Systems and methods for performing discrete data replication

Information

  • Patent Grant
  • 9495382
  • Patent Number
    9,495,382
  • Date Filed
    Wednesday, December 9, 2009
    14 years ago
  • Date Issued
    Tuesday, November 15, 2016
    7 years ago
Abstract
Systems and methods for performing intelligent replication of production data on a source storage device. In certain examples, a full backup of the production data is first performed and stored on a destination system. A journal module on the storage device (e.g., a shared storage device), or on at least one source system, tracks files on the storage device that change during a particular period of time. Following this period, a snapshot is taken of the production data. Upon mounting the snapshot, the replication system uses the journal information to identify modified files, conduct a block-level comparison of only the modified files with corresponding files on the destination system, and identify the particular data blocks that changed. The replication system then replicates only the changed blocks to the destination system. Certain systems further store information indicating a source system time of a known good state of the production data.
Description
BACKGROUND

Field


The present disclosure relates to performing copy and/or data management operations in a computer network and, in particular, to systems and methods for performing data replication in a storage management system.


Description of the Related Art


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.


Many approaches to protecting data involve creating a copy of the data, such as backing up and/or replicating data on one or more storage devices. Data shadowing and mirroring, or duplexing, provide for copying but can require substantial amounts of time, processing power and/or storage space, especially for large databases. Moreover, such storage management systems can have a significant adverse impact on the performance of the source or primary system.


To address these drawbacks, certain systems perform backup operations that copy less than an entire volume of data to a desired location. For example, differential backup operations are used to copy all files that have changed since a last full backup of the data. Moreover, incremental backup operations can be used to copy all files that have changed since the most recent full, differential or incremental backup. These techniques, however, can require a significant amount of processing power or network bandwidth, especially when dealing with changes to relatively large files or databases.


SUMMARY

In view of the foregoing, a need exists for improved systems and methods for copying and/or replicating data in computing systems. In particular, a need exists for intelligent systems and methods that reduce the amount of data replicated from a source volume to a destination volume, including replication of a shared storage volume. Such intelligent and focused data replication can advantageously reduce network loads, expedite copy operations and/or decrease consumption of valuable processing resources.


In certain embodiments of the invention, systems and methods are disclosed for performing discrete data replication of data (e.g., application-specific data) in a computer network environment. For instance, in certain embodiments only the changed blocks of a source file are replicated to a destination file. The time intervals of such replication can advantageously be selected and/or varied to balance the need to maintain current the replication data and to reduce network and processing loads.


Accordingly, certain embodiments of the invention can recognize one or more points within application data that represent known good state(s) of the application. This information is then used by the replication system to intelligently and/or timely replicate sections of application data that represent a recoverable state rather than the rote copying of certain blocks of data based on hardware capacity and/or criteria that are unrelated to application recoverability.


In certain embodiments, a method is disclosed for replicating data in a computer network. The method includes performing a full backup of source data comprising a plurality of source files on a source storage device to copy replication data to a destination storage device, the replication data comprising a plurality of destination files corresponding to the plurality of source files. Following the full backup, the method includes identifying changed source files by tracking at a logical level which of the plurality of source files changes between the full backup and a second time and performing a snapshot of the source data to capture a state, or point-in-time image, of the source data at the second time. The method further includes mounting the snapshot and, based on the mounted snapshot, comparing blocks of the changed source files with blocks of the corresponding destination files to detect changed blocks between the changed source files and the corresponding destination files. The method then includes replicating only the changed blocks to the replication data of the destination storage device.


In certain embodiments, a system is disclosed for performing data replication in a computer network environment. The system comprises a shared storage device for storing source data as a plurality of source files, a first source computing device having a first application operative to write data to the plurality of source files, a second source computing device having a second application operative to write data to the plurality of source files, and a journal module configured to identify changed source files by tracking logical changes to the plurality of source files on the shared storage device between a first time and a second time. The system further comprises a data agent module configured to: instruct a creation of a snapshot of the source data to capture a state of the source data at the second time; instruct a mounting of the snapshot; based on the mounted snapshot, compare blocks of the changed source files with blocks of corresponding replication files on a replication storage device to detect inconsistent blocks between the changed source files and the corresponding replication files, and transmit the detected inconsistent blocks to the replication storage device. In certain embodiments, the transmission is made without copying other (consistent) blocks of the source data.


