices of the same or different media.
Storage of the backup data 104 to the storage device 102 is performed by media agent modules or devices 106A and 106B (collectively referred to by reference numeral “106”). In general, the media agent devices 106 comprise storage controller computers that serve as intermediary devices and/or means for managing the flow of data from, for example, client information stores to individual storage devices. For instance, the media agent 106 can comprise a module that conducts data between one or more source devices, such as a client computing device, and the storage device(s) 102.
In certain embodiments, the media agents 106 store the backup data 104 on the storage device 102 as a plurality of data chunks. The terms “chunk” and “data chunk” as used herein are broad terms and are used in their ordinary sense and include, without limitation, a portion of data having a payload and encapsulated with metadata describing the contents of the payload placed in a tag header of the chunk. In certain embodiments, a chunk represents the smallest restorable component (e.g., 512 megabytes) of an archive or backup file.
In certain embodiments, the media agent 106 is communicatively coupled with and controls the storage device 102. For example, the media agent 106 may instruct the storage device 102 to use a robotic arm or other means to load or eject a media cartridge, and/or to archive, migrate, or restore application-specific data. In certain embodiments, the media agent 106 communicates with the storage device 102 via a local bus, such as a Small Computer System Interface (SCSI) adaptor. In some embodiments, the storage device 102 is communicatively coupled to the media agent 106 via a SAN.
Each media agent 106 can further maintain an index cache that stores index data generated during backup, data migration/relocation, and restore operations as further described herein. Such index data provides the backup system 100 with an efficient and intelligent mechanism for locating backed up objects and/or files during restore or recovery operations. For example, the index data can include metadata such as file/object name(s), size, location, offset, checksum and the like of backup data 104 stored on the storage device 102. The index cache is illustratively configured at the computing device that hosts the media agent 106.
Once a backup operation is complete, the index data is generally stored as an index 108 with the data backed up to the storage device 102. This advantageously facilitates access to the files and/or objects within the backup data when performing a restore operation. However, with conventional backup systems, in the event that there is a failure during backup of the data 104, a complete and accurate representation of the backed up data is not stored on the storage device 102. Thus, such failures oftentimes result in a restarting of the backup process and a re-creation of the index data.
To provide for failover during backup operations, the media agents 106 of the backup system 100 are further configured to generate one or more transaction logs for each data chunk backed up to the storage device 102. Such transaction logs can maintain similar information as entries of the index 108 (e.g., object name, size offset, length, checksum, time stamp, combinations of the same or the like). Once a particular data chunk is committed to, or stored on, the storage device 102, the corresponding transaction log(s) are uploaded or transmitted on-the-fly to a main index, or catalog, 110.
The catalog 110, in certain embodiments, represents a copy of the most recent index 108 stored with the backup data 104 on the storage device 102. Like the index 108, the catalog 110 entries contain sufficient information to restore one or more files or blocks from the last completed backup operation. When used in combination with uploaded transaction logs, the catalog 110 can be advantageously used to resume a backup operation that terminates prematurely or otherwise interrupted, such as from a failure of a media agent 106.
The catalog 110 is advantageously accessible to each of the media agents 106 such that if a first media agent (e.g., media agent 106A) fails while performing a backup operation, a second media agent (e.g., media agent 106B) can access the catalog 110 and resume the backup operation in place of the first media agent. For instance, in certain embodiments, the catalog 110 can be stored on a server or other computing device (e.g., indexing server) separate from the media agents 106. In yet other embodiments, the catalog 110 can be maintained by a storage manager 112. It will also be appreciated that catalog 110 can represent a computing device, such as a server computer, that maintains the catalog or index.
In certain embodiments, the storage manager 112 comprises a module or application that coordinates and controls storage, data migration/relocation, recovery and/or restore operations within the backup system 100. For instance, such operations can be based on one or more storage policies, schedules, user preferences or the like. As shown, the storage manager 112 can communicate with each of the media agents 106 and the catalog 110. In yet further embodiments, the storage manager 112 can communicate with the storage device(s) 102.
Although the backup system 100 is shown and described with respect to particular arrangements, it will be understood from the disclosure herein that other embodiments of the invention can take on different configurations. For instance, the backup system 100 can comprise a plurality of media agent modules or devices that each communicate with one or more storage devices and/or one or more client devices.
Furthermore, components of the backup system 100 can also communicate with each other via a computer network. For example, the network may comprise a public network such as the Internet, virtual private network (VPN), token ring or TCP/IP based network, wide area network (WAN), local area network (LAN), an intranet network, point-to-point link, a wireless network, cellular network, wireless data transmission system, two-way cable system, interactive kiosk network, satellite network, broadband network, baseband network, combinations of the same or the like.
At Block 205, the process 200 begins a backup operation performed by a media agent device 106. For example, the storage manager 112 may instruct the media agent device 106 to back up data relating to one or more applications executing on one or more client computing devices. As discussed, in certain embodiments, the media agent 106A stores the backup data 104 on the storage device 102 in a chunk-by-chunk manner.
In certain embodiments, the media agent device 106 receives the data to be backed up from one or more data agents operating on a client device. In certain examples, the data can comprise application-specific data or can include data streams with multiple data types or objects contained therein.
At Block 210, the media agent device 106 processes a data chunk of the received data to be backed up. In certain embodiments, such processing includes generating metadata indicative of the contents and/or attributes of the objects within the data chunk or of the data chunk itself, as well as information regarding the storage location of such objects or files on the storage device 102 (e.g., with the backup data 104).
The media agent device 106 then backs up the data chunk to the backup file 104 on the storage device 102 (Block 215). The media agent device 106 also uploads one or more transaction logs to the catalog 110 that contain the above-described metadata for the backed up data chunk (Block 220). In certain embodiments, a single transaction log corresponds to a single data chunk.
At Block 225, the process 200 determines if there are additional data chunks as part of the backup operation. If so, the process 200 returns to Block 210 to process the next data chunk. If not, the process 200 proceeds with Block 230 to store the index 108 with the backup data 104. In certain embodiments, the index 108 allows for restoring individual objects and/or files from the backup data 104. The process 200 also includes applying the uploaded transaction logs to the catalog 110 so that the catalog 110 contains up-to-date information reflecting the contents of the entire backup file 104 (Block 235).
It will be appreciated that the process 200 is not limited to the arrangement of blocks illustrated in
The process 300 begins at Block 305 by initiating a backup operation with the first media agent 106A. At Block 310, the process 300 detects a failure of the first media agent 106A. For instance, in certain embodiments, the storage manager 112 can detect that the first media agent 106A has prematurely ceased performing the backup operation. In one embodiment, the failure of the first media agent 112 causes the backup operation to fail, and during the next system restart, the storage manager 112 detects the failure of the first media agent 106A.
Upon detecting failure of the first media agent 106A, the process 300 obtains a copy of the index associated with the last complete backup (Block 315). For example, the storage manager 112 can instruct the second media agent 106B to retrieve a copy of the index 108 from the storage device 102, the catalog 110 (or a computing device maintaining the catalog 110) or the like. In certain embodiments, the retrieved index contains information for retrieving objects and/or files that were stored on the storage device 102 prior to the commencement of the current backup operation (e.g., the most recently completed full backup).
At Block 320, the second media agent 106B also retrieves a copy of the transaction log(s) associated with the interrupted backup operation by the first media agent 106A. In certain embodiments, the transaction logs are stored on the catalog server 110 as a result of Block 220 of the process 200. For instance, the storage manager 112 may instruct that the transaction logs be sent to the second media agent 106B along with instructions to the second media agent 106B to take over the interrupted backup operation.
At Block 325, the second media agent 106B applies the transaction logs to the retrieved index to the point that reflects where in the backup process the first media agent 106A failed. The second media agent 106B is then able to resume the backup operation without needing to repeat the backup of data that was performed by the first media agent 106A (Block 330). For instance, the second media agent 106B can continue backing up the data according to the process 200 depicted in
Although the process 300 has been described with respect to detecting a failure of a media agent device, other embodiments of the invention can utilize similar steps to achieve load balancing or other selective use of multiple media agents during a single backup operation. For example, at Block 310, the storage manager 112 or other component can determine if the first media agent 106A is operating under unbalanced and/or excessive load. Such an embodiment allows for the second media agent 106B to take over the backup operation prior to a failure of the first media agent 106A. For instance, the storage manager 112 can monitor bandwidth usage, a jobs queue and/or a schedule of the first media agent 106A to evaluate its load.
In certain embodiments of the invention, the backup operations disclosed herein can be used to copy data of one or more applications residing on and/or being executed by a computing device. For instance, the applications may comprise software applications that interact with a user to process data and may include, for example, database applications (e.g., SQL applications), word processors, spreadsheets, financial applications, management applications, e-commerce applications, browsers, combinations of the same or the like. For example, in certain embodiments, the applications may comprise one or more of the following: MICROSOFT EXCHANGE, MICROSOFT SHAREPOINT, MICROSOFT SQL SERVER, ORACLE, MICROSOFT WORD and LOTUS NOTES.
Moreover, in certain embodiments of the invention, data backup systems and methods may be used in a modular storage management system, embodiments of which are described in more detail in U.S. Pat. No. 7,035,880, issued Apr. 5, 2006, and U.S. Pat. No. 6,542,972, issued Jan. 30, 2001, each of which is hereby incorporated herein by reference in its entirety. For example, the disclosed backup systems may be part of one or more storage operation cells that includes combinations of hardware and software components directed to performing storage operations on electronic data. Exemplary storage operation cells usable with embodiments of the invention are described in U.S. Pat. No. 7,454,569, issued Nov. 18, 2008, which is hereby incorporated herein by reference in its entirety.
Like index/catalog 110, index/catalog 410 is a data structure comprising information sufficient to locate and restore data backed up in earlier storage operations—so long as those storage operations were indexed to index/catalog 410. Like index/catalog 110, index/catalog 410 is in communication with storage manager 112 and with one or more media agents 106 (e.g., media agents 106A and 106B). Illustratively, each index/catalog is stored and maintained in cache memory at the host computing device, e.g., 506, 520. The amount of cache memory used by a given index/catalog is used in some embodiments as criteria for migrating the index/catalog to another host.
In contrast to a single centralized “main” index/catalog 110 as envisioned in
Management database 512 is a logical, but not necessarily a physical, component of storage manager 112. Management database stores system preferences and status information about storage operations that occurred (or failed) system 100/400.
Each host computing device (e.g., 520, 506A, 506B) comprises one or more hardware data processors and computer memory for storing program instructions, cache memory, and optionally mass storage resources. Illustratively, index/catalogs 110, 410 are stored in cache memory at the host computing device. Indexing host 520 and media agent/indexing host 506B both are shown hosting index/catalog 110 in this figure to illustrate alternative embodiments.
In a given embodiment, index/catalog 110 is configured in one of host 520 OR host 506B, but not both. In a migration job, index/catalog 110 migrates from host 520 to host 506B or vice-versa for load balancing purposes, e.g., migrating to a more lightly loaded host. More details are given in other figures herein. There is no limit to the number of distinct indexing hosts 520 in the illustrative backup systems. Illustratively, indexing hosts operate mutually independently. Thus, a first indexing host performs its functions asynchronously and autonomously relative to a second indexing host, regardless of whether the type of indexing technology used (e.g., ctree, solr, SQL, etc.) is the same or different.
Transaction logs 610 are described in more detail elsewhere herein and are generated by media agents performing storage operations, e.g., backup operations performed by media agent 106A, without limitation. Illustratively, any number of transaction logs 610 can be stored at indexing server 520, received from any number of media agents 106 in system 400. In some embodiments, transaction logs 610 are received from systems outside system 400 and added to indexing server 520.
A plurality of indexing modules are illustratively installed on, configured, and hosted by indexing server 520, including indexing modules 620 and 640, and others depicted by the dots emanating from module 640, without limitation. Illustratively, indexing module 620 performs ctree indexing by processing one or more transaction logs 610, and resulting in ctree index/catalog 110. Illustratively, indexing module 640 performs solr indexing by processing one or more transaction logs 610 (not necessarily the same transaction logs processed by module 620), resulting in solr index/catalog 410. Illustratively, another indexing module (not shown here) performs SQL database indexing by processing one or more transaction logs 610 (not necessarily the same transaction logs processed by modules 620/640), resulting in a corresponding SQL index/catalog (not shown here). As noted elsewhere herein, the types of indexing modules and the corresponding index/catalogs they generate and maintain are diverse and more numerous than what is depicted in the present figure. In some embodiments, multiple indexing modules of the same type co-exist in the system, whether on the same or different indexing hosts. Different embodiments will implement different types of indexing modules depending on the nature of the source data whose backups are indexed.
Each index/catalog (e.g., 110, 410, etc.) is backed up at one or more suitable times. Criteria for backing up each index/catalog may vary among the various types of index/catalogs, but in some embodiments will be the same throughout system 400. Illustratively, index/catalog 110 is backed up to one or more copies 651. Illustratively, index/catalog 410 is backed up to one or more copies 654. Catalog backup copies 651 and 654 are shown here stored to the same data storage device 650, but the invention is not so limited. In some embodiments, backup copies 651 and 654 are stored to different data storage devices. In some embodiments data storage 650 is the same as data storage device 102, which stores backup data 104, as shown in
The arrows depict logical data flows. The dotted arrows in host 520 from transaction logs 610 to solr indexing modules 640 indicate that every transaction log 610 does not necessary go to every indexing module. In some embodiments all transaction logs 610 transmitted to a first indexing module are also transmitted to another like indexing module that generates a replication index of the first—see
At block 705, rules for deciding indexing destination(s) are defined. Illustratively, the rules (indexing preferences) are stored in management database 512. In some embodiments, the rules are defaulted into system preferences and do not require administration. The rules define different indexing technologies and/or destinations for various data sources in system 400, illustratively through the use of storage policies that indicate how source data sets are to be treated. For example, a storage policy for a data source that is a file system indicates that a first index/catalog (e.g., ctree type) is the indexing destination for the data source, e.g., 110; alternatively the storage policy indicates that a first indexing technology (e.g., ctree, etc.) is to be used for the data source; alternatively the storage policy indicates a host computing device (e.g., 506B, 520) is the indexing destination, predicated on the host determining a suitable indexing module (e.g., 620, 640) for processing transaction logs for the data source. For example, a storage policy for a data source that is metadata-rich (e.g., OneDrive, SharePoint, Exchange, etc.) indicates that a second index/catalog (e.g., solr type, elasticsearch type, etc.) is the indexing destination for the data source, e.g., 410; alternatively the storage policy indicates that a second indexing technology (e.g., solr, elasticsearch, etc.) is to be used for the data source; alternatively, a host (e.g., 520) is indicated. For example, a storage policy for a data source that is a structured database managed by a database management system (e.g., Oracle) indicates that another index/catalog (e.g., database type) is the indexing destination; alternatively the storage policy indicates that a third indexing technology (e.g., Oracle DBMS, etc.) is to be used for the data source; alternatively, a host (e.g., 520) is indicated.
At block 710, the media agent (e.g., 106A, 106B) that handles storage operations (e.g., backups, archiving, etc.) for a given data source receives the aforementioned rules (indexing preferences). In some embodiments, they are received from storage manager 112, e.g., one-time transmission, transmitted with instructions for starting every storage operation/job, such as when storage manager 112 triggers a backup operation for a given data source. In some embodiments, the rules (indexing preferences) are received from a data agent operating on a client device with access to the source data. In some embodiments, the rules (indexing preferences) are received from the indexing destination itself, e.g., indexing module 620, 640, etc. or from its host computing device, e.g., 106B, 520, etc. In some embodiments the rules (indexing preferences) are programmed/configured into media agent 106, and are thus obtained locally from system configurations.
At block 715, the storage operation (e.g., backup) is performed at least in part by media agent 106. In some embodiments, the media agent performs the operation in conjunction with a data agent operating on a client device with access to the source data. Media agent 106 generates one or more backup data 104 from the source data and further generates one or more transaction logs 610. Notably, completion of the storage operation does NOT depend on whether the generated transaction logs have been indexed. Rather, blocks 720, 725, and 735 occur asynchronously with block 715. Likewise, block 735 also is asynchronous with blocks 720, 725, and 735.
At block 720, media agent 106 determines a suitable indexing destination for the transaction logs 610 based on the rules (indexing preferences) received at block 710. Accordingly, media agent 106 transmits transaction logs 610 to the indexing destination, e.g., indexing host 520, media agent/indexing host 506B, etc. In embodiments where media agent 106 executes on the same host computing device as the destination indexing module, e.g., on a media agent/indexing host 506B, media agent 106 transmits transaction logs 610 locally to the indexing module. Control passes to block 725 for handling by a first indexing module, to block 730 for handling by a second indexing module, or to another block (not shown) for handling by another indexing module, without limitation. Preferably, after the media agent transmits transaction logs to an indexing destination (and/or to an as-is repository in some embodiments), media agent 106 purges the transaction logs from its local storage to make room for more transaction logs, but the invention is not so limited.
At block 725, a first indexing module, e.g., 620, 640, etc., processes the transaction logs received from the media agent. The processing extracts and applies the information (e.g., metadata) in the transaction logs into a corresponding index/catalog generated and maintained by the indexing module, e.g., 110, 410, etc. Thus, information from transaction logs from a storage operation such as a backup of certain source data is transformed into updates to an index/catalog that tracks metadata, which is associated with the source data, with the storage operation, and/or with results of the backup operation, such as backup data chunks. The type of indexing technology of the first indexing module, e.g., ctree, solr, elasticsearch, SQL, etc., determines the type (structure, organization, schema) of the resultant index/catalog. Control passes back to block 710 (not shown) for performing further storage operations having the same or different indexing preferences. Control also passes to block 735.