In certain embodiments, a replication system is disclosed that includes means for storing source data accessible to both a first source computing device and a second source computing device, the source data being stored as a plurality of source files. The system further includes: means for performing a full backup of the source data at a first time, the full backup resulting in replication data being stored on a destination storage device, the replication data comprising a plurality of destination files corresponding to the plurality of source files; and means for tracking logical changes to the plurality of source files between the first time and a second time to identify changed source files. The method also includes means for mounting a snapshot capturing a state of the source data at the second time; means for comparing blocks of the changed source files with blocks of the corresponding destination files to detect changed blocks; and means for replicating only the changed blocks to the destination storage device.


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.





BRIEF DESCRIPTION OF THE DRAWINGS


FIG. 1 illustrates a block diagram of a data replication system, according to certain embodiments of the invention.



FIG. 2 illustrates a block diagram of an embodiment of the data replication system of FIG. 1.



FIG. 3 illustrates a flowchart of an exemplary embodiment of a data replication process usable by the data replication system of FIG. 2.



FIG. 4 illustrates a diagram of block level changes replicated from a single file, according to certain embodiments of the invention.



FIG. 5 illustrates a flowchart of an exemplary embodiment of another data replication process usable by the data replication system of FIG. 2.



FIG. 6 illustrates a block diagram of a data replication system having a single source system, according to certain embodiments of the invention.





DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

As will be seen from the disclosure herein, certain systems and methods are provided for intelligent data replication. In particular, embodiments of the invention are capable of performing discrete replication of data from a source system to a destination system.


In certain embodiments, one or more modules executing on a shared storage device and/or at least one source system can monitor data modification operations to determine which files on the storage device change during a period of time. Using a mounted snapshot of the source data, the replication system can then detect which blocks of data were modified within the changed files and replicate these particular blocks to a destination volume.


In certain embodiments, the snapshot of the source volume reflects a known good, or recoverable, state of the application. For instance, replication systems and methods may determine appropriate points within the application data at which enough information is collected to reliably restore the application as of a particular point in time. At certain known good states, the replication system quiesces the application and/or generates a snapshot of the source data in order to perform the replication operations. Time information, such as, for example, a time stamp, can also be recorded to indicate the source system time of the application's known good state.


The destination system is further capable of performing one or more data management operations, such as, for example, storage operations (e.g., snapshot, backup), search operations, data classification, combinations of the same or the like, on the replicated data when it represents a known good state. Performing data management operations on the replicated data allows for the processing of copies of application data without significantly impacting the resources of the source system.


Moreover, using the time information, the destination system is further capable of logically associating the copied data (e.g., a snapshot of the replicated data) with the source system time of the known good state of the application. That is, even though the copy of the replicated data occurs at some point after the replication of the production (source system) data, the copied data is logically associated with the (earlier) source system time of the known good state of the application. As a result, the copy of the replicated data appears as if it was directly performed on the production data. In certain embodiments, this method advantageously allows for further processing of the copied data (e.g., processing of snapshots of the replicated data) without touching the production data.


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 processes described herein are not limited to any particular sequence, and the blocks or states relating thereto can be performed in other sequences that are appropriate. For example, described blocks or states may be performed in an order other than that specifically disclosed, or multiple blocks or states may be combined in a single block or state.



FIG. 1 illustrates a block diagram of a data replication system 100, according to certain embodiments of the invention. In general, embodiments of the data replication system 100 perform discrete data replication by copying changed blocks of data from within one or more files on a primary storage device. Such intelligent and focused data replication can advantageously reduce network loads, expedite copy operation and/or decrease valuable consumption of processing resources.


As shown, the data replication system 100 comprises a source (or primary) system 102 capable of communicating with a destination system 104 by sending and/or receiving data over a network 106. For instance, in certain embodiments, the destination system 104 receives and/or stores a replicated copy of at least a portion of data, such as application-specific data, associated with the source system 102.


The illustrated network 106 advantageously comprises any means for communicating data between two or more systems or components. In certain embodiments, the network 106 comprises a computer network. For example, the network 106 can comprise a public network such as the Internet, virtual private network (VPN), a 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. In embodiments wherein the source system 102 and destination system 104 are part of the same computing device, the network 106 may represent a communications socket or other suitable internal data transfer path or mechanism.


As shown, the source system 102 comprises a shared file system configuration in which multiple source devices have shared access to data (e.g., production data) on the same storage volume(s). In particular, a source device A 110 and a source device B 112 both communicate with source (or primary) storage volume(s) 114 through a switch 124 to have read/write access to the production data. For example, in certain embodiments, the source system 102 comprises a clustered file system, a storage area network (SAN) system, combinations of the same or the like.


The source devices 110 and 112 can comprise any computing device capable of accessing and/or processing data on a storage volume. In certain embodiments, either or both of the source devices 110 and 112 comprises a server computer. In yet other embodiments, the source storage devices 110, 112 can comprise a workstation, a personal computer, a cell phone, a portable computing device, a handheld computing device, a personal digital assistant (PDA), combinations of the same or the like.