At block 730, a second indexing module, of a type that is different from the first indexing module in block 725, processes transaction logs received from media agent 106. As in block 725, the type of indexing technology of the second indexing module, e.g., ctree, solr, elasticsearch, SQL, etc., determines the type (structure, organization, schema) of the resultant index/catalog. Control passes back to block 710 (not shown) for performing further storage operations having the same or different indexing preferences. Control also passes to block 735.
At block 735, process 700 backs up one or more index/catalogs based on respective criteria. Illustratively, each index/catalog is backed up independently of other index/catalogs in system 400, based on respective criteria associated with the particular index/catalog. Illustratively, indexing preferences such as a policy or other criteria govern when an index/catalog is to be backed up and where the backed up index/catalog is to be stored. Illustratively, criteria are stored in management database 512 and storage manager 112 triggers the backup operation. Examples of criteria that trigger an index/catalog backup job include one or more of: a time of day; a number and/or certain types of storage operations performed upon data sources tracked by the index, e.g., back up the index/catalog after each full backup of a source file system, or back up the index/catalog after every other incremental backup of the source file system, etc.; a number of transaction logs as yet not applied to the index, i.e., keeping no more than a threshold number of unprocessed transaction logs; a system event such as an upgrade to one or more system components such as data agents, media agents, storage manager, media agent/indexing host; instructions received from another component, such as from a metrics server or from another storage system; on demand; etc., without limitation. Index/catalogs are backed up to the same or different storage devices than backup data according to preferences, e.g., storage device 102, storage device 650, etc. Each backup copy of an index/catalog (e.g., 651, 654, etc.) is associated with a point-in-time, and can be used at another time to restore the index/catalog.
At block 740, process 700 serves search results from one or more index/catalogs such as 110, 410, etc. Illustratively, a user interface operates in system 100/400 for enabling user searching of index/catalog entries. Illustratively a user interface is provided by a web console in communication with storage manager 112. Storage manager 112 processes user queries, including adding/populating additional information into each query, e.g., client information, etc., before directing the query to the various indexing hosts. According to some embodiments, the storage manager appoints one of the indexing hosts as the query manager, whereas in other embodiments an indexing host that hosts the most index/catalogs appoints itself the query manager. The query manager directs the query to other indexing hosts in the backup system. Each indexing host runs the query locally against one or more index/catalogs on the host and transmits results to the query manager. The query manager aggregates query results and transmits them to the user interface, e.g., at the web console, illustratively bypassing the storage manager.
The backup system (e.g., using storage manager 112) illustratively determines usage patterns of media agent modules, indexing modules, and/or their host computing devices. Trending analysis predicts growth in usage, e.g., using time series analysis from past history. Each host computing device receives a usage rating based on historical analysis and further based on predicted future usage, e.g., optimal, light, warning, or overload rating. Disk usage is one exemplary factor for measuring load for a host, but the invention is not so limited. The illustrative migration job re-associates data sources (e.g., one or more subclients or backup sets) with a different media agent and/or different index/catalog, including transferring some or all relevant transaction logs and/or indexing information from the old host to the new host. The migration job also ensures that the changed associations are updated in system preferences. For example, the changed associations are transmitted to storage manager 112 or other system component, which updates the management database associated therewith, but the invention is not limited to this implementation. When a next storage operation is initiated, the new associations are applied so that the new host performs the duties formerly assigned to the old host, e.g., data backups performed by a new media agent and/or indexing performed by a new indexing module. In some embodiments (see
At block 805, storage manager 112 determines usage patterns for several target components, including indexing modules (e.g., 620, 640), media agents (e.g., 106A, 106B), and/or their respective host computing devices (e.g., 506A, 506B, 520). In some embodiments, block 805 is limited to analyzing computing devices such as hosts 506A, 506B, and 520, without regard to operational characteristics of the software modules executing thereon, such as media agent modules and indexing modules. Usage patterns are generally based on information gathered in past operations. A trending analysis is added to predict usage needs for the next cycle of the respective component. The result is a rating e.g., optimal, light, warning, or overload. More details on block 805 are given in
At block 810, which is a decision point, process 800A determines whether migration criteria have been met. If not, control passes back to block 805. If migration criteria are met, control passes to block 815. An illustrative load classification routine on storage manager 112 determines whether migration is needed from a first host to another host. This process follows the “load rule” below, illustratively for whether to migrate an index/catalog, i.e., for whether migration criteria are met:
At block 815, which is a decision point reached when migration criteria have been met, process 800A determines whether a new host computing device is available as the migration destination. If not, storage manager 112 raises alarms at block 835. If a new host is found, control passes to block 820.
At block 820, process 800A updates associations in system preferences, and in other suitable configurations, to indicate the new indexing modules, new media agents, and/or new host computing device. Storage manager 112 is illustratively responsible for executing the updates, but the invention is not so limited. For example, storage policies that previously specified a first indexing host now are updated to indicate the new indexing host. Likewise, storage policies that previously specified a first media agent or media agent host now are updated to indicate the new media agent and/or host, respectively. And so on.
At block 825, process 800A transfers transaction logs 610 and one or more index/catalogs (e.g., 110, 410, etc.) from a first host computing device (e.g., 506B, 520, etc.) to a second (destination) host computing device. Notably, the second host computing device need not be a never-before-used component in the system, and in some embodiments is already host to another media agent module and/or indexing module, without limitation. A suitable indexing module and/or media agent module also is activated at the destination (second) host. At this point, the pre-migration associations have been updated, the module has been readied for operation, and the migration job is complete.
At block 830, which is reached after the migration job is complete, on a next storage operation, the updated associations are applied and the new (second, destination) host computing device is used. This assures a smooth transition of resources.
At block 835, which is reached if new host computing device cannot be found to off-load a first host for which migration criteria have been met, storage manager 112 raises one or more alarms to notify administrators to take action. Except for block 835, no human intervention is required for the migration job of process 800A.
At block 817, which follows after a suitable migration destination host has been found at block 815, process 800B suspends active storage operations that make use of the component that is about to migrate, e.g., media agent, indexing module, host computing device. Illustratively, storage manager 112 triggers and manages the suspensions, e.g., instructing the components executing the storage operation (e.g., data agent, media agent, indexing module) to quiesce and/or pause until further instructed.
At block 833, which follows after the migration operation is completed at block 825, process 800B resumes the suspended storage operations using the new host computing device. Illustratively, storage manager 112 triggers and manages the resumptions, e.g., instructing the components involved in the storage operation to use the new host when resuming the storage operation. As a result, process 800B assures a smooth transition of resources without requiring storage operations in progress to begin anew. Except for block 835, no human intervention is required for the migration job of process 800B.
At block 905, each host computing device (e.g., media agent host 506A, media agent/indexing host 506B, indexing host 520, etc.) loads its own system usage information into a routine that is part of block 805. Illustratively, this occurs once a day, but the invention is not so limited. System usage information is generally collected by the operating system and/or other utilities that run on the host computing device. These utilities are well known in the art.
At block 910, the host computing device calculates a storage capacity occupied by the index/catalog and/or transaction logs relative to local storage available on the host computing device. When too much of the local memory is used up by the index/catalog and/or transaction logs, the host computing device will tend to experience slower performance and risks running out of space altogether.
At block 915, the host computing device calculates one or more load statistics, e.g., CPU usage from resource monitor log file over a predefined past time period.
At block 920, the host computing device forecasts the load likely to occur based on a time-series statistical analysis, which is a technique well known in the art.
At block 925, the host computing device determines whether the time-series statistical analysis shows a rising or a falling trend; and further calculates a rating of Light, Optimal, Warning, or Overloaded based on the past data and the predicted next cycle load.
At block 930, the host computing device transmits these results (e.g., from blocks 905-925, without limitation) to storage manager 112, which stores the received results to management database 512 for future use.
In alternative embodiments, some or all the above-recited calculations are performed by storage manager 112 rather than by each host computing device.
Example Block 805 Operations. Additional illustrative details in reference to the operations of block 805 are given below. For example, and without limitation, once a day each active media agent host and/or indexing host starts the metrics calculation service, which loads the stored host's system data and calculates static, current, and forecasted metrics. With the metrics calculated, the host sends results to be stored and analyzed by the storage manager 112. In some embodiments, the calculations run at the storage manager 112. In some embodiments, the schedule for when the calculations are run is managed by the storage manager 112.
Illustrative Process at the Host Computing Device, e.g., 506A, 506B, 520, etc.
Exemplary Calculated Metrics. A value is calculated that represents the host based on its capacity and status in a way that can be measured and compared to other hosts. Metrics comprise:
Values are normalized between 0 and 1. The capacity value is calculated every time the load balance task starts, and is defined by the formula:
The load is obtained by getting the current status of the resources in the host computing device. Other features can be added to this analysis as long as we keep the k sum constraint.
Similar to the capacity, the load formula is defined by:
Those values are defaulted to:
The next cycle trend is obtained by calculating the next cycle expected load using a time-series analyzer on the last “N” load figures and then checking if the forecasted load values are rising or falling. After obtaining the forecasted values, the value for k is calculated by counting each time whether the predicted load (W f) is greater than the threshold defined for OPTIMAL (M 2). After that, the averages and load trend are calculated as follows:
The predicted capacity is calculated:
Cf=|C×(1−)−Wtrend|
All data and/or results obtained in this process are illustratively sent to the storage manager for further load balance processing.
Forecasting the Next Cycle. Illustratively, in an exemplary embodiment, the forecasting is done by time-series model analysis, using data loaded from the resource monitor files. The forecasting is for “N” days, “N” being a configurable number of days to forecast a Next Cycle. The basic rule for forecasting is that the bigger the value of “N,” the more historical data is needed for better precision. Default value for the next cycle is seven days. For that value we need at least one month of logged data to use.
Overload Event Message. Illustratively, if in the metrics calculation process the system detects that the host computing device is in WARNING or OVERLOADED state, an event message with critical severity is sent to the system administrator comprising the following information:
Illustrative Load Table. The host computing device should store the collected data to the storage manager 112, comprising the following exemplary fields:
Illustrative Migration Table. The migration jobs use this exemplary table as reference for pending and running migration jobs:
End of Example Operations in Block 805.
Ctree indexing module 620 is depicted here creating and maintaining a plurality of ctree index/catalogs 110, in contrast to solr indexing module 640 in
Replication ctree indexing module 1020 is identical to ctree indexing module 620, but is configured as a replication resource, i.e., as a standby resource for disaster recovery. Although module 1020 is depicted here operating on the same host computing device 520 as the “live” module 620, preferably module 1020 operates on another host computing device that is readily available if host 520 fails, e.g., in a cloud computing account distinct from host 520, in the same or another data center, on a virtual machine distinct from host 520, etc. In some embodiments, both module 620 and module 1020 are configured in the same or distinct cloud computing accounts, so that host 1020 can take over from host 520 in a disaster recovery scenario as a failover destination.
Replication ctree index/catalogs 1010 are generated and maintained by module 1020, based on transaction logs 610. Index/catalogs 1010 are identical to their counterpart index/catalogs 110 generated and maintained by module 620. Index/catalogs 1010, like module 1020, are intended as failover resources and preferably are stored in a distinct host computing device apart from the host of “live” indexing module 620.
Indexing host 1052 is a host computing device, distinct from host 520, that is configured to be a destination for catalog migration jobs such as the one depicted here by the dotted arrows. Illustratively, ctree indexing module 620 migrates to host 1052 in a catalog migration job. In some embodiments, module 620 actually moves from host 520 to host 1052, i.e., no longer operates at host 520, but in other embodiments a second module 620 is activated to operate at host 1052 while the first module 620 continues operating at host 520, e.g., generating index/catalogs 110 for unmigrated subclients. Preferably, the catalog migration job includes transferring existing index/catalogs 110 for the migrating subclients so that existing and future index/catalogs for a given subclient reside at the same host e.g., host 1052. In another catalog migration job (not shown here), a reverse migration causes ctree indexing module 620 and ctree index/catalogs 110 to migrate from host 1052 back to host 520 or to another host computing device based on changed conditions that trigger the migration job.
In regard to replication, any type and any number of index/catalogs, e.g., 110, 410, etc., can be replicated to a respective counterpart using a corresponding replication indexing module (not shown here). Thus, in some embodiments, solr index/catalogs 410 are replicated by a replication solr indexing module, database index/catalogs are replicated by replication database indexing module(s), ctree index/catalogs 110 are replicated by replication ctree indexing module 1020, etc. and/or any combination thereof.
In regard to catalog migration, any type and any number of index/catalogs, e.g., 110, 410, etc., can be migrated to any number of other host computing devices, e.g., 506A, 506B, 520, 1052, etc. In some embodiments, when a new media agent host computing device is brought online in an illustrative backup system, storage manager 112 triggers a catalog migration analysis to determine whether criteria are met for launching catalog migration job(s) to the newly operational host computing device. Thus, the illustrative backup systems keep themselves load balanced on an ongoing basis without administrator intervention, unless new host computing resources are needed. After new host computing resources are added, the illustrative backup systems evaluate load balancing needs and launch migration jobs(s) accordingly.
In regard to the figures described herein, other embodiments are possible within the scope of the present invention, such that the above-recited components, steps, blocks, operations, messages, requests, queries, instructions, and/or responses are differently arranged, sequenced, sub-divided, organized, and/or combined. In some embodiments, a different component may initiate or execute a given operation and/or store certain data.
Example Embodiments. Some example enumerated embodiments of the present invention are recited in this section in the form of methods, systems, and non-transitory computer-readable media, without limitation.
According to an exemplary embodiment, a method comprises: by a first media agent executing on a first computing device, generating first backup data from a first data source, wherein the first computing device comprises one or more hardware processors; by the first media agent, storing the first backup data to one or more storage devices that are communicatively coupled to the first media agent; by the first media agent, generating one or more first log files, wherein the one or more log files are based on one or more of: the generating of the first backup data and the storing of the first backup data, and wherein the one or more log file comprise information for locating the first backup data at the one or more storage devices; by the first media agent, transmitting the one or more first log files to a first index that is configured to enable restoring backup files generated by at least the first media agent, including restoring first backup files from the first backup data; and wherein the first index is updated by applying the one or more first log files to the first index. The above-recited method further comprising: migrating the first media agent from the first computing device to a second computing device, wherein an association between the first backup data and the first media agent is updated to indicate that the first media agent resides at the second computing device; and by the first media agent executing at the second computing device, restoring an individual data file from the first backup data based on using the first index. The above-recited method wherein the first index is maintained at a second computing device that is distinct from the first computing device, and wherein the second computing device comprises one or more hardware processors; and wherein the first index is backed up when index-backup criteria are met that are distinct from a timeframe for the generating of the first backup data. The above-recited method further comprising: by the first media agent, storing the one or more first log files to at least one of: the first computing device, and a second storage device associated with the first computing device, wherein the second storage device is distinct from the one or more storage devices where the first backup data is stored. The above-recited method wherein the transmitting of the one or more first log files to the first index is at a first time after a storage operation that generated the first backup data has completed.
The above-recited method wherein the first index is maintained at a second computing device that is distinct from the first computing device, and wherein the first index is one of a first plurality of indexes maintained at the second computing device using ctree indexing technology; wherein after the first index migrates to a third computing device that is distinct from the second computing device, at least one other of the first plurality of indexes remains at the second computing device and is maintained thereon by the ctree indexing technology; and wherein the first index is maintained at the third computing device by a ctree indexing technology that executes at the third computing device. The above-recited method further comprising: migrating the first index from a second computing device to a third computing device, wherein an association between the first backup data and the first index is updated to indicate that the first index resides at the third computing device. The above-recited method wherein the first index is based on a first type of indexing technology, and wherein the first index is associated with the first data source, and further comprising: by the first media agent, transmitting second log files to a second index that is based on a second type of indexing technology that differs from the first type, wherein the second log files are based on generating second backup data from a second data source, and wherein the second index is updated by applying the second log files to the second index, and wherein the second index is associated with the second data source. The above-recited method wherein the first media agent is configured to choose between the first index and the second index based on a type of data source being backed up. The above-recited method wherein a storage manager instructs the first media agent to transmit the first log files to the first index and to transmit the second log files to the second index based on one or more preferences that govern a choice of index, and wherein the storage manager comprises one or more hardware processors. The above-recited method wherein a first data agent that transmits data to the first media agent for generating the first backup data instructs the first media agent to transmit the first log files to the first index; and wherein a second data agent that transmits data to the first media agent for generating the second backup data instructs the first media agent to transmit the second log files to the second index.
According to another exemplary embodiment, a storage system comprises: a first computing device comprising one or more hardware processors and computer memory; a second computing device comprising one or more hardware processors and computer memory; wherein the first computing device is configured to: at a first time, perform a first backup operation that generates first backup data from a first data source, stores the first backup data to one or more storage devices that are communicatively coupled to the first computing device, and generates first log files, and at a second time, transmit the first log files to a first index for tracking backup data generated by at least the first computing device, including the first backup data; and wherein the second computing device is configured to: use a first indexing technology to update the first index by applying the first log files to the first index, and at a third time, after applying the first log files to the first index, cause the first index to be backed up to a backup index. The above-recited system further comprising: wherein the second time is after the first backup operation completes. The above-recited system wherein the first index is backed up when index-backup criteria are met that are distinct from a timeframe for performing the first backup operation. The above-recited system wherein the first index is one of a plurality of indexes in the system, and wherein each index in the plurality of indexes is maintained by a respective indexing module using a respective type of indexing technology, and wherein each indexing module is associated with one or more data sources. The above-recited system further comprising: a third computing device comprising one or more hardware processors and computer memory, wherein the third computing device is configured to: determine that one or more criteria for migration are met by the second computing device that comprises the first index, based at least in part on an amount of storage space occupied by the first index, and cause the first index to migrate from the second computing device to a fourth computing device, wherein an association between the first backup data and the first index is updated to indicate that the first index resides at the fourth computing device.