The source storage volume 114 can include any type of media capable of storing data. For example, the source storage volume 114 can comprise magnetic storage (such as a disk or a tape drive) or other type of mass storage. In certain embodiments, the source storage volume(s) 114 can comprise 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 array of independent (or inexpensive) disks (RAID). In certain embodiments, the source storage volume(s) 114 can include multiple storage devices of the same or different media.


Although the source storage volume 114 is illustrated separate from both source devices 110, 112, it will be understood that at least a portion of the source storage volume(s) 114 can be internal and/or external (e.g., remote) to the source device A 110 and/or the source device B 112.



FIG. 1 further illustrates an application 120 residing and/or executing on the source device 110 and an application 122 residing and/or executing on the source device 112. In certain embodiments, either or both of the applications 120, 122 can comprise software applications that interact with a user to process data on the source storage volume 114 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 120, 122 can comprise one or more of the following: MICROSOFT EXCHANGE, MICROSOFT SHAREPOINT, MICROSOFT SQL SERVER, ORACLE, MICROSOFT WORD and LOTUS NOTES.


The switch 124 comprises software and/or hardware usable by multiple computing devices to access a shared storage device. For instance, the switch 124 can comprise a Fibre Channel switch or other type of network switch. In yet other embodiments, the shared storage can be arranged in a network file system, a network attached storage (NAS) system, combinations of the same or the like.


As further illustrated in FIG. 1, the destination system 104 comprises a replication module 130 and destination storage volume(s) 132. In certain embodiments, the replication module 130 is configured to monitor and/or manage the copying of data from the source system 102 to the destination system 104. In yet other embodiments, the replication module 130 comprises a “dumb” server or terminal that receives and executes instructions from the source system 102 and/or a storage management module (not shown).


The destination storage volume 132 may include any type of media capable of storing data, such as replication data sent from the source system 102. For example, the destination storage volume 132 may comprise magnetic storage or other type of mass storage. In certain embodiments, the destination storage volume 132 may be internal and/or external to the computing device(s) executing the replication module 130.


Although FIG. 1 illustrates the data replication system 100 having a shared storage configuration, other embodiments of the invention can include a single source device and/or each of multiple source devices can have separate, associated storage volumes.



FIG. 2 illustrates a block diagram of a data replication system 200, according to certain embodiments of the invention. In particular, the data replication system 200 illustrates further details of an embodiment of the replication system 100 of FIG. 1. Thus, to simplify the description, components will not be redescribed in detail if they were described above. Rather, the components in the embodiments of FIG. 2 will be given a reference numeral that retains the same last two digits as the reference numeral used in the embodiment of FIG. 1 and will be preceded with a numeral “2.”


In general, the system 200 is configured to perform intelligent data replication of data on a shared storage volume. In certain embodiments, the data replication is performed at discrete points in time and comprises copying only changed blocks of data to a destination system. This process can be performed, for example, by comparing, on a block-by-block basis, modified files with corresponding files on a destination system. Moreover, the frequency of such replication can be adjusted to meet the needs of the user(s) and/or system.


As shown, the data replication system 200 comprises a source device A 210 and a source device B 212 that communicate with a destination system 204 over a network 206. In general, the data replication system 200 is configured to perform discrete data replication with respect to data stored on a shared source storage volume(s) 214, which is accessible by both source devices 210, 212.


Each of the source devices 210, 212 comprises application(s) 220 and application(s) 222, respectively, executing thereon. As illustrated, the application(s) 220, 222 are configured for shared access to the data on the source storage volume 214 through a switch 224.


The source device A 210 further comprises a data agent 226. In certain embodiments, the data agent 226 comprises a module responsible for performing data and/or storage tasks related to the source device A 210 and/or the source storage volume 214. For example, the data agent 226 can manage and/or coordinate the compilation and/or transferring of replication data from the source storage volume 214. In other embodiments, the data agent 226 may provide archiving, migrating, and/or recovery of client computer data.


In certain embodiments, the source device A 210 comprises a plurality of data agents 226, each of which performs data management operations related to data associated with each application. In yet other embodiments, the data agent 226 can work with data from multiple applications 220.


In certain embodiments, the data agent 226 is configured to perform data management operations in accordance with one or more “storage policies” or other preferences. For example, a storage policy can include a data structure or other information having a set of preferences and/or other storage criteria for performing a storage operation. The preferences and storage criteria may include, but are not limited to, information regarding storage locations, relationships between system components, network pathways, retention policies, data characteristics, compression or encryption requirements, preferred system components, combinations of the same or the like.