The above-recited system wherein the first index is one of a first plurality of indexes maintained at the second computing device using ctree indexing technology; wherein after the first index migrates to the fourth computing device, at least one other of the first plurality of indexes remains at the second computing device and is maintained thereon by the ctree indexing technology; and wherein the first index is maintained at the fourth computing device by a ctree indexing technology that executes at the fourth computing device. The above-recited system wherein the first index is generated using a first indexing technology; and wherein the first computing device is further configured to: transmit second log files to a second index which is maintained by a second indexing technology of a different type from the first indexing technology, wherein the second log files are based on generating second backup data from a second data source, wherein the second indexing technology is associated with the second data source, and wherein the second index is updated by applying the second log files to the second index. The above-recited system wherein preferences in the system govern a choice of index based on a type of data source, and further comprising: a third computing device comprising one or more hardware processors and computer memory, wherein the third computing device is configured to: instruct the first computing device to transmit the first log files to the first index based on the preferences that govern the choice of index for the first data source, and instruct the first computing device to transmit second log files to a second index based on backing up a second data source, wherein the first data source is of a different type from the second data source, wherein the first index is of a first type associated with the first data source, and wherein the second index is of a second type associated with the second data source. The above-recited system wherein the second computing device is further configured to: by the first media agent, restore an individual data file from the first backup data based on using the first index.
According to an illustrative embodiment, a method of generating, storing, and restoring backup data comprises: generating first backup data from a first data source, by a first media agent executing on a first computing device, wherein the first computing device comprises one or more hardware processors; by the first media agent, storing the first backup data to one or more first storage devices; by the first media agent, generating one or more first log files based on the generating and the storing of the first backup data; by the first media agent, storing the one or more first log files to the one or more first storage devices; by the first media agent, transmitting the one or more first log files to a first index of a first type, wherein the first type is associated with the first data source, and wherein the first index is updated by applying the one or more first log files to the first index. The above-recited method further comprising: by the first media agent, transmitting second log files to a second index of a second type that differs from the first type, wherein the second log files are based on generating second backup data from a second data source, wherein the second type is associated with the second data source, and wherein the second index is updated by applying the second log files to the second index. The above-recited method wherein the first index is maintained at a second computing device that is distinct from the first computing device, and wherein the first index is backed up when index-backup criteria are met that are distinct from a timeframe for the generating of the first backup data; and wherein the second computing device comprises one or more hardware processors. The above-recited method further comprising: by the first media agent, storing the one or more first log files to at least one of: the first computing device, and a second storage device associated with the first computing device, wherein the second storage device is distinct from the one or more storage devices where the first backup data is stored. The above-recited method wherein the transmitting to the first index is at a first time, and wherein the transmitting to the second index is at a second time after a storage operation that generated the first backup data has completed. The above-recited method wherein the first media agent is configured to choose between the first index and the second index based on a type of data source being backed up. The above-recited method wherein a storage manager instructs the first media agent to transmit the first log files to the first index and to transmit the second log files to the second index based on one or more preferences that govern a choice of index to be used for a type of data source coincident with the first data source.
The above-recited method wherein a first data agent that transmits data to the first media agent for generating the first backup data instructs the first media agent to transmit the first log files to the first index; and wherein a second data agent that transmits data to the first media agent for generating the second backup data instructs the first media agent to transmit the second log files to the second index. The above-recited method further comprising: by a storage manager, determining whether to direct a search for one or more objects in backup data to the first index or to the second index. The above-recited method further comprising: migrating the first index from a second computing device to a third computing device, wherein an association between the first backup data and the first index is updated to indicate that the first index resides at the third computing device. The above-recited method further comprising: by a storage manager comprising one or more hardware processors, determining that one or more criteria for migration are met by the first computing device; and by the storage manager, causing the first index to migrate from the first computing device to a second computing device, wherein an association between the first backup data and the first index is updated to indicate that the first index resides at the second computing device. The above-recited method further comprising: migrating the first media agent from the first computing device to a second computing device, wherein an association between the first backup data and the first media agent is updated to indicate that the first media agent resides at the second computing device; and by the first media agent, restoring an individual data file from the first backup data based on using the first index at the second computing device.
According to another illustrative embodiment, a system comprises: a first computing device comprising one or more hardware processors and computer memory; a second computing device comprising one or more hardware processors and computer memory; wherein the first computing device is configured to: at a first time, perform a first backup operation that generates first backup data from a first data source, store the first backup data to one or more storage devices that are communicatively coupled to the first computing device, generate first log files based on the first backup operation, wherein the first log files comprise information for locating the first backup data at the one or more storage devices, and store the first log files to at least one of: the first computing device, and the one or more storage devices that store the first backup data, and at a second time, after the first backup operation completes, transmit the first log files to a first index for keeping track of backup data generated by at least the first computing device, including the first backup data; and wherein the second computing device is configured to update the first index by applying the first log files to the first index, and is further configured to, at a third time after applying the first log files to the first index, cause the first index to be backed up to a backup index.
The above-recited system further comprising: wherein the first index is one of a plurality of indexes in the system, and wherein each index in the plurality is maintained by a respective indexing module using a respective type of indexing technology, and wherein each indexing module is associated with one or more data sources. The above-recited system further comprising: wherein the first index is one of a plurality of indexes in the system that are stored at the second computing device, and wherein each index in the plurality is maintained by a respective indexing module that executes at the second computing device and uses a respective type of indexing technology that is associated with one or more types of data sources in the system. The above-recited system further comprising: a third computing device comprising one or more hardware processors and computer memory, wherein the third computing device is configured to: determine that one or more criteria for migration are met by the second computing device that comprises the first index, based at least in part on an amount of storage space occupied by the first index, and cause the first index to migrate from the second computing device to a fourth computing device, wherein an association between the first backup data and the first index is updated to indicate that the first index resides at the second computing device. The above-recited system wherein the first index is generated using a first indexing technology; and wherein the first computing device is further configured to: transmit second log files to a second index which is generated using a second indexing technology, wherein the second log files are based on generating second backup data from a second data source, wherein the second indexing technology is associated with the second data source, and wherein the second index is updated by applying the second log files to the second index. The above-recited system further comprising: a third computing device comprising one or more hardware processors and computer memory, wherein the third computing device is configured to: instruct the first computing device to transmit the first log files to the first index based preferences that govern a choice of index to be used for a first type of data source coincident with the first data source, and instruct the first computing device to transmit second log files to a second index generated from backing up a second data source a second type that differs from the first type of the first data source, based on preferences that govern a choice of index to be used for the second type of data source.
According to yet another illustrative embodiment, a method comprises: by a storage manager, initiating a first backup operation with a first media agent, wherein the first media agent receives instructions from the storage manager, wherein the first media agent executes on a first computing device comprising one or more hardware processors, and wherein the storage manager executes on a second computing device, distinct from the first computing device, and comprising one or more hardware processors; in response to instructions, performing a first backup operation by the first media agent at a first time, wherein the backup operation generates first backup data from a first data source and causes the first backup data to be stored to one or more storage devices that are communicatively coupled to the first media agent; by the first media agent, generating one or more log files based on the first backup operation, and storing the one or more log files to at least one of: the first computing device, and the one or more storage devices that store the first backup data; by the first media agent, at a second time after the first backup operation completes, transmitting the one or more log files to a first index, wherein the one or more log files comprise information about the first backup data, and wherein the first index is configured to enable restoring a plurality of backup data generated by at least the first media agent, including the first backup data; and wherein the index resides on a third computing device that is distinct from the first computing device and comprises one or more hardware processors, and wherein the first index is kept up-to-date by applying the one or more log files to the first index by the storage manager, determining that one or more criteria for migration are met by the third computing device; by the storage manager, causing the first index to migrate from the third computing device to a fourth computing device, wherein an association between the first data source and the first index is updated to indicate that the first index resides at the fourth computing device. The above-recited method wherein the one or more criteria for migration are based on an amount of cache storage space occupied by the first index at the third computing device.
The above-recited method wherein the first index is one of a first plurality of indexes maintained at the third computing device using ctree indexing technology, and wherein after the first index migrates to the fourth computing device, at least one other of the first plurality of indexes remains at the third computing device and is maintained thereon by the ctree indexing technology, and wherein the first index is maintained at the fourth computing device by ctree indexing technology that executes at the fourth computing device. The above-recited method wherein rules for determining which type of index/catalog tracks a given data source favor choosing solr technology (alternatively, elasticsearch) for data sources that are relatively rich in metadata; when the data source is a file system or network attached storage, which is relatively metadata-poor compared to the above-mentioned sources, the illustrative rules favor choosing ctree indexing technology; and when the data source is a structured database (e.g., managed by a database management system, such as an Oracle database), the rules favor SQL database technology or the like. The above-recited method wherein file system data from a first source device is assigned to a first ctree index/catalog at the third computing device, whereas database data from the first source is assigned to an SQL index/catalog on the third computing device or on the fourth computing device.
In other embodiments, a system or systems may operate according to one or more of the methods and/or computer-readable media recited in the preceding paragraphs. In yet other embodiments, a method or methods may operate according to one or more of the systems and/or computer-readable media recited in the preceding paragraphs. In yet more embodiments, a computer-readable medium or media, excluding transitory propagating signals, may cause one or more computing devices having one or more processors and non-transitory computer-readable memory to operate according to one or more of the systems and/or methods recited in the preceding paragraphs.
Systems and modules described herein may comprise software, firmware, hardware, or any combination(s) of software, firmware, or hardware suitable for the purposes described herein. Software and other modules may reside on servers, workstations, personal computers, computerized tablets, PDAs, and other devices suitable for the purposes described herein. Software and other modules may be accessible via local memory, via a network, via a browser, or via other means suitable for the purposes described herein. Data structures described herein may comprise computer files, variables, programming arrays, programming structures, or any electronic information storage schemes or methods, or any combinations thereof, suitable for the purposes described herein. User interface elements described herein may comprise elements from graphical user interfaces, command line interfaces, and other interfaces suitable for the purposes described herein.
Embodiments of the invention are also described above with reference to flow chart illustrations and/or block diagrams of methods, apparatus (systems) and computer program products. It will be understood that each block of the flow chart illustrations and/or block diagrams, and combinations of blocks in the flow chart illustrations and/or block diagrams, may be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the acts specified in the flow chart and/or block diagram block or blocks.
These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to operate in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the acts specified in the flow chart and/or block diagram block or blocks. The computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operations to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the acts specified in the flow chart and/or block diagram block or blocks.
While certain embodiments of the inventions have been described, these embodiments have been presented by way of example only and are not intended to limit the scope of the disclosure. Indeed, the novel methods and systems described herein may be embodied in a variety of other forms; furthermore, various omissions, substitutions and changes in the form of the methods and systems described herein may be made without departing from the spirit of the disclosure. The accompanying claims and their equivalents are intended to cover such forms or modifications as would fall within the scope and spirit of the disclosure.
Terminology. Conditional language, such as, among others, “can,” “could,” “might,” or “may,” unless specifically stated otherwise, or otherwise understood within the context as used, is generally intended to convey that certain embodiments include, while other embodiments do not include, certain features, elements and/or steps. Thus, such conditional language is not generally intended to imply that features, elements and/or steps are in any way required for one or more embodiments or that one or more embodiments necessarily include logic for deciding, with or without user input or prompting, whether these features, elements and/or steps are included or are to be performed in any particular embodiment.
Unless the context clearly requires otherwise, throughout the description and the claims, the words “comprise,” “comprising,” and the like are to be construed in an inclusive sense, as opposed to an exclusive or exhaustive sense, i.e., in the sense of “including, but not limited to.” As used herein, the terms “connected,” “coupled,” or any variant thereof means any connection or coupling, either direct or indirect, between two or more elements; the coupling or connection between the elements can be physical, logical, or a combination thereof. Additionally, the words “herein,” “above,” “below,” and words of similar import, when used in this application, refer to this application as a whole and not to any particular portions of this application. Where the context permits, words using the singular or plural number may also include the plural or singular number respectively. The word “or” in reference to a list of two or more items, covers all of the following interpretations of the word: any one of the items in the list, all of the items in the list, and any combination of the items in the list. Likewise, the term “and/or” in reference to a list of two or more items, covers all of the following interpretations of the word: any one of the items in the list, all of the items in the list, and any combination of the items in the list.
In some embodiments, certain operations, acts, events, or functions of any of the algorithms described herein can be performed in a different sequence, can be added, merged, or left out altogether (e.g., not all are necessary for the practice of the algorithms). In certain embodiments, operations, acts, functions, or events can be performed concurrently, e.g., through multi-threaded processing, interrupt processing, or multiple processors or processor cores or on other parallel architectures, rather than sequentially.
Systems and modules described herein may comprise software, firmware, hardware, or any combination(s) of software, firmware, or hardware suitable for the purposes described. Software and other modules may reside and execute on servers, workstations, personal computers, computerized tablets, PDAs, and other computing devices suitable for the purposes described herein. Software and other modules may be accessible via local computer memory, via a network, via a browser, or via other means suitable for the purposes described herein. Data structures described herein may comprise computer files, variables, programming arrays, programming structures, or any electronic information storage schemes or methods, or any combinations thereof, suitable for the purposes described herein. User interface elements described herein may comprise elements from graphical user interfaces, interactive voice response, command line interfaces, and other suitable interfaces.
Further, processing of the various components of the illustrated systems can be distributed across multiple machines, networks, and other computing resources. Two or more components of a system can be combined into fewer components. Various components of the illustrated systems can be implemented in one or more virtual machines, rather than in dedicated computer hardware systems and/or computing devices. Likewise, the data repositories shown can represent physical and/or logical data storage, including, e.g., storage area networks or other distributed storage systems. Moreover, in some embodiments the connections between the components shown represent possible paths of data flow, rather than actual connections between hardware. While some examples of possible connections are shown, any of the subset of the components shown can communicate with any other subset of components in various implementations.
Embodiments are also described above with reference to flow chart illustrations and/or block diagrams of methods, apparatus (systems) and computer program products. Each block of the flow chart illustrations and/or block diagrams, and combinations of blocks in the flow chart illustrations and/or block diagrams, may be implemented by computer program instructions. Such instructions may be provided to a processor of a general purpose computer, special purpose computer, specially-equipped computer (e.g., comprising a high-performance database server, a graphics subsystem, etc.) or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor(s) of the computer or other programmable data processing apparatus, create means for implementing the acts specified in the flow chart and/or block diagram block or blocks. These computer program instructions may also be stored in a non-transitory computer-readable memory that can direct a computer or other programmable data processing apparatus to operate in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the acts specified in the flow chart and/or block diagram block or blocks. The computer program instructions may also be loaded to a computing device or other programmable data processing apparatus to cause operations to be performed on the computing device or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computing device or other programmable apparatus provide steps for implementing the acts specified in the flow chart and/or block diagram block or blocks.
Any patents and applications and other references noted above, including any that may be listed in accompanying filing papers, are incorporated herein by reference. Aspects of the invention can be modified, if necessary, to employ the systems, functions, and concepts of the various references described above to provide yet further implementations of the invention. These and other changes can be made to the invention in light of the above Detailed Description. While the above description describes certain examples of the invention, and describes the best mode contemplated, no matter how detailed the above appears in text, the invention can be practiced in many ways. Details of the system may vary considerably in its specific implementation, while still being encompassed by the invention disclosed herein. As noted above, particular terminology used when describing certain features or aspects of the invention should not be taken to imply that the terminology is being redefined herein to be restricted to any specific characteristics, features, or aspects of the invention with which that terminology is associated. In general, the terms used in the following claims should not be construed to limit the invention to the specific examples disclosed in the specification, unless the above Detailed Description section explicitly defines such terms. Accordingly, the actual scope of the invention encompasses not only the disclosed examples, but also all equivalent ways of practicing or implementing the invention under the claims.
To reduce the number of claims, certain aspects of the invention are presented below in certain claim forms, but the applicant contemplates other aspects of the invention in any number of claim forms. For example, while only one aspect of the invention is recited as a means-plus-function claim under 35 U.S.C sec. 112(f) (AIA), other aspects may likewise be embodied as a means-plus-function claim, or in other forms, such as being embodied in a computer-readable medium. Any claims intended to be treated under 35 U.S.C. § 112(f) will begin with the words “means for,” but use of the term “for” in any other context is not intended to invoke treatment under 35 U.S.C. § 112(f). Accordingly, the applicant reserves the right to pursue additional claims after filing this application, in either this application or in a continuing application.
The present application is a Continuation of U.S. patent application Ser. No. 16/685,326 filed Nov. 15, 2019 (now U.S. Pat. No. 11,449,394), which is a Continuation-in-Part of U.S. patent application Ser. No. 15/684,410 filed Aug. 23, 2017 (now U.S. Pat. No. 10,534,673), which is a continuation of U.S. patent application Ser. No. 14/675,524 filed Mar. 31, 2015 (now abandoned), which is a continuation of U.S. patent application Ser. No. 13/958,353 filed Aug. 2, 2013 (now U.S. Pat. No. 9,026,497), which is a continuation of U.S. patent application Ser. No. 12/982,165 filed Dec. 30, 2010 (now U.S. Pat. No. 8,504,526), which claims the benefit of priority under 35 U.S.C. § 119(e) of U.S. Provisional Patent Application No. 61/351,790, filed on Jun. 4, 2010, and entitled “Failover Systems And Methods For Performing Backup Operations,” each of which is hereby incorporated herein by reference in its entirety. The present application also claims the benefit of priority under 35 U.S.C. § 119(e) to U.S. Provisional Patent Application No. 62/811,424 entitled “Heterogeneous Indexing In A Data Storage Management System” and filed on Feb. 27, 2019, which is incorporated herein by reference in its entirety. Any and all applications for which a foreign or domestic priority claim is identified in the Application Data Sheet, or any correction thereto, are hereby incorporated by reference under 37 CFR 1.57.
| Number | Name | Date | Kind |
|---|---|---|---|
| 4084231 | Capozzi et al. | Apr 1978 | A |
| 4267568 | Dechant et al. | May 1981 | A |
| 4283787 | Chambers | Aug 1981 | A |
| 4417321 | Chang et al. | Nov 1983 | A |
| 4641274 | Swank | Feb 1987 | A |
| 4654819 | Stiffler et al. | Mar 1987 | A |
| 4686620 | Ng | Aug 1987 | A |
| 4912637 | Sheedy et al. | Mar 1990 | A |
| 4995035 | Cole et al. | Feb 1991 | A |
| 5005122 | Griffin et al. | Apr 1991 | A |
| 5093912 | Dong et al. | Mar 1992 | A |
| 5133065 | Cheffetz et al. | Jul 1992 | A |
| 5193154 | Kitajima et al. | Mar 1993 | A |
| 5212772 | Masters | May 1993 | A |
| 5226157 | Nakano et al. | Jul 1993 | A |
| 5239647 | Anglin et al. | Aug 1993 | A |
| 5241668 | Eastridge et al. | Aug 1993 | A |
| 5241670 | Eastridge et al. | Aug 1993 | A |
| 5276860 | Fortier et al. | Jan 1994 | A |
| 5276867 | Kenley et al. | Jan 1994 | A |
| 5287500 | Stoppani, Jr. | Feb 1994 | A |
| 5301286 | Rajani | Apr 1994 | A |
| 5321816 | Rogan et al. | Jun 1994 | A |
| 5333315 | Saether et al. | Jul 1994 | A |
| 5347653 | Flynn et al. | Sep 1994 | A |
| 5410700 | Fecteau et al. | Apr 1995 | A |
| 5420996 | Aoyagi | May 1995 | A |
| 5448724 | Hayashi | Sep 1995 | A |
| 5454099 | Myers et al. | Sep 1995 | A |
| 5481694 | Chao et al. | Jan 1996 | A |
| 5491810 | Allen | Feb 1996 | A |
| 5495607 | Pisello et al. | Feb 1996 | A |
| 5504873 | Martin et al. | Apr 1996 | A |
| 5544345 | Carpenter et al. | Aug 1996 | A |
| 5544347 | Yanai et al. | Aug 1996 | A |
| 5544359 | Tada et al. | Aug 1996 | A |
| 5548750 | Larsson et al. | Aug 1996 | A |
| 5559957 | Balk | Sep 1996 | A |
| 5559991 | Kanfi | Sep 1996 | A |
| 5594901 | Andoh | Jan 1997 | A |
| 5619644 | Crockett et al. | Apr 1997 | A |
| 5638509 | Dunphy et al. | Jun 1997 | A |
| 5640561 | Satoh et al. | Jun 1997 | A |
| 5642496 | Kanfi | Jun 1997 | A |
| 5664204 | Wang | Sep 1997 | A |
| 5673381 | Huai et al. | Sep 1997 | A |
| 5699361 | Ding et al. | Dec 1997 | A |
| 5729743 | Squibb | Mar 1998 | A |
| 5751997 | Kullick et al. | May 1998 | A |
| 5758359 | Saxon | May 1998 | A |
| 5761677 | Senator et al. | Jun 1998 | A |
| 5764972 | Crouse et al. | Jun 1998 | A |
| 5778395 | Whiting et al. | Jul 1998 | A |
| 5793867 | Cordery et al. | Aug 1998 | A |
| 5812398 | Nielsen | Sep 1998 | A |
| 5813009 | Johnson et al. | Sep 1998 | A |
| 5813017 | Morris | Sep 1998 | A |
| 5875478 | Blumenau | Feb 1999 | A |
| 5887134 | Ebrahim | Mar 1999 | A |
| 5901327 | Ofek | May 1999 | A |
| 5924102 | Perks | Jul 1999 | A |
| 5930831 | Marsh et al. | Jul 1999 | A |
| 5950205 | Aviani, Jr. | Sep 1999 | A |
| 5974563 | Beeler, Jr. | Oct 1999 | A |
| 6021415 | Cannon et al. | Feb 2000 | A |
| 6026414 | Anglin | Feb 2000 | A |
| 6052735 | Ulrich et al. | Apr 2000 | A |
| 6076148 | Kedem | Jun 2000 | A |
| 6078932 | Haye et al. | Jun 2000 | A |
| 6094416 | Ying | Jul 2000 | A |
| 6101585 | Brown et al. | Aug 2000 | A |
| 6131095 | Low et al. | Oct 2000 | A |
| 6131190 | Sidwell | Oct 2000 | A |
| 6148412 | Cannon et al. | Nov 2000 | A |
| 6154787 | Urevig et al. | Nov 2000 | A |
| 6161111 | Mutalik et al. | Dec 2000 | A |
| 6167402 | Yeager | Dec 2000 | A |
| 6175904 | Gunderson | Jan 2001 | B1 |
| 6185474 | Nakamura et al. | Feb 2001 | B1 |
| 6199074 | Kern et al. | Mar 2001 | B1 |
| 6212512 | Barney et al. | Apr 2001 | B1 |
| 6230166 | Velamuri et al. | May 2001 | B1 |
| 6260069 | Anglin | Jul 2001 | B1 |
| 6269431 | Dunham | Jul 2001 | B1 |
| 6272631 | Thomlinson et al. | Aug 2001 | B1 |
| 6275953 | Vahalia et al. | Aug 2001 | B1 |
| 6301592 | Aoyama et al. | Oct 2001 | B1 |
| 6324581 | Xu et al. | Nov 2001 | B1 |
| 6328766 | Long | Dec 2001 | B1 |
| 6330570 | Crighton | Dec 2001 | B1 |
| 6330642 | Carteau | Dec 2001 | B1 |
| 6343324 | Hubis et al. | Jan 2002 | B1 |
| RE37601 | Eastridge et al. | Mar 2002 | E |
| 6356801 | Goodman et al. | Mar 2002 | B1 |
| 6389432 | Pothapragada et al. | May 2002 | B1 |
| 6397242 | Devine et al. | May 2002 | B1 |
| 6415323 | McCanne et al. | Jul 2002 | B1 |
| 6418478 | Ignatius et al. | Jul 2002 | B1 |
| 6421711 | Blumenau et al. | Jul 2002 | B1 |
| 6487561 | Ofek et al. | Nov 2002 | B1 |
| 6516327 | Zondervan et al. | Feb 2003 | B1 |
| 6519679 | Devireddy et al. | Feb 2003 | B2 |
| 6538669 | Lagueux, Jr | Mar 2003 | B1 |
| 6542972 | Ignatius et al. | Apr 2003 | B2 |
| 6564228 | O'Connor | May 2003 | B1 |
| 6581076 | Ching et al. | Jun 2003 | B1 |
| 6658436 | Oshinsky et al. | Dec 2003 | B2 |
| 6658526 | Nguyen et al. | Dec 2003 | B2 |
| 6704839 | Butterworth et al. | Mar 2004 | B2 |
| 6704885 | Salas-Meza et al. | Mar 2004 | B1 |
| 6721767 | De Meno et al. | Apr 2004 | B2 |
| 6732124 | Koseki et al. | May 2004 | B1 |
| 6760723 | Oshinsky et al. | Jul 2004 | B2 |
| 6769003 | Park et al. | Jul 2004 | B2 |
| 6772290 | Bromley et al. | Aug 2004 | B1 |
| 6795904 | Kamvysselis | Sep 2004 | B1 |
| 6820214 | Cabrera et al. | Nov 2004 | B1 |
| 6836830 | Yamagami et al. | Dec 2004 | B1 |
| 6839747 | Blumenau et al. | Jan 2005 | B1 |
| 6880101 | Golasky et al. | Apr 2005 | B2 |
| 7003641 | Prahlad et al. | Feb 2006 | B2 |
| 7035880 | Crescenti et al. | Apr 2006 | B1 |
| 7065537 | Cha et al. | Jun 2006 | B2 |
| 7076270 | Jaggers et al. | Jul 2006 | B2 |
| 7082464 | Hasan et al. | Jul 2006 | B2 |
| 7100007 | Saika | Aug 2006 | B2 |
| 7103432 | Drader et al. | Sep 2006 | B2 |
| 7107298 | Prahlad et al. | Sep 2006 | B2 |
| 7130970 | Devassy et al. | Oct 2006 | B2 |
| 7143121 | Mendonca et al. | Nov 2006 | B2 |
| 7162496 | Amarendran et al. | Jan 2007 | B2 |
| 7174433 | Kottomtharayil et al. | Feb 2007 | B2 |
| 7178059 | Greenspan et al. | Feb 2007 | B2 |
| 7209972 | Ignatius et al. | Apr 2007 | B1 |
| 7219162 | Donker et al. | May 2007 | B2 |
| 7234073 | Roytman et al. | Jun 2007 | B1 |
| 7246207 | Kottomtharayil et al. | Jul 2007 | B2 |
| 7249150 | Watanabe et al. | Jul 2007 | B1 |
| 7315923 | Retnamma et al. | Jan 2008 | B2 |
| 7315924 | Prahlad et al. | Jan 2008 | B2 |
| 7318134 | Oliveira et al. | Jan 2008 | B1 |
| 7324543 | Wassew et al. | Jan 2008 | B2 |
| 7343356 | Prahlad et al. | Mar 2008 | B2 |
| 7343453 | Prahlad et al. | Mar 2008 | B2 |
| 7346623 | Prahlad et al. | Mar 2008 | B2 |
| 7346751 | Prahlad et al. | Mar 2008 | B2 |
| 7353335 | Kawamura | Apr 2008 | B2 |
| 7376895 | Tsao | May 2008 | B2 |
| 7380072 | Kottomtharayil et al. | May 2008 | B2 |
| 7380155 | Fung et al. | May 2008 | B2 |
| 7383293 | Gupta et al. | Jun 2008 | B2 |
| 7386744 | Barr et al. | Jun 2008 | B2 |
| 7389311 | Crescenti et al. | Jun 2008 | B1 |
| 7395282 | Crescenti et al. | Jul 2008 | B1 |
| 7401154 | Ignatius et al. | Jul 2008 | B2 |
| 7409509 | Devassy et al. | Aug 2008 | B2 |
| 7412460 | Hrle | Aug 2008 | B2 |
| 7424519 | Hoshino et al. | Sep 2008 | B2 |
| 7437388 | DeVos | Oct 2008 | B1 |
| 7440982 | Lu et al. | Oct 2008 | B2 |
| 7447692 | Oshinsky et al. | Nov 2008 | B2 |
| 7448079 | Tremain | Nov 2008 | B2 |
| 7454569 | Kavuri et al. | Nov 2008 | B2 |
| 7475282 | Tormasov et al. | Jan 2009 | B2 |
| 7484054 | Kottomtharayil et al. | Jan 2009 | B2 |
| 7484208 | Nelson | Jan 2009 | B1 |
| 7490207 | Amarendran | Feb 2009 | B2 |
| 7500053 | Kavuri et al. | Mar 2009 | B1 |
| 7502820 | Manders et al. | Mar 2009 | B2 |
| 7512595 | McBride et al. | Mar 2009 | B1 |
| 7529782 | Prahlad et al. | May 2009 | B2 |
| 7536291 | Retnamma et al. | May 2009 | B1 |
| 7539707 | Prahlad et al. | May 2009 | B2 |
| 7543125 | Gokhale | Jun 2009 | B2 |
| 7546324 | Prahlad et al. | Jun 2009 | B2 |
| 7546484 | Sen et al. | Jun 2009 | B2 |
| 7552279 | Gandler | Jun 2009 | B1 |
| 7568080 | Prahlad et al. | Jul 2009 | B2 |
| 7581077 | Ignatius et al. | Aug 2009 | B2 |
| 7594138 | Abdulvahid | Sep 2009 | B2 |
| 7596721 | Flake et al. | Sep 2009 | B1 |
| 7600125 | Stringham | Oct 2009 | B1 |
| 7603386 | Amarendran et al. | Oct 2009 | B2 |
| 7606844 | Kottomtharayil | Oct 2009 | B2 |
| 7613748 | Brockway et al. | Nov 2009 | B2 |
| 7613752 | Prahlad et al. | Nov 2009 | B2 |
| 7617253 | Prahlad et al. | Nov 2009 | B2 |
| 7617262 | Prahlad et al. | Nov 2009 | B2 |
| 7617307 | Childress et al. | Nov 2009 | B2 |
| 7620710 | Kottomtharayil et al. | Nov 2009 | B2 |
| 7631351 | Erofeev | Dec 2009 | B2 |
| 7636743 | Erofeev | Dec 2009 | B2 |
| 7640406 | Hagerstrom et al. | Dec 2009 | B1 |
| 7651593 | Prahlad et al. | Jan 2010 | B2 |
| 7657550 | Prahlad et al. | Feb 2010 | B2 |
| 7660807 | Prahlad et al. | Feb 2010 | B2 |
| 7661028 | Erofeev | Feb 2010 | B2 |
| 7668884 | Prahlad et al. | Feb 2010 | B2 |
| 7685177 | Hagerstrom et al. | Mar 2010 | B1 |
| 7694070 | Mogi et al. | Apr 2010 | B2 |
| 7702782 | Pai | Apr 2010 | B1 |
| 7707184 | Zhang et al. | Apr 2010 | B1 |
| 7707190 | Yu et al. | Apr 2010 | B2 |
| 7707373 | Murayama | Apr 2010 | B2 |
| 7721138 | Lyadvinsky et al. | May 2010 | B1 |
| 7725893 | Jaeckel et al. | May 2010 | B2 |
| 7730035 | Berger et al. | Jun 2010 | B2 |
| 7734578 | Prahlad et al. | Jun 2010 | B2 |
| 7734669 | Kottomtharayil et al. | Jun 2010 | B2 |
| 7739459 | Kottomtharayil et al. | Jun 2010 | B2 |
| 7747579 | Prahlad et al. | Jun 2010 | B2 |
| 7756835 | Pugh | Jul 2010 | B2 |
| 7756964 | Madison, Jr. et al. | Jul 2010 | B2 |
| 7757043 | Kavuri et al. | Jul 2010 | B2 |
| 7765167 | Prahlad et al. | Jul 2010 | B2 |
| 7769961 | Kottomtharayil et al. | Aug 2010 | B2 |
| 7778984 | Zhang et al. | Aug 2010 | B2 |
| 7792789 | Prahlad et al. | Sep 2010 | B2 |
| 7793307 | Gokhale et al. | Sep 2010 | B2 |
| 7797281 | Greene et al. | Sep 2010 | B1 |
| 7801864 | Prahlad et al. | Sep 2010 | B2 |
| 7802067 | Prahlad et al. | Sep 2010 | B2 |
| 7809914 | Kottomtharayil et al. | Oct 2010 | B2 |
| 7822717 | Kapoor et al. | Oct 2010 | B2 |
| 7822939 | Veprinsky et al. | Oct 2010 | B1 |
| 7822967 | Fung | Oct 2010 | B2 |
| 7840537 | Gokhale | Nov 2010 | B2 |
| 7849361 | Ahal et al. | Dec 2010 | B2 |
| 7861234 | Lolo | Dec 2010 | B1 |
| 7882077 | Gokhale et al. | Feb 2011 | B2 |
| 7890467 | Watanable et al. | Feb 2011 | B2 |
| 7899788 | Chandhok et al. | Mar 2011 | B2 |
| 7917617 | Ponnapur | Mar 2011 | B1 |
| 7937421 | Mikesell et al. | May 2011 | B2 |
| 7937612 | Lyadvinsky et al. | May 2011 | B1 |
| 7966292 | Ozekinci et al. | Jun 2011 | B1 |
| 7966293 | Owara et al. | Jun 2011 | B1 |
| 8001277 | Mega et al. | Aug 2011 | B2 |
| 8037028 | Prahlad et al. | Oct 2011 | B2 |
| 8037032 | Pershin et al. | Oct 2011 | B2 |
| 8046550 | Feathergill | Oct 2011 | B2 |
| 8051473 | Szucs | Nov 2011 | B2 |
| 8055745 | Atluri | Nov 2011 | B2 |
| 8060476 | Afonso et al. | Nov 2011 | B1 |
| 8069271 | Brunet et al. | Nov 2011 | B2 |
| 8086650 | Milford | Dec 2011 | B1 |
| 8099391 | Monckton | Jan 2012 | B1 |
| 8108638 | Kishi | Jan 2012 | B2 |
| 8108640 | Holl, II | Jan 2012 | B1 |
| 8117492 | Searls et al. | Feb 2012 | B1 |
| 8131681 | Hangud et al. | Mar 2012 | B1 |
| 8135930 | Mattox et al. | Mar 2012 | B1 |
| 8140786 | Bunte | Mar 2012 | B2 |
| 8156086 | Lu et al. | Apr 2012 | B2 |
| 8156301 | Khandelwal et al. | Apr 2012 | B1 |
| 8170995 | Prahlad et al. | May 2012 | B2 |
| 8185777 | Davies et al. | May 2012 | B2 |
| 8185893 | Hyser et al. | May 2012 | B2 |
| 8195623 | Prahlad et al. | Jun 2012 | B2 |
| 8199911 | Tsaur et al. | Jun 2012 | B1 |
| 8200637 | Stringham | Jun 2012 | B1 |
| 8204859 | Ngo | Jun 2012 | B2 |
| 8219524 | Gokhale | Jul 2012 | B2 |
| 8219653 | Keagy et al. | Jul 2012 | B1 |
| 8219769 | Wilk | Jul 2012 | B1 |
| 8225133 | Lyadvinsky et al. | Jul 2012 | B1 |
| 8229896 | Narayanan | Jul 2012 | B1 |
| 8229954 | Kottomtharayil et al. | Jul 2012 | B2 |
| 8230195 | Amarendran et al. | Jul 2012 | B2 |
| 8230256 | Raut | Jul 2012 | B1 |
| 8271443 | Swift et al. | Sep 2012 | B1 |
| 8285681 | Prahlad et al. | Oct 2012 | B2 |
| 8291170 | Zhang et al. | Oct 2012 | B1 |
| 8291407 | Greenwood et al. | Oct 2012 | B2 |
| 8307177 | Prahlad et al. | Nov 2012 | B2 |
| 8307187 | Chawla et al. | Nov 2012 | B2 |
| 8315992 | Gipp et al. | Nov 2012 | B1 |
| 8336040 | Davidson et al. | Dec 2012 | B2 |
| 8364652 | Vijayan et al. | Jan 2013 | B2 |
| 8370542 | Lu et al. | Feb 2013 | B2 |
| 8396838 | Brockway | Mar 2013 | B2 |
| 8407190 | Prahlad | Mar 2013 | B2 |
| 8433679 | Crescenti | Apr 2013 | B2 |
| 8433682 | Ngo | Apr 2013 | B2 |
| 8434131 | Varadharajan | Apr 2013 | B2 |
| 8438347 | Tawri et al. | May 2013 | B1 |
| 8453145 | Naik | May 2013 | B1 |
| 8473594 | Astete et al. | Jun 2013 | B2 |
| 8479304 | Clifford | Jul 2013 | B1 |
| 8489676 | Chaplin et al. | Jul 2013 | B1 |
| 8504526 | Gokhale et al. | Aug 2013 | B2 |
| 8560788 | Sreedharan et al. | Oct 2013 | B1 |
| 8577845 | Nguyen et al. | Nov 2013 | B2 |
| 8578120 | Attarde et al. | Nov 2013 | B2 |
| 8578126 | Gaonkar et al. | Nov 2013 | B1 |
| 8595191 | Prahlad et al. | Nov 2013 | B2 |
| 8620870 | Dwarampudi et al. | Dec 2013 | B2 |
| 8650389 | Thornewell et al. | Feb 2014 | B1 |
| 8667171 | Guo et al. | Mar 2014 | B2 |
| 8706867 | Vijayan | Apr 2014 | B2 |
| 8751857 | Frenkel et al. | Jun 2014 | B2 |
| 8776043 | Thimsen et al. | Jul 2014 | B1 |
| 8793222 | Stringham | Jul 2014 | B1 |
| 8799431 | Pabari | Aug 2014 | B2 |
| 8825720 | Xie et al. | Sep 2014 | B1 |
| 8831202 | Abidogun et al. | Sep 2014 | B1 |
| 8850146 | Majumdar | Sep 2014 | B1 |
| 8904081 | Kulkarni | Dec 2014 | B1 |
| 8909980 | Lewis et al. | Dec 2014 | B1 |
| 8924967 | Nelson | Dec 2014 | B2 |
| 8930496 | Gokhale et al. | Jan 2015 | B2 |
| 8930543 | Ashok et al. | Jan 2015 | B2 |
| 8938481 | Kumarasamy et al. | Jan 2015 | B2 |
| 8938643 | Karmarkar et al. | Jan 2015 | B1 |
| 8954446 | Vijayan et al. | Feb 2015 | B2 |
| 8954796 | Cohen et al. | Feb 2015 | B1 |
| 8959299 | Ngo et al. | Feb 2015 | B2 |
| 8966318 | Shah | Feb 2015 | B1 |
| 9020895 | Rajashekar | Apr 2015 | B1 |
| 9020900 | Vijayan et al. | Apr 2015 | B2 |
| 9020987 | Nanda et al. | Apr 2015 | B1 |
| 9021459 | Qu | Apr 2015 | B1 |
| 9026497 | Gokhale et al. | May 2015 | B2 |
| 9026498 | Kumarasamy | May 2015 | B2 |
| 9069587 | Agarwal et al. | Jun 2015 | B2 |
| 9098457 | Towstopiat et al. | Aug 2015 | B2 |
| 9098495 | Gokhale | Aug 2015 | B2 |
| 9116633 | Sancheti et al. | Aug 2015 | B2 |
| 9124633 | Eizadi et al. | Sep 2015 | B1 |
| 9141529 | Klein et al. | Sep 2015 | B2 |
| 9146755 | Lassonde et al. | Sep 2015 | B2 |
| 9213706 | Long et al. | Dec 2015 | B2 |
| 9223597 | Deshpande et al. | Dec 2015 | B2 |
| 9235474 | Petri et al. | Jan 2016 | B1 |
| 9235582 | Madiraju Varadaraju et al. | Jan 2016 | B1 |
| 9239687 | Vijayan et al. | Jan 2016 | B2 |
| 9239762 | Gunda et al. | Jan 2016 | B1 |
| 9244777 | Boullery et al. | Jan 2016 | B2 |
| 9246996 | Brooker | Jan 2016 | B1 |
| 9268602 | Prahlad et al. | Feb 2016 | B2 |
| 9280378 | Shah | Mar 2016 | B2 |
| 9280430 | Sarfare et al. | Mar 2016 | B2 |
| 9286086 | Deshpande et al. | Mar 2016 | B2 |
| 9286110 | Mitkar et al. | Mar 2016 | B2 |
| 9292350 | Pendharkar et al. | Mar 2016 | B1 |
| 9298386 | Baldwin et al. | Mar 2016 | B2 |
| 9298715 | Kumarasamy et al. | Mar 2016 | B2 |
| 9311121 | Deshpande et al. | Apr 2016 | B2 |
| 9311248 | Wagner | Apr 2016 | B2 |
| 9336076 | Baldwin et al. | May 2016 | B2 |
| 9342537 | Kumarasamy et al. | May 2016 | B2 |
| 9372827 | Kumarasamy et al. | Jun 2016 | B2 |
| 9378035 | Kirpalani | Jun 2016 | B2 |
| 9397944 | Hobbs et al. | Jul 2016 | B1 |
| 9405763 | Prahlad et al. | Aug 2016 | B2 |
| 9417968 | Dornemann et al. | Aug 2016 | B2 |
| 9424136 | Teater et al. | Aug 2016 | B1 |
| 9436555 | Dornemann et al. | Sep 2016 | B2 |
| 9444811 | Nara et al. | Sep 2016 | B2 |
| 9448731 | Nallathambi et al. | Sep 2016 | B2 |
| 9451023 | Sancheti | Sep 2016 | B2 |
| 9461881 | Kumarasamy | Oct 2016 | B2 |
| 9471441 | Lyadvinsky et al. | Oct 2016 | B1 |
| 9477683 | Ghosh | Oct 2016 | B2 |
| 9483361 | Gokhale et al. | Nov 2016 | B2 |
| 9483362 | Gokhale et al. | Nov 2016 | B2 |
| 9483363 | Gokhale et al. | Nov 2016 | B2 |
| 9483364 | Gokhale et al. | Nov 2016 | B2 |
| 9489244 | Mitkar et al. | Nov 2016 | B2 |
| 9495251 | Kottomtharayil et al. | Nov 2016 | B2 |
| 9495370 | Chatterjee et al. | Nov 2016 | B1 |
| 9495404 | Kumarasamy et al. | Nov 2016 | B2 |
| 9563518 | Klose | Feb 2017 | B2 |
| 9575789 | Rangari et al. | Feb 2017 | B1 |
| 9575991 | Ghosh | Feb 2017 | B2 |
| 9588847 | Natanzon et al. | Mar 2017 | B1 |
| 9588972 | Dwarampudi et al. | Mar 2017 | B2 |
| 9594636 | Mortensen et al. | Mar 2017 | B2 |
| 9606745 | Satoyama et al. | Mar 2017 | B2 |
| 9612966 | Joshi et al. | Apr 2017 | B2 |
| 9632882 | Kumarasamy et al. | Apr 2017 | B2 |
| 9633033 | Vijayan et al. | Apr 2017 | B2 |
| 9639274 | Maranna et al. | May 2017 | B2 |
| 9639426 | Pawar et al. | May 2017 | B2 |
| 9652283 | Mitkar et al. | May 2017 | B2 |
| 9684535 | Deshpande et al. | Jun 2017 | B2 |
| 9684567 | Derk et al. | Jun 2017 | B2 |
| 9703584 | Kottomtharayil et al. | Jul 2017 | B2 |
| 9710465 | Dornemann et al. | Jul 2017 | B2 |
| 9766989 | Mitkar et al. | Jul 2017 | B2 |
| 9740702 | Pawar et al. | Aug 2017 | B2 |
| 9760398 | Pai | Sep 2017 | B1 |
| 9760448 | Per et al. | Sep 2017 | B1 |
| 9766825 | Bhagi et al. | Sep 2017 | B2 |
| 9811427 | Klose | Nov 2017 | B2 |
| 9823977 | Dornemann et al. | Nov 2017 | B2 |
| 9852026 | Mitkar et al. | Dec 2017 | B2 |
| 9886346 | Kumarasamy et al. | Feb 2018 | B2 |
| 9892276 | Bell et al. | Feb 2018 | B2 |
| 9898213 | Joshi et al. | Feb 2018 | B2 |
| 9928001 | Dornemann et al. | Mar 2018 | B2 |
| 9939981 | White et al. | Apr 2018 | B2 |
| 9965306 | Natanzon | May 2018 | B1 |
| 9965316 | Deshpande et al. | May 2018 | B2 |
| 9977687 | Kottomtharayil et al. | May 2018 | B2 |
| 9983936 | Dornemann et al. | May 2018 | B2 |
| 9990253 | Rajimwale et al. | Jun 2018 | B1 |
| 9996287 | Dornemann et al. | Jun 2018 | B2 |
| 9996534 | Dornemann et al. | Jun 2018 | B2 |
| 10001935 | Gokhale et al. | Jun 2018 | B2 |
| 10013314 | Klose | Jul 2018 | B2 |
| 10048889 | Dornemann et al. | Aug 2018 | B2 |
| 10061658 | Long et al. | Aug 2018 | B2 |
| 10061663 | Vijayan et al. | Aug 2018 | B2 |
| 10073649 | DeJong et al. | Sep 2018 | B2 |
| 10084873 | Dornemann et al. | Sep 2018 | B2 |
| 10108652 | Kumarasamy et al. | Oct 2018 | B2 |
| 10146643 | Fang | Dec 2018 | B2 |
| 10152251 | Sancheti et al. | Dec 2018 | B2 |
| 10162528 | Sancheti et al. | Dec 2018 | B2 |
| 10162873 | Desphande et al. | Dec 2018 | B2 |
| 10191816 | Vijayan et al. | Jan 2019 | B2 |
| 10228962 | Dornemann et al. | Mar 2019 | B2 |
| 10229133 | Vijayan et al. | Mar 2019 | B2 |
| 10255143 | Vijayan et al. | Apr 2019 | B2 |
| 10365839 | Gokhale et al. | Jul 2019 | B2 |
| 10379892 | Kripalani | Aug 2019 | B2 |
| 10380072 | Attarde et al. | Aug 2019 | B2 |
| 10387073 | Bhagi et al. | Aug 2019 | B2 |
| 10387269 | Muller et al. | Aug 2019 | B2 |
| 10417102 | Sanakkayala et al. | Sep 2019 | B2 |
| 10437505 | Dornemann et al. | Oct 2019 | B2 |
| 10452303 | Dornemann et al. | Oct 2019 | B2 |
| 10474483 | Kottomtharayil et al. | Nov 2019 | B2 |
| 10474542 | Mitkar et al. | Nov 2019 | B2 |
| 10474548 | Sanakkayala et al. | Nov 2019 | B2 |
| 10474638 | Mitkar et al. | Nov 2019 | B2 |
| 10481826 | Vijayan et al. | Nov 2019 | B2 |
| 10481984 | Semyonov et al. | Nov 2019 | B1 |
| 10496547 | Naenko | Dec 2019 | B1 |
| 10503619 | Kremane | Dec 2019 | B2 |
| 10503753 | Mitkar et al. | Dec 2019 | B2 |
| 10534672 | Klose | Jan 2020 | B2 |
| 10534673 | Gokhale et al. | Jan 2020 | B2 |
| 10540327 | Ngo et al. | Jan 2020 | B2 |
| 10565067 | Dornemann | Feb 2020 | B2 |
| 10572468 | Dornemann et al. | Feb 2020 | B2 |
| 10592145 | Bedadala et al. | Mar 2020 | B2 |
| 10592350 | Dornemann | Mar 2020 | B2 |
| 10592357 | Vijayan et al. | Mar 2020 | B2 |
| 10628267 | Prahlad et al. | Apr 2020 | B2 |
| 10650057 | Pawar et al. | May 2020 | B2 |
| 10673943 | Prahlad et al. | Jun 2020 | B2 |
| 10678758 | Dornemann | Jun 2020 | B2 |
| 10684883 | Deshpande et al. | Jun 2020 | B2 |
| 10684924 | Kilaru et al. | Jun 2020 | B2 |
| 10732885 | Gutta et al. | Aug 2020 | B2 |
| 10733143 | Pawar et al. | Aug 2020 | B2 |
| 10747630 | Sanakkayala et al. | Aug 2020 | B2 |
| 10768971 | Dornemann et al. | Sep 2020 | B2 |
| 10776209 | Pawar et al. | Sep 2020 | B2 |
| 10838824 | Klose | Nov 2020 | B2 |
| 10853195 | Ashraf et al. | Dec 2020 | B2 |
| 10877928 | Nagrale et al. | Dec 2020 | B2 |
| 10884635 | Gokhale et al. | Jan 2021 | B2 |
| 10896104 | Sanakkayala et al. | Jan 2021 | B2 |
| 10990484 | Gokhale et al. | Apr 2021 | B2 |
| 11016696 | Ankireddypalle et al. | May 2021 | B2 |
| 11099943 | Gokhale et al. | Aug 2021 | B2 |
| 11099956 | Polimera et al. | Aug 2021 | B1 |
| 11200124 | Rathi et al. | Dec 2021 | B2 |
| 11321189 | Klose | May 2022 | B2 |
| 20010044910 | Ricart et al. | Nov 2001 | A1 |
| 20020069369 | Tremain | Jun 2002 | A1 |
| 20020095609 | Tokunaga | Jul 2002 | A1 |
| 20020178143 | Fujimoto | Nov 2002 | A1 |
| 20020184239 | Mosher, Jr. et al. | Dec 2002 | A1 |
| 20020194511 | Swoboda | Dec 2002 | A1 |
| 20030021223 | Kashyap | Jan 2003 | A1 |
| 20030031127 | Saleh et al. | Feb 2003 | A1 |
| 20030056142 | Hashemi et al. | Mar 2003 | A1 |
| 20030074600 | Tamatsu | Apr 2003 | A1 |
| 20030084076 | Sekiguchi et al. | May 2003 | A1 |
| 20030126494 | Strasser | Jul 2003 | A1 |
| 20030149750 | Franzenburg | Aug 2003 | A1 |
| 20030163495 | Lanzatella et al. | Aug 2003 | A1 |
| 20030182301 | Patterson et al. | Sep 2003 | A1 |
| 20030182329 | Sato | Sep 2003 | A1 |
| 20030204597 | Arakawa et al. | Oct 2003 | A1 |
| 20030236956 | Grubbs et al. | Dec 2003 | A1 |
| 20040019892 | E et al. | Jan 2004 | A1 |
| 20040030668 | Pawlowski et al. | Feb 2004 | A1 |
| 20040030822 | Rajan et al. | Feb 2004 | A1 |
| 20040044642 | Fujii et al. | Mar 2004 | A1 |
| 20040078654 | Holland et al. | Apr 2004 | A1 |
| 20040128442 | Hinshaw et al. | Jul 2004 | A1 |
| 20040139127 | Pofelski | Jul 2004 | A1 |
| 20040153823 | Ansari | Aug 2004 | A1 |
| 20040230899 | Pagnano et al. | Nov 2004 | A1 |
| 20040250033 | Prahlad et al. | Dec 2004 | A1 |
| 20040267838 | Curran et al. | Dec 2004 | A1 |
| 20040268175 | Koch et al. | Dec 2004 | A1 |
| 20050039069 | Prahlad et al. | Feb 2005 | A1 |
| 20050044114 | Kottomtharayil et al. | Feb 2005 | A1 |
| 20050060356 | Saika | Mar 2005 | A1 |
| 20050080970 | Jeyasingh et al. | Apr 2005 | A1 |
| 20050131996 | Mastrianni et al. | Jun 2005 | A1 |
| 20050138461 | Allen et al. | Jun 2005 | A1 |
| 20050172161 | Cruz et al. | Aug 2005 | A1 |
| 20050183072 | Horning et al. | Aug 2005 | A1 |
| 20050187891 | Johnson et al. | Aug 2005 | A1 |
| 20050198303 | Knauerhase et al. | Sep 2005 | A1 |
| 20050216788 | Mani-Meitav et al. | Sep 2005 | A1 |
| 20050235286 | Ballew et al. | Oct 2005 | A1 |
| 20050257062 | Ignatius | Nov 2005 | A1 |
| 20050262033 | Yamashita | Nov 2005 | A1 |
| 20050262097 | Sim-Tang | Nov 2005 | A1 |
| 20050262316 | Obayashi et al. | Nov 2005 | A1 |
| 20050268156 | Mashayekhi et al. | Dec 2005 | A1 |
| 20050278397 | Clark | Dec 2005 | A1 |
| 20060005048 | Osaki | Jan 2006 | A1 |
| 20060010227 | Atluri | Jan 2006 | A1 |
| 20060026452 | Suzuki et al. | Feb 2006 | A1 |
| 20060036658 | Henrickson | Feb 2006 | A1 |
| 20060047626 | Raheem | Mar 2006 | A1 |
| 20060058994 | Ravi et al. | Mar 2006 | A1 |
| 20060085672 | Watanabe et al. | Apr 2006 | A1 |
| 20060101189 | Chandrasekaran et al. | May 2006 | A1 |
| 20060155594 | Almeida et al. | Jul 2006 | A1 |
| 20060155712 | Prahlad et al. | Jul 2006 | A1 |
| 20060179347 | Anderson, Jr. et al. | Aug 2006 | A1 |
| 20060184935 | Abels et al. | Aug 2006 | A1 |
| 20060195715 | Herington | Aug 2006 | A1 |
| 20060206547 | Kulkarni et al. | Sep 2006 | A1 |
| 20060224846 | Amarendran et al. | Oct 2006 | A1 |
| 20060225065 | Chandhok et al. | Oct 2006 | A1 |
| 20060230136 | Ma | Oct 2006 | A1 |
| 20060236054 | Kitamura et al. | Oct 2006 | A1 |
| 20070027999 | Allen et al. | Feb 2007 | A1 |
| 20070043870 | Ninose | Feb 2007 | A1 |
| 20070050526 | Abe et al. | Mar 2007 | A1 |
| 20070074068 | Hsieh | Mar 2007 | A1 |
| 20070094467 | Yamasaki | Apr 2007 | A1 |
| 20070094533 | Coombs et al. | Apr 2007 | A1 |
| 20070100792 | Lent et al. | May 2007 | A1 |
| 20070150499 | D'Souza et al. | Jun 2007 | A1 |
| 20070156793 | D'Souza et al. | Jul 2007 | A1 |
| 20070185922 | Kapoor et al. | Aug 2007 | A1 |
| 20070185938 | Prahlad et al. | Aug 2007 | A1 |
| 20070186068 | Agrawal | Aug 2007 | A1 |
| 20070198802 | Kavuri | Aug 2007 | A1 |
| 20070203938 | Prahlad et al. | Aug 2007 | A1 |
| 20070208918 | Harbin et al. | Sep 2007 | A1 |
| 20070220319 | Desai et al. | Sep 2007 | A1 |
| 20070226535 | Gokhale | Sep 2007 | A1 |
| 20070234108 | Cox et al. | Oct 2007 | A1 |
| 20070234302 | Suzuki et al. | Oct 2007 | A1 |
| 20070239804 | Armstrong et al. | Oct 2007 | A1 |
| 20070250365 | Chakrabarti et al. | Oct 2007 | A1 |
| 20070266056 | Stacey et al. | Nov 2007 | A1 |
| 20070271471 | Merzlikine et al. | Nov 2007 | A1 |
| 20070282921 | Atluri et al. | Dec 2007 | A1 |
| 20070283355 | Misono et al. | Dec 2007 | A1 |
| 20070299930 | Wendelrup et al. | Dec 2007 | A1 |
| 20080022058 | Nadathur et al. | Jan 2008 | A1 |
| 20080059704 | Kavuri | Mar 2008 | A1 |
| 20080071841 | Okada et al. | Mar 2008 | A1 |
| 20080071842 | Tokuda | Mar 2008 | A1 |
| 20080077633 | Kaplan et al. | Mar 2008 | A1 |
| 20080091655 | Gokhale | Apr 2008 | A1 |
| 20080098049 | Pillai et al. | Apr 2008 | A1 |
| 20080126833 | Callaway et al. | May 2008 | A1 |
| 20080134177 | Fitzgerald et al. | Jun 2008 | A1 |
| 20080147754 | Littlefield et al. | Jun 2008 | A1 |
| 20080162840 | Augenstein | Jul 2008 | A1 |
| 20080189468 | Schmidt et al. | Aug 2008 | A1 |
| 20080195639 | Freeman et al. | Aug 2008 | A1 |
| 20080201600 | Lu | Aug 2008 | A1 |
| 20080228771 | Prahlad et al. | Sep 2008 | A1 |
| 20080228833 | Kanc | Sep 2008 | A1 |
| 20080229037 | Bunte | Sep 2008 | A1 |
| 20080235479 | Scales et al. | Sep 2008 | A1 |
| 20080243855 | Prahlad | Oct 2008 | A1 |
| 20080243947 | Kaneda | Oct 2008 | A1 |
| 20080244068 | Lyoda et al. | Oct 2008 | A1 |
| 20080244177 | Crescenti et al. | Oct 2008 | A1 |
| 20080244204 | Cremelie et al. | Oct 2008 | A1 |
| 20080250407 | Dadhia et al. | Oct 2008 | A1 |
| 20080253283 | Douglis et al. | Oct 2008 | A1 |
| 20080270488 | Ozawa et al. | Oct 2008 | A1 |
| 20080270564 | Rangegowda et al. | Oct 2008 | A1 |
| 20080275924 | Fries | Nov 2008 | A1 |
| 20080282253 | Huizenga | Nov 2008 | A1 |
| 20080307020 | Ko et al. | Dec 2008 | A1 |
| 20080313371 | Kedem et al. | Dec 2008 | A1 |
| 20080320319 | Muller | Dec 2008 | A1 |
| 20090006733 | Gold et al. | Jan 2009 | A1 |
| 20090013258 | Hintermeister et al. | Jan 2009 | A1 |
| 20090037680 | Colbert et al. | Feb 2009 | A1 |
| 20090037763 | Adhya et al. | Feb 2009 | A1 |
| 20090055507 | Oeda | Feb 2009 | A1 |
| 20090055606 | Gallaher et al. | Feb 2009 | A1 |
| 20090077557 | Ichikawa et al. | Mar 2009 | A1 |
| 20090113109 | Nelson et al. | Apr 2009 | A1 |
| 20090144416 | Chatley et al. | Jun 2009 | A1 |
| 20090157882 | Kashyap | Jun 2009 | A1 |
| 20090158080 | Furuya et al. | Jun 2009 | A1 |
| 20090183145 | Hu et al. | Jul 2009 | A1 |
| 20090204649 | Wong et al. | Aug 2009 | A1 |
| 20090210427 | Eidler et al. | Aug 2009 | A1 |
| 20090210458 | Glover et al. | Aug 2009 | A1 |
| 20090216816 | Basler et al. | Aug 2009 | A1 |
| 20090222496 | Liu et al. | Sep 2009 | A1 |
| 20090228669 | Siesarev et al. | Sep 2009 | A1 |
| 20090240904 | Austruy et al. | Sep 2009 | A1 |
| 20090243846 | Yuuki | Oct 2009 | A1 |
| 20090248755 | Watanabe | Oct 2009 | A1 |
| 20090248762 | Prahlad et al. | Oct 2009 | A1 |
| 20090249005 | Bender et al. | Oct 2009 | A1 |
| 20090282404 | Khandekar et al. | Nov 2009 | A1 |
| 20090287665 | Prahlad | Nov 2009 | A1 |
| 20090300023 | Vaghani | Dec 2009 | A1 |
| 20090300057 | Friedman | Dec 2009 | A1 |
| 20090307166 | Routray et al. | Dec 2009 | A1 |
| 20090313260 | Mimatsu | Dec 2009 | A1 |
| 20090313447 | Nguyen et al. | Dec 2009 | A1 |
| 20090313503 | Atluri et al. | Dec 2009 | A1 |
| 20090319534 | Gokhale | Dec 2009 | A1 |
| 20090319585 | Gokhale | Dec 2009 | A1 |
| 20090320029 | Kottomtharayil | Dec 2009 | A1 |
| 20090320137 | White et al. | Dec 2009 | A1 |
| 20090327477 | Madison, Jr. et al. | Dec 2009 | A1 |
| 20100005126 | Lehr | Jan 2010 | A1 |
| 20100011178 | Feathergill | Jan 2010 | A1 |
| 20100017444 | Chatterjee et al. | Jan 2010 | A1 |
| 20100017647 | Callaway et al. | Jan 2010 | A1 |
| 20100030984 | Erickson | Feb 2010 | A1 |
| 20100031086 | Leppard | Feb 2010 | A1 |
| 20100042790 | Mondal et al. | Feb 2010 | A1 |
| 20100049929 | Nagarkar et al. | Feb 2010 | A1 |
| 20100049930 | Pershin | Feb 2010 | A1 |
| 20100070466 | Prahlad et al. | Mar 2010 | A1 |
| 20100070474 | Lad | Mar 2010 | A1 |
| 20100070478 | Anglin | Mar 2010 | A1 |
| 20100070725 | Prahlad et al. | Mar 2010 | A1 |
| 20100070726 | Ngo et al. | Mar 2010 | A1 |
| 20100077161 | Stoakes et al. | Mar 2010 | A1 |
| 20100082672 | Kottomtharayil | Apr 2010 | A1 |
| 20100094948 | Ganesh et al. | Apr 2010 | A1 |
| 20100094981 | Cordray | Apr 2010 | A1 |
| 20100101300 | Rigby et al. | Apr 2010 | A1 |
| 20100106691 | Preslan et al. | Apr 2010 | A1 |
| 20100107158 | Chen et al. | Apr 2010 | A1 |
| 20100107172 | Calinescu et al. | Apr 2010 | A1 |
| 20100161919 | Dodgson et al. | Jun 2010 | A1 |
| 20100162037 | Maule et al. | Jun 2010 | A1 |
| 20100186014 | Vaghani et al. | Jul 2010 | A1 |
| 20100211829 | Ziskind et al. | Aug 2010 | A1 |
| 20100223495 | Leppard | Sep 2010 | A1 |
| 20100228913 | Czezatke et al. | Sep 2010 | A1 |
| 20100242096 | Varadharajan et al. | Sep 2010 | A1 |
| 20100250549 | Muller et al. | Sep 2010 | A1 |
| 20100250832 | Zhang | Sep 2010 | A1 |
| 20100257523 | Frank | Oct 2010 | A1 |
| 20100262586 | Rosikiewicz et al. | Oct 2010 | A1 |
| 20100262794 | De Beer et al. | Oct 2010 | A1 |
| 20100280999 | Atluri et al. | Nov 2010 | A1 |
| 20100281458 | Paladino et al. | Nov 2010 | A1 |
| 20100293439 | Flynn et al. | Nov 2010 | A1 |
| 20100299309 | Maki et al. | Nov 2010 | A1 |
| 20100299490 | Attarde et al. | Nov 2010 | A1 |
| 20100299666 | Agbaria et al. | Nov 2010 | A1 |
| 20100306173 | Frank | Dec 2010 | A1 |
| 20100306486 | Balasubramanian et al. | Dec 2010 | A1 |
| 20100325471 | Mishra et al. | Dec 2010 | A1 |
| 20100325727 | Neystad et al. | Dec 2010 | A1 |
| 20100332401 | Prahlad | Dec 2010 | A1 |
| 20100332454 | Prahlad et al. | Dec 2010 | A1 |
| 20100332456 | Prahlad et al. | Dec 2010 | A1 |
| 20100332479 | Prahlad | Dec 2010 | A1 |
| 20100332629 | Cotugno et al. | Dec 2010 | A1 |
| 20100332818 | Prahlad | Dec 2010 | A1 |
| 20100333100 | Miyazaki et al. | Dec 2010 | A1 |
| 20100333116 | Prahlad | Dec 2010 | A1 |
| 20110004586 | Cherryholmes et al. | Jan 2011 | A1 |
| 20110010515 | Ranade | Jan 2011 | A1 |
| 20110016467 | Kane | Jan 2011 | A1 |
| 20110022811 | Kirihata et al. | Jan 2011 | A1 |
| 20110023114 | Diab et al. | Jan 2011 | A1 |
| 20110035359 | Bendakovsky | Feb 2011 | A1 |
| 20110035620 | Elyashev et al. | Feb 2011 | A1 |
| 20110047541 | Yamaguchi et al. | Feb 2011 | A1 |
| 20110061045 | Phillips | Mar 2011 | A1 |
| 20110072430 | Mani | Mar 2011 | A1 |
| 20110082832 | Vadali et al. | Apr 2011 | A1 |
| 20110087632 | Subramanian et al. | Apr 2011 | A1 |
| 20110107025 | Urkude et al. | May 2011 | A1 |
| 20110107331 | Evans et al. | May 2011 | A1 |
| 20110153570 | Kim et al. | Jun 2011 | A1 |
| 20110154109 | Levine | Jun 2011 | A1 |
| 20110161299 | Prahlad | Jun 2011 | A1 |
| 20110179414 | Goggin et al. | Jul 2011 | A1 |
| 20110185355 | Chawla et al. | Jul 2011 | A1 |
| 20110191559 | Li et al. | Aug 2011 | A1 |
| 20110202728 | Nichols et al. | Aug 2011 | A1 |
| 20110202734 | Dhakras et al. | Aug 2011 | A1 |
| 20110208928 | Chandra et al. | Aug 2011 | A1 |
| 20110213754 | Bindal | Sep 2011 | A1 |
| 20110218967 | Sliger et al. | Sep 2011 | A1 |
| 20110219144 | Amit et al. | Sep 2011 | A1 |
| 20110225277 | Freimuth et al. | Sep 2011 | A1 |
| 20110234583 | Bakalash | Sep 2011 | A1 |
| 20110239013 | Muller | Sep 2011 | A1 |
| 20110246430 | Prahlad et al. | Oct 2011 | A1 |
| 20110252208 | Ali et al. | Oct 2011 | A1 |
| 20110264786 | Kedem et al. | Oct 2011 | A1 |
| 20110289281 | Spackman | Nov 2011 | A1 |
| 20110302140 | Gokhale et al. | Dec 2011 | A1 |
| 20120016840 | Lin et al. | Jan 2012 | A1 |
| 20120017027 | Baskakov et al. | Jan 2012 | A1 |
| 20120017043 | Aizman et al. | Jan 2012 | A1 |
| 20120017114 | Timashev et al. | Jan 2012 | A1 |
| 20120054736 | Arcese et al. | Mar 2012 | A1 |
| 20120072685 | Otani | Mar 2012 | A1 |
| 20120078881 | Crump et al. | Mar 2012 | A1 |
| 20120079221 | Sivasubramanian et al. | Mar 2012 | A1 |
| 20120084262 | Dwarampudi et al. | Apr 2012 | A1 |
| 20120084272 | Garces-Erice et al. | Apr 2012 | A1 |
| 20120084769 | Adi et al. | Apr 2012 | A1 |
| 20120096149 | Sunkara et al. | Apr 2012 | A1 |
| 20120101999 | Scherzinger et al. | Apr 2012 | A1 |
| 20120110328 | Pate et al. | May 2012 | A1 |
| 20120131295 | Nakajima | May 2012 | A1 |
| 20120131578 | Ciano et al. | May 2012 | A1 |
| 20120136832 | Sadhwani | May 2012 | A1 |
| 20120150815 | Parfumi | Jun 2012 | A1 |
| 20120150818 | Vijayan Retnamma et al. | Jun 2012 | A1 |
| 20120150826 | Vijayan Retnamma et al. | Jun 2012 | A1 |
| 20120150949 | Vijayan Retnamma et al. | Jun 2012 | A1 |
| 20120151084 | Stathopoulos et al. | Jun 2012 | A1 |
| 20120159232 | Shimada et al. | Jun 2012 | A1 |
| 20120167083 | Suit | Jun 2012 | A1 |
| 20120209812 | Bezbaruah | Aug 2012 | A1 |
| 20120221843 | Bak et al. | Aug 2012 | A1 |
| 20120233285 | Suzuki | Sep 2012 | A1 |
| 20120254119 | Kumarasamy et al. | Oct 2012 | A1 |
| 20120254364 | Vijayan | Oct 2012 | A1 |
| 20120254824 | Bansold | Oct 2012 | A1 |
| 20120278287 | Wilk | Nov 2012 | A1 |
| 20120278571 | Fleming et al. | Nov 2012 | A1 |
| 20120278799 | Starks et al. | Nov 2012 | A1 |
| 20120290802 | Wade et al. | Nov 2012 | A1 |
| 20120324183 | Chiruvolu et al. | Dec 2012 | A1 |
| 20120331248 | Kono et al. | Dec 2012 | A1 |
| 20130024641 | Talagala et al. | Jan 2013 | A1 |
| 20130024722 | Kotagiri | Jan 2013 | A1 |
| 20130036418 | Yadappanavar et al. | Feb 2013 | A1 |
| 20130042234 | Deluca et al. | Feb 2013 | A1 |
| 20130054533 | Hao et al. | Feb 2013 | A1 |
| 20130061014 | Prahlad et al. | Mar 2013 | A1 |
| 20130074181 | Singh | Mar 2013 | A1 |
| 20130080841 | Reddy et al. | Mar 2013 | A1 |
| 20130086580 | Simonsen et al. | Apr 2013 | A1 |
| 20130117744 | Klein et al. | May 2013 | A1 |
| 20130138880 | Murata | May 2013 | A1 |
| 20130173771 | Ditto et al. | Jul 2013 | A1 |
| 20130204849 | Chacko | Aug 2013 | A1 |
| 20130227558 | Du et al. | Aug 2013 | A1 |
| 20130232215 | Gupta et al. | Sep 2013 | A1 |
| 20130232480 | Winterfeldt et al. | Sep 2013 | A1 |
| 20130238562 | Kumarasamy et al. | Sep 2013 | A1 |
| 20130238572 | Prahlad et al. | Sep 2013 | A1 |
| 20130262390 | Kumarasamy et al. | Oct 2013 | A1 |
| 20130262396 | Kripalani et al. | Oct 2013 | A1 |
| 20130262638 | Kumarasamy et al. | Oct 2013 | A1 |
| 20130262801 | Sancheti et al. | Oct 2013 | A1 |
| 20130268931 | O'Hare et al. | Oct 2013 | A1 |
| 20130290267 | Dwarampudi et al. | Oct 2013 | A1 |
| 20130297772 | Ashok et al. | Nov 2013 | A1 |
| 20130311429 | Agetsuma | Nov 2013 | A1 |
| 20130326260 | Wei et al. | Dec 2013 | A1 |
| 20140006858 | Helfman et al. | Jan 2014 | A1 |
| 20140007097 | Chin et al. | Jan 2014 | A1 |
| 20140007181 | Sarin et al. | Jan 2014 | A1 |
| 20140052892 | Klein et al. | Feb 2014 | A1 |
| 20140059380 | Krishnan | Feb 2014 | A1 |
| 20140075440 | Prahlad et al. | Mar 2014 | A1 |
| 20140082128 | Beard | Mar 2014 | A1 |
| 20140089266 | Une et al. | Mar 2014 | A1 |
| 20140095816 | Hsu et al. | Apr 2014 | A1 |
| 20140101300 | Rosensweig et al. | Apr 2014 | A1 |
| 20140115285 | Arcese et al. | Apr 2014 | A1 |
| 20140115287 | Schnapp et al. | Apr 2014 | A1 |
| 20140136803 | Qin | May 2014 | A1 |
| 20140143636 | Frost et al. | May 2014 | A1 |
| 20140156684 | Zaslavsky et al. | Jun 2014 | A1 |
| 20140181038 | Pawar et al. | Jun 2014 | A1 |
| 20140181044 | Pawar et al. | Jun 2014 | A1 |
| 20140181046 | Pawar et al. | Jun 2014 | A1 |
| 20140188803 | James et al. | Jul 2014 | A1 |
| 20140195749 | Colgrove et al. | Jul 2014 | A1 |
| 20140196037 | Gopalan et al. | Jul 2014 | A1 |
| 20140196038 | Kottomtharayil et al. | Jul 2014 | A1 |
| 20140196039 | Kottomtharayil et al. | Jul 2014 | A1 |
| 20140201142 | Varadharajan et al. | Jul 2014 | A1 |
| 20140201151 | Kumarasamy et al. | Jul 2014 | A1 |
| 20140201153 | Vijayan et al. | Jul 2014 | A1 |
| 20140201157 | Pawar et al. | Jul 2014 | A1 |
| 20140201162 | Kumarasamy et al. | Jul 2014 | A1 |
| 20140201170 | Vijayan et al. | Jul 2014 | A1 |
| 20140201365 | Ashok et al. | Jul 2014 | A1 |
| 20140229451 | Venkatesh et al. | Aug 2014 | A1 |
| 20140237537 | Manmohan et al. | Aug 2014 | A1 |
| 20140244610 | Raman et al. | Aug 2014 | A1 |
| 20140258245 | Estes | Sep 2014 | A1 |
| 20140259015 | Chigusa et al. | Sep 2014 | A1 |
| 20140278530 | Bruce et al. | Sep 2014 | A1 |
| 20140281758 | Klein et al. | Sep 2014 | A1 |
| 20140282514 | Carson et al. | Sep 2014 | A1 |
| 20140330874 | Novak et al. | Nov 2014 | A1 |
| 20140337285 | Gokhale et al. | Nov 2014 | A1 |
| 20140337295 | Haselton et al. | Nov 2014 | A1 |
| 20140337662 | Gokhale et al. | Nov 2014 | A1 |
| 20140337664 | Gokhale et al. | Nov 2014 | A1 |
| 20140344323 | Pelavin et al. | Nov 2014 | A1 |
| 20140372384 | Long et al. | Dec 2014 | A1 |
| 20140372788 | Vavrick et al. | Dec 2014 | A1 |
| 20150026508 | Jacobs et al. | Jan 2015 | A1 |
| 20150058382 | St. Laurent | Feb 2015 | A1 |
| 20150067391 | Merchant et al. | Mar 2015 | A1 |
| 20150067393 | Madani et al. | Mar 2015 | A1 |
| 20150074536 | Varadharajan et al. | Mar 2015 | A1 |
| 20150088821 | Blea et al. | Mar 2015 | A1 |
| 20150089185 | Brandyberry et al. | Mar 2015 | A1 |
| 20150095908 | Jacobs et al. | Apr 2015 | A1 |
| 20150120928 | Gummaraju et al. | Apr 2015 | A1 |
| 20150121122 | Towstopiat et al. | Apr 2015 | A1 |
| 20150134607 | Magdon-Ismail et al. | May 2015 | A1 |
| 20150142745 | Tekade et al. | May 2015 | A1 |
| 20150149813 | Mizuno et al. | May 2015 | A1 |
| 20150160884 | Scales et al. | Jun 2015 | A1 |
| 20150161015 | Kumarasamy et al. | Jun 2015 | A1 |
| 20150163172 | Mudigonda et al. | Jun 2015 | A1 |
| 20150169417 | Brandwine et al. | Jun 2015 | A1 |
| 20150199238 | Badgley | Jul 2015 | A1 |
| 20150205682 | Gokhale et al. | Jul 2015 | A1 |
| 20150227438 | Jaquette | Aug 2015 | A1 |
| 20150227602 | Ramu | Aug 2015 | A1 |
| 20150242283 | Simoncelli et al. | Aug 2015 | A1 |
| 20150248333 | Aravot | Sep 2015 | A1 |
| 20150268876 | Ahn et al. | Sep 2015 | A1 |
| 20150278046 | Zellermayer et al. | Oct 2015 | A1 |
| 20150293817 | Subramanian et al. | Oct 2015 | A1 |
| 20150317216 | Hsu et al. | Nov 2015 | A1 |
| 20150347165 | Lipchuk et al. | Dec 2015 | A1 |
| 20150347306 | Gschwind | Dec 2015 | A1 |
| 20150347430 | Ghosh | Dec 2015 | A1 |
| 20150350027 | Raissinia et al. | Dec 2015 | A1 |
| 20150363254 | Satoyama et al. | Dec 2015 | A1 |
| 20150363413 | Ghosh | Dec 2015 | A1 |
| 20150370652 | He et al. | Dec 2015 | A1 |
| 20150370668 | Nazari et al. | Dec 2015 | A1 |
| 20150378758 | Duggan et al. | Dec 2015 | A1 |
| 20150378771 | Tarasuk-Levin | Dec 2015 | A1 |
| 20150378833 | Misra et al. | Dec 2015 | A1 |
| 20150378849 | Liu et al. | Dec 2015 | A1 |
| 20150378857 | Sevigny et al. | Dec 2015 | A1 |
| 20150381711 | Singh et al. | Dec 2015 | A1 |
| 20160019317 | Pawar et al. | Jan 2016 | A1 |
| 20160026405 | Dhuse | Jan 2016 | A1 |
| 20160070623 | Derk | Mar 2016 | A1 |
| 20160085606 | Panasko et al. | Mar 2016 | A1 |
| 20160092467 | Lee et al. | Mar 2016 | A1 |
| 20160132400 | Pawar et al. | May 2016 | A1 |
| 20160154709 | Mitkar et al. | Jun 2016 | A1 |
| 20160170844 | Long et al. | Jun 2016 | A1 |
| 20160188413 | Abali et al. | Jun 2016 | A1 |
| 20160202916 | Cui et al. | Jul 2016 | A1 |
| 20160203060 | Singh | Jul 2016 | A1 |
| 20160210064 | Dornemann et al. | Jul 2016 | A1 |
| 20160226966 | Lin | Aug 2016 | A1 |
| 20160283335 | Yao et al. | Sep 2016 | A1 |
| 20160299818 | Vijayan et al. | Oct 2016 | A1 |
| 20160306706 | Pawar et al. | Oct 2016 | A1 |
| 20160308722 | Kumarasamy et al. | Oct 2016 | A1 |
| 20160321145 | Fang | Nov 2016 | A1 |
| 20160335007 | Ryu et al. | Nov 2016 | A1 |
| 20160350391 | Vijayan et al. | Dec 2016 | A1 |
| 20160371127 | Antony | Dec 2016 | A1 |
| 20170031768 | Sarab | Feb 2017 | A1 |
| 20170054720 | Geng et al. | Feb 2017 | A1 |
| 20170090972 | Ryu et al. | Mar 2017 | A1 |
| 20170123939 | Maheshwari et al. | May 2017 | A1 |
| 20170168903 | Dornemann et al. | Jun 2017 | A1 |
| 20170185488 | Kumarasamy et al. | Jun 2017 | A1 |
| 20170192866 | Vijayan et al. | Jul 2017 | A1 |
| 20170192868 | Vijayan et al. | Jul 2017 | A1 |
| 20170193003 | Vijayan et al. | Jul 2017 | A1 |
| 20170235647 | Kilaru et al. | Aug 2017 | A1 |
| 20170242871 | Kilaru et al. | Aug 2017 | A1 |
| 20170249220 | Kumarasamy et al. | Aug 2017 | A1 |
| 20170262204 | Dornemann et al. | Sep 2017 | A1 |
| 20170262347 | Dornemann | Sep 2017 | A1 |
| 20170262350 | Dornemann | Sep 2017 | A1 |
| 20170264589 | Hunt et al. | Sep 2017 | A1 |
| 20170286230 | Zamir | Oct 2017 | A1 |
| 20170300394 | Raut | Oct 2017 | A1 |
| 20170315876 | Dornquast et al. | Nov 2017 | A1 |
| 20170371547 | Fruchtman et al. | Dec 2017 | A1 |
| 20180011885 | Prahlad et al. | Jan 2018 | A1 |
| 20180060104 | Tarasuk-Levin et al. | Mar 2018 | A1 |
| 20180067955 | Pawar et al. | Mar 2018 | A1 |
| 20180075166 | Pawar et al. | Mar 2018 | A1 |
| 20180089031 | Dornemann et al. | Mar 2018 | A1 |
| 20180095845 | Sanakkayala et al. | Apr 2018 | A1 |
| 20180095846 | Sanakkayala et al. | Apr 2018 | A1 |
| 20180095855 | Sanakkayala et al. | Apr 2018 | A1 |
| 20180113623 | Sancheti | Apr 2018 | A1 |
| 20180143879 | Dornemann | May 2018 | A1 |
| 20180143880 | Dornemann | May 2018 | A1 |
| 20180173454 | Dornemann et al. | Jun 2018 | A1 |
| 20180181598 | Pawar et al. | Jun 2018 | A1 |
| 20180253192 | Varadharajan et al. | Sep 2018 | A1 |
| 20180260157 | Dornemann et al. | Sep 2018 | A1 |
| 20180267861 | Lyer et al. | Sep 2018 | A1 |
| 20180275913 | Mitkar et al. | Sep 2018 | A1 |
| 20180276022 | Mitkar et al. | Sep 2018 | A1 |
| 20180276083 | Mitkar et al. | Sep 2018 | A1 |
| 20180276084 | Mitkar et al. | Sep 2018 | A1 |
| 20180276085 | Mitkar et al. | Sep 2018 | A1 |
| 20180284986 | Bhagi et al. | Oct 2018 | A1 |
| 20180285202 | Bhagi et al. | Oct 2018 | A1 |
| 20180285209 | Liu et al. | Oct 2018 | A1 |
| 20180285215 | Ashraf et al. | Oct 2018 | A1 |
| 20180285353 | Rao et al. | Oct 2018 | A1 |
| 20180300168 | Deshpande et al. | Oct 2018 | A1 |
| 20180307510 | Kottomtharayil et al. | Oct 2018 | A1 |
| 20180314694 | Dornemann et al. | Nov 2018 | A1 |
| 20180329636 | Dornemann et al. | Nov 2018 | A1 |
| 20180373597 | Rana | Dec 2018 | A1 |
| 20190012339 | Kumarasamy et al. | Jan 2019 | A1 |
| 20190026187 | Gulam et al. | Jan 2019 | A1 |
| 20190065069 | Sancheti et al. | Feb 2019 | A1 |
| 20190090305 | Hunter et al. | Mar 2019 | A1 |
| 20190108341 | Bedhapudi et al. | Apr 2019 | A1 |
| 20190196916 | Kumarasamy et al. | Jun 2019 | A1 |
| 20190272220 | Vijayan et al. | Sep 2019 | A1 |
| 20190272221 | Vijayan et al. | Sep 2019 | A1 |
| 20190278662 | Nagrale et al. | Sep 2019 | A1 |
| 20190324791 | Kripalani | Oct 2019 | A1 |
| 20190340088 | Sanakkayala et al. | Nov 2019 | A1 |
| 20190347120 | Kottomtharayil et al. | Nov 2019 | A1 |
| 20190369901 | Dornemann et al. | Dec 2019 | A1 |
| 20190370107 | Subburasu et al. | Dec 2019 | A1 |
| 20190391742 | Bhagi et al. | Dec 2019 | A1 |
| 20200034252 | Mitkar et al. | Jan 2020 | A1 |
| 20200142612 | Dornemann et al. | May 2020 | A1 |
| 20200142782 | Dornemann | May 2020 | A1 |
| 20200142783 | Dornemann | May 2020 | A1 |
| 20200159627 | Bedadala et al. | May 2020 | A1 |
| 20200174894 | Dornemann | Jun 2020 | A1 |
| 20200174895 | Dornemann | Jun 2020 | A1 |
| 20200183728 | Deshpande et al. | Jun 2020 | A1 |
| 20200183802 | Rathi et al. | Jun 2020 | A1 |
| 20200241907 | Dornemann et al. | Jul 2020 | A1 |
| 20200241908 | Dornemann et al. | Jul 2020 | A1 |
| 20200265024 | Pawar et al. | Aug 2020 | A1 |
| 20200301891 | Dornemann | Sep 2020 | A1 |
| 20200327163 | Pawar et al. | Oct 2020 | A1 |
| 20200334113 | Sanakkayala et al. | Oct 2020 | A1 |
| 20200334201 | Pawar et al. | Oct 2020 | A1 |
| 20200334221 | Prahlad et al. | Oct 2020 | A1 |
| 20210026741 | Klose | Jan 2021 | A1 |
| 20210334002 | Ankireddypalle et al. | Oct 2021 | A1 |
| 20210342237 | Polimera et al. | Nov 2021 | A1 |
| 20220012135 | Gokhale et al. | Jan 2022 | A1 |
| 20220043727 | Rathi et al. | Feb 2022 | A1 |
| Number | Date | Country |
|---|---|---|
| 2004227949 | Oct 2004 | AU |
| 2498174 | Mar 2004 | CA |
| 69415115.7 | Aug 1999 | DE |
| 60020978.4 | Apr 2006 | DE |
| 0259912 | Mar 1988 | EP |
| 0405926 | Jan 1991 | EP |
| 0467546 | Jan 1992 | EP |
| 0541281 | May 1993 | EP |
| 0645709 | Mar 1995 | EP |
| 0774715 | May 1997 | EP |
| 0809184 | Nov 1997 | EP |
| 0817040 | Jan 1998 | EP |
| 0899662 | Mar 1999 | EP |
| 0918284 | May 1999 | EP |
| 0981090 | Feb 2000 | EP |
| 1204922 | May 2002 | EP |
| 1209569 | May 2002 | EP |
| 1384135 | Jan 2004 | EP |
| 1387269 | Feb 2004 | EP |
| 1393181 | Mar 2004 | EP |
| 1533701 | May 2005 | EP |
| 1938192 | Nov 2009 | EP |
| 2447361 | Sep 2008 | GB |
| 4198050 | Dec 2008 | JP |
| 4267443 | May 2009 | JP |
| WO 1995013580 | May 1995 | WO |
| WO 1999012098 | Mar 1999 | WO |
| 0114975 | Mar 2001 | WO |
| WO 2004023317 | Mar 2004 | WO |
| WO 2005050449 | Jun 2005 | WO |
| 2005086032 | Sep 2005 | WO |
| WO 2005103955 | Nov 2005 | WO |
| WO 2006052872 | May 2006 | WO |
| WO 2007021678 | Feb 2007 | WO |
| WO2007075587 | Jul 2007 | WO |
| 2010147794 | Dec 2010 | WO |
| WO 2010140264 | Dec 2010 | WO |
| Entry |
|---|
| M. Satyanarayanan et al., “On the ubiquity of logging in distributed file systems”, [1992] Proceedings Third Workshop on Workstation Operating Systems, Apr. 1992, pp. 122-125. |
| P. Eitel, “Backup and storage management in distributed heterogeneous environments”, Proceedings Thirteenth IEEE Symposium on Mass Storage Systems. Toward Distributed Storage and Data Management Systems, Jun. 1994, pp. 124-126. |
| Adjeroh, Donald A., and Kingsley C. Nwosu. “Multimedia database management-requirements and issues.” IEEE multimedia 4.3 (1997): pp. 24-33. (Year: 1997). |
| Armstead et al., “Implementation of a Campus-wide Distributed Mass Storage Service: The Dream vs. Reality,” IEEE, Sep. 11-14, 1995, pp. 190-199. |
| Arneson, “Mass Storage Archiving in Network Environments” IEEE, 1998, pp. 45-50. |
| Bhagwat et al., “Extreme Binning: Scalable, Parallel Deduplication for Chunk-based File Backup”, IEEE International Symposium on Modeling, Analysis & Simulation of Computer and Telecommunication Systems, Sep. 2009, pp. 1-9. |
| Bonvin, Nicolas, Thanasis G. Papaioannou, and Karl Aberer. “Dynamic cost-efficient replication in data clouds.” Proceedings of the 1st Workshop on Automated Control for Datacenters and Clouds. 2009.pp. 49-56 (Year: 2009). |
| Brandon, J., “Virtualization Shakes up Backup Strategy,” <http://www.computerworld.com>, Feb. 21, 2008, 3 pages. |
| Cabrera, et al. “ADSM: A Multi-Platform, Scalable, Back-up and Archive Mass Storage System,” Digest of Papers, Compcon '95, Proceedings of the 40th IEEE Computer Society International Conference, Mar. 5, 1995-Mar. 9, 1995, pp. 420-427, San Francisco, CA. |
| Celesti, et al., “Improving Virtual Machine Migration in Federated Cloud Environments”, 2010, pp. 61-67. |
| Chan, et al., “An Approach to High Availability for Cloud Servers with Snapshot Mechanism,” 2012, pp. 1-6. |
| Chen et al., “When Virtual is Better Than Real”, IEEE 2001, pp. 133-138. |
| Chervenak, et al., “Protecting File Systems—A Survey of Backup Techniques,” 1998, pp. 17-31. |
| Chiappetta, Marco, “ESA Enthusiast System Architecture,” <http://hothardware.com/Articles/NVIDIA-ESA-Enthusiast-System-Architecture/>, Nov. 5, 2007, 2 pages. |
| CommVault Systems, Inc., “A CommVault White Paper: VMware Consolidated Backup (VCB) Certification Information Kit,” 2007, 23 pages. |
| CommVault Systems, Inc., “CommVault Solutions—VMware,” <http://www.commvault.com/solutions/vmware/>, accessed Apr. 30, 2014, 1 page. |
| CommVault Systems, Inc., “Enhanced Protection and Manageability of Virtual Servers,” Partner Solution Brief, 2008, 6 pages. |
| Cully, et al., “Remus: High Availability via Asynchronous Virtual Machine Replication”, 2008, pp. 161-174. |
| Data Protection for Large Vmware and Vblock Environments Using EMC Avamar Applied Technology, Nov. 2010, EMC Corporation, 26 pages. |
| Davis, D., “3 VMware Consolidated Backup (VCB) Utilities You Should Know,” Petri IT Knowlegebase, <http://www.petri.co.il/vmware-consolidated-backup-utilities.htm>, Nov. 16, 2007, 3 pages. |
| Davis, D., “Understanding VMware VMX Configuration Files,” Petri IT Knowledgebase, <http://www.petri.co.il/virtual_vmware_vmx_configuration_files.htm>, Nov. 16, 2007, 3 pages. |
| Davis, D., “VMware Server & Workstation Disk Files Explained,” Petri IT Knowledgebase, <http://www.petri.co.il/virtual_vmware_files_explained.htm>, May 3, 2008, 3 pages. |
| Davis, D., “VMware Versions Compared,” Petri IT Knowledgebase, <http://www.petri.co.il/virtual_vmware_versions_compared.htm>, Nov. 16, 2007, 3 pages. |
| Deng, et al., “Fast Saving and Restoring Virtual Machines with Page Compression”, 2011, pp. 150-157. |
| Diallo, Ousmane, et al. “Distributed database management techniques for wireless sensor networks.” IEEE Transactions on Parallel and Distributed Systems 26.2 (2013): pp. 604-620. (Year: 2013). |
| Eitel, “Backup and Storage Management in Distributed Heterogeneous Environments,” IEEE, 1994, pp. 124-126. |
| Eldos Callback File System product information from https://www.eldos.com/clients/104-345.php retrieved on Dec. 30, 2016, in 2 pages. |
| Eldos Usermode filesystem for your Windows applications—Callback File System® (CBFS®)—Create and manage virtual filesystems and disks from your Windows applications retrieved from https://eldos.com/cbfs on Dec. 30, 2016 in 4 pages. |
| Fraser et al., “Safe Hardware Access With the Xen Virtual Machine Monitor”, 1st Workshop on Operating System and Architectural Support for the demand IT InfraStructure (OASIS), 2004, pp. 1-10. |
| Fu et al., “Fine Grained Transaction Log for Data Recovery in Database Systems”, Third Asia-Pacific Trusted Infrastructure Technologies Conference, IEEE, 2008, pp. 123-131. |
| Gait, “The Optical File Cabinet: A Random-Access File System for Write-Once Optical Disks,” IEEE Computer, vol. 21, No. 6, pp. 11-22 (Jun. 1988) (see in particular figure 5 in p. 15 and recitation in claim 5). |
| Galan et al. “Service Specification in Cloud Environments Based on Extension to Oper Standards” COMSWARE Jun. 16-19, 2009 Dublin, Ireland ACM. |
| Gibson, et al., “Implementing Preinstallation Environment Media for Use in User Support,” 2007, pp. 129-130. |
| Gorton, Ian, and John Klein. “Distribution, data, deployment: Software architecture convergence in big data systems.” IEEE Software 32.3 (2014): pp. 78-85. (Year: 2014). |
| Granger, et al., “Survivable Storage Systems”, 2001, pp. 184-195. |
| Gupta, et al., “GPFS-SNC: An enterprise storage framework for virtual-machine clouds”, 2011, pp. 1-10. |
| Haselhorst, et al., “Efficient Storage Synchronization for Live Migration in Cloud Infrastructures”, 2011, pp. 511-518. |
| Hirofuchio, Takahiro et al., “A live storage migration mechanism over wan and its performance evaluation,” 2009, pp. 67-74. |
| Hirofuchi, et al., “Enabling Instantaneous Relocation of Virtual Machines with a Lightweight VMM Extension”, 2010, pp. 73-83. |
| Hu, et al., “Virtual Machine based Hot-spare Fault-tolerant System”, 2009, pp. 429-432. |
| Hu, Wenjin et al., “A Quantitative Study of Virtual Machine Live Migration,” 2013, pp. 1-10. |
| Huff, “Data Set Usage Sequence Number,” IBM Technical Disclosure Bulletin, vol. 24, No. 5, Oct. 1981 New York, US, pp. 2404-2406. |
| Ibrahim, Shadi et al., “CLOUDLET: Towards MapReduce Implementation on Virtual Machines,” 2009, pp. 65-66. |
| IBM Technical Disclosure Bulletin, vol. 24, No. 5, Oct. 1981 New York, US, pp. 2404-2406, K.L. Huff, “Data Set Usage Sequence Number”. |
| Ismail et al., Architecture of Scalable Backup Service For Private Cloud, IEEE 2013, pp. 174-179. |
| Jander, “Launching Storage-Area Net,” Data Communications, US, McGraw Hill, NY, vol. 27, No. 4 (Mar. 21, 1998), pp. 64-72. |
| Javaraiah, et al., “Backup for Cloud and Disaster Recovery for Consumers and SMBs,” 2008, pp. 1-3. |
| Jhawar et al., “Fault Tolerance Management in Cloud Computing: A System-Level Perspective”, IEEE Systems Journal, vol. 7, No. 2, 2013, pp. 288-297. |
| Jo, et al., “Efficient Live Migration of Virtual Machines Using Shared Storage”, 2013, pp. 1-10. |
| Kashyap “RLC—A Reliable approach to Fast and Efficient Live Migration of Virtual Machines in the Clouds” IEEE 2014 IEEE Computer Society. |
| Kim, et al., “Availability Modeling and Analysis of a Virtualized System,” 2009, pp. 365-371. |
| Kuo, et al., “A Hybrid Cloud Storage Architecture for Service Operational High Availability”, 2013, pp. 487-492. |
| Levy et al., “Log-Driven Backups: A Recovery Scheme for Large Memory Database Systems”, IEEE 1990, pp. 99-109. |
| Li et al. “Comparing Containers versus Virtual Machines for Achieving High Availability” 2015 IEEE. |
| Li et al., “Research on the Backup Mechanism of Oracle Database” International Conference on Environmental Science and Information Application Technology, Jul. 2009, pp. 423-426. |
| Liang, et al., “A virtual disk environment for providing file system recovery”, 2006, pp. 589-599. |
| Lu et al., “Virtual Machine Memory Access Tracing with Hypervisor Exclusive Cache”, Usenix Annual Technical Conference, 2007, pp. 29-43. |
| Mao, et al., “Read-Performance Optimization for Deduplication-Based Storage Systems in the Cloud”, 2014, pp. 1-22. |
| Microsoft Corporation, “How NTFS Works,” Windows Server TechCenter,<http://technet2.mircrosoft.com/windowsserver/en/library/8cc5891d-bf8e-4164-862d-dac5418c5948...>, updated Mar. 28, 2003, internet accessed Mar. 26, 2008, 26 pages. |
| Migrate a Virtual Machine with Storage vMotion in the vSphere Client. http://pubs.vmware.com/vsphere-51/advanced/print/jsp?topic=/com.vmware.vsphere.vcent . . . Retrieved Aug. 12, 2014; 2 pages. |
| Nance et al., “Virtual Machine Introspection: Observation or Interference?”, 2008 IEEE. |
| Ng, Chun-Ho et al., “Live Deduplication Storage of Virtual Machine Images in an Open-Source Cloud,” 2011, pp. 80-99. |
| Nicolae, Bogdan et al., “A Hybrid Local Storage Transfer Scheme for Live Migration of 1/0 Intensive Workloads,” 2012, pp. 85-96. |
| Reingold, B. et al., “Cloud Computing: The Intersection of Massive Scalability, Data Security and Privacy (Part I),” LegalWorks, a Thomson Business, Jun. 2009, 5 pages. |
| Reingold, B. et al., “Cloud Computing: Industry and Government Developments (Part II),” LegalWorks, Sep. 2009, 5 pages. |
| Reingold, B. et al., “Cloud Computing: Whose Law Governs the Cloud? (Part III),” LegalWorks, Jan.-Feb. 2010, 6 pages. |
| Rosenblum et al., “The Design and Implementation of a Log-Structure File System,” Operating Systems Review SIGOPS, vol. 25, No. 5, New York, US, pp. 1-15 (May 1991). |
| Sanbarrow.com, “Disktype-table,” <http://sanbarrow.com/vmdk/disktypes.html>, internet accessed on Apr. 30, 2014, 4 pages. |
| Sanbarrow.com, “Files Used by a VM,” <http://sanbarrow.com/vmx/vmx-files-used-by-a-vm.html>, internet accessed on Apr. 30, 2014, 1 page. |
| Sanbarrow.com, “Monolithic Versus Split Disks,” <http://sanbarrow.com/vmdk/monolithicversusspllit.html>, internet accessed on Jul. 14, 2008, 2 pages. |
| Somasundaram et al., Information Storage and Management. 2009, pp. 251-281. |
| Terry, Douglas B., et al. “Managing update conflicts in Bayou, a weakly connected replicated storage system.” ACM SIGOPS Operating Systems Review 29.5 (1995): pp. 172-182. (Year: 1995). |
| Tran, et al., “Efficient Cooperative Backup with Decentralized Trust Management”, 2012, pp. 1-25. |
| Travostino, et al., “Seamless live migration of virtual machines over the MAN/WAN”, 2006, pp. 901-907. |
| Tudoran, Radu et al., “Adaptive File Management for Scientific Workflows on the Azure Cloud, ” 2013, pp. 273-281. |
| Vaghani, “Virtual Machine File System”, 2010, pp. 57-70. |
| VMware, Inc., “VMware Solution Exchange (VSX)” <http://www.vmware.com/appliances/learn/ovf.html>, 2014, 3 pages. |
| VMware, Inc., “OVF, Open Virtual Machine Format Specification, version 0.9,” White Paper, <http://www.vmware.com>, Sep. 7, 2007, 50 pages. |
| VMware, Inc., “The Open Virtual Machine Format Whitepaper for OVF Specification, version 0.9,” White Paper, <http://www.vmware.com>, 2007, 16 pages. |
| VMware, Inc., “Understanding VMware Consolidated Backup,” White Paper, <http://www.vmware.com>, accessed Apr. 30, 2014, 11 pages. |
| VMware, Inc., “Using VMware Infrastructure for Backup and Restore,” Best Practices, <http://www.vmware.com>, accessed Apr. 30, 2014, 20 pages. |
| VMware, Inc., “Virtual Disk API Programming Guide,” <http://www.vmware.com>, Revision 20080411, 2008, 44 pages. |
| VMware, Inc., “Virtual Disk Format 1.1,” VMware Technical Note, <http://www.vmware.com>, Revision 20071113, Version 1.1, 2007, 18 pages. |
| VMware, Inc., “Virtualized iSCSI SANS: Flexible, Scalable Enterprise Storage for Virtual Infrastructures,” White Paper, <http://www.vmware.com>, Mar. 2008, 13 pages. |
| VMware, Inc., “Virtual Machine Backup Guide, ESX Server 3.5, ESX Server 3i version 3.5, VirtualCenter 2.5,” <http://www.vmware.com>, updated Feb. 21, 2008, 78 pages. |
| VMware, Inc., “Virtual Machine Backup Guide, ESX Server 3.0.1 and VirtualCenter 2.0.1,” <http://www.vmware.com>, updated Nov. 21, 2007, 74 pages. |
| VMware, Inc., “VMware Consolidated Backup,” Product Datasheet, <http://www.vmware.com>, 2009, 2 pages. |
| VMware, Inc., “VMware Consolidated Backup, Improvements in Version 3.5,” Information Guide, <http://www.vmware.com>, accessed Apr. 30, 2014, 11 pages. |
| VMware, Inc., “VMware ESX 3.5,” Product Datasheet, <http://www.vmware.com>, 2008, 4 pages. |
| VMware, Inc., “VMware GSX Server 3.2, Disk Types: Virtual and Physical,” <http://www.vmware.com/support/gsx3/doc/disks_types_gsx.html>, 2008, 2 pages. |
| VMware, Inc., “VMware OVF Tool,” Technical Note, <http://www.vmware.com>, 2007, 4 pages. |
| VMware, Inc., “VMware Workstation 5.0, Snapshots in a Process Tree,”<http://www.vmware.com/support/ws5/doc/ws_preserve_sshot_tree.html>, accessed Apr. 30, 2014, 1 page. |
| VMware, Inc., “VMware Workstation 5.0, Snapshots in a Linear Process,”<http:/www.vmware.com/support/ws5/doc/ws_preserve_sshot_linear.html>, internet accessed on 2014, 1 page. |
| Vmware, Inc., “VMware Workstation 5.5, What Files Make Up a Virtual Machine?” <http://www.vmware.com/support/ws55/doc/ws_learning_files_in_a_vm.html>, 2014, 2 pages. |
| VMware Storage VMotion—Non-Disruptive Live Migration for Virtual Machine Storage Disk Files. Copyright 2009 VMware, Inc.; 2 pages. |
| Vrable, et al., “Cumulus: Filesystem Backup to the Cloud”, 2009, pp. 1-28. |
| VSphere Storage vMotion: Storage Management & Virtual Machine Migration. |
| Weil, Sage A., et al. “CRUSH: Controlled, scalable, decentralized placement of replicated data.” SC'06: Proceedings of the 2006 ACM/IEEE Conference on Supercomputing. IEEE, 2006.pp. 1-12 (Year: 2006). |
| Wikipedia, “Cloud computing,” <http://en.wikipedia.org/wiki/Cloud-computing>, 2009, 11 pages. |
| Wikipedia, “Cluster (file system),” <http://en.wikipedia.org/wiki/Cluster_%28file_system%29>, Sep. 2, 2008, 1 page. |
| Wikipedia, “Cylinder-head-sector,” <http://en.wikipedia.org/wiki/Cylinder-head-sector>, Jan. 4, 2009, 6 pages. |
| Wikipedia, “File Allocation Table,” <http://en.wikipedia.org/wiki/File_Allocation_Table>, Dec. 3, 2008, 12 pages. |
| Wikipedia, “Logical Disk Manager,” <http://en.wikipedia.org/wiki/Logical_Disk_Manager>, Nov. 16, 2007, 3 pages. |
| Wikipedia, “Logical Volume Management,” <http://en.wikipedia.org/wiki/Logical_volume_management>, Oct. 27, 2008, 3 pages. |
| Wikipedia, “Storage Area Network,” <http://en.wikipedia.org/wiki/Storage_area_network>, Dec. 5, 2008, 5 pages. |
| Wikipedia, “Virtualization,” <http://en.wikipedia.org/wiki/Virtualization>, Apr. 29, 2014, 7 pages. |
| Wood, et al., “Disaster Recovery as a Cloud Service: Economic Benefits & Deployment Challenges”, 2010, pp. 1-7. |
| Yang, et al., “Toward Reliable Data Delivery for Highly Dynamic Mobile Ad Hoc Networks,” 2012, pp. 111-124. |
| Yang, et al., “TRAP-Array: A Disk Array Architecture Providing Timely Recovery to Any Point-in-time,” 2006, pp. 1-12. |
| Yoshida et al., “Orthros: A High-Reliability Operating System with Transmigration of Processes,” 2013, pp. 318-327. |
| Zhao, et al., “Adaptive Distributed Load Balancing Algorithm based on Live Migration of Virtual Machines in Cloud”, 2009, pp. 170-175. |
| Zhao, et al., Supporting Application-Tailored Grid File System Sessions with WSRF-Based Services, Advanced Computing and Information Systems Laboratory (ACIS), pp. 24-33. |
| International Search Report and Written Opinion for PCT/US2011/054374, dated May 2, 2012, 7 pages. |
| International Preliminary Report on Patentability and Written Opinion for PCT/US2011/054374, dated Apr. 2, 2013, 9 pages. |
| Shamis et al., “Fast General Distributed Transactions with Opacity”, SIGMOD '19, Jun. 30-Jul. 5, 2019, pp. 433-448. |
| Number | Date | Country | |
|---|---|---|---|
| 20230034651 A1 | Feb 2023 | US |
| Number | Date | Country | |
|---|---|---|---|
| 62811424 | Feb 2019 | US | |
| 61351790 | Jun 2010 | US |
| Number | Date | Country | |
|---|---|---|---|
| Parent | 16685326 | Nov 2019 | US |
| Child | 17884443 | US | |
| Parent | 14675524 | Mar 2015 | US |
| Child | 15684410 | US | |
| Parent | 13958353 | Aug 2013 | US |
| Child | 14675524 | US | |
| Parent | 12982165 | Dec 2010 | US |
| Child | 13958353 | US |
| Number | Date | Country | |
|---|---|---|---|
| Parent | 15684410 | Aug 2017 | US |
| Child | 16685326 | US |