Although only a single data agent is illustrated with respect to the data replication system 200, other embodiments of the invention can utilize a data agent on each of a plurality of source devices (e.g., source device 212).


As further illustrated in FIG. 2, the source storage volume 214 further comprises a journal file 227. For instance, the journal file 227 can track data changes on a logical level, such as when a particular file has been changed or modified. In certain embodiments, the journal file 227 comprises a new technology file system (NTFS) change journal or other like file system change journal capable of detecting modifications made to files and/or data stored on the source storage volume 214.


In yet other embodiments, the journal file 227 can store copies or portions of some or all the data operations output from applications 220, 222 to the source storage volume 214. In yet other embodiments, the journal file entries can include other system information, such as time stamp information. In still other embodiments, the journal file entries may be enriched with other useful system or application information available on source devices 210, 212. For example, the journal file entries can include metadata and/or data classification information that has been obtained from the application data.


In certain embodiments of the invention, the journal file 227 can comprise a customized change journal that tracks in real-time the block-level changes made to data files stored on the source storage volume 214. Such embodiments could obviate the need for later performing comparison algorithms to detect which blocks of a modified file were affected by one or more data modification operations.


The source storage volume 214 also comprises one or more snapshots 228 that provide a static image of data on the source storage volume 214. In certain embodiments, the snapshot 228 captures a point-in-time, read-only image of the volume to detect changed files and/or blocks and to facilitate replication of data on the source storage volume 214.


Snapshots may be implemented by several different methods. For example, in certain embodiments, a “copy-on-write” process can be used. In yet other embodiments, the snapshot 228 can be generated using another process, such as, for example, direct-on-write, split mirror, copy-on-write with background copy, continuous data protection copies, combinations of the same or the like.


The destination system 204 further comprises a replication agent 230 in communication with a replication volume 232. In certain embodiments, the replication agent 230 comprises any computing device and/or software module that coordinates the transfer of data to the replication volume 232.


For instance, in certain embodiments, the replication agent 230 instantiates an appropriate number of threads, processes, or routines, for replicating data received from the source storage volume 214 to the replication volume 232. In certain embodiments, the replication agent 230 further includes mapping or correlation information that determines when and to where the data from the source storage volume 214 is copied by the threads. In certain embodiments, such mapping information may be based on system- or user-defined parameters and/or may be automatically generated, such as based on the status of the replication volume 232.


In certain embodiments, the replication agent 230 communicates with the data agent 226 to coordinate data replication. For example, the data agent 226 can open a socket and communicate to the replication agent 230 regarding the transfer of data. For instance, the data agent 226 may request from the replication agent 230 and/or other network management components information that may affect, or be related to, the correlation or mapping of network storage paths for replication data.


The illustrated data replication system 200 further comprises an optional preference database 234 in communication with the network 206. In certain embodiments, the preference database 234 includes storage policies and/or other preferences usable by the replication system 200 in managing data. For instance, the stored preferences may indicate the desired frequency at which data is to be replicated from the source storage volume 214 to the replication volume 232. The preference database 234 may also store path information for detailing to which location(s) on the replication volume 232 data should be copied. In yet other embodiments, the preference database 234 may include storage policies that dictate particular criteria for performing one or more data management operations on the data stored on the replication volume 232.


The replication system 200 advantageously provides for data management operations to be performed on replicated data in order to avoid burdening the source systems. For example, one or more storage operations may be performed on replicated data that represents a recoverable state, or “known good state” of a particular application(s) running on the source system(s).


For instance, in certain embodiments, known good replication copies may be viewed as copies of production volume data. This feature allows a management component in the computing system to directly access, copy, restore, backup or otherwise manipulate the replication copies of production data as if the data was the production data of the source storage volume 214. Such can advantageously improve various system performance characteristics such as access time, reducing memory requirements and reducing impact on source, or client, applications.


In certain embodiments, the replication copies of the production data include time information (such as one or more time stamps) that indicates the source system time when the production data was modified and/or when the subject application was in a known good state. Such time stamps are then associated with copies of the replicated data, thereby allowing for the synchronization of time references between the production data and copies of the replicated data.


For example, FIG. 2 illustrates one or more snapshots 236 associated with the replication volume 232. In certain embodiments, the snapshots 236 comprise point-in-time images of data stored on the replication volume 232. As a result, such snapshots 236 provide copies of the production data on the source system without affecting the performance thereof.



FIG. 3 illustrates a flowchart of a data replication process 300, according to certain embodiments of the invention. In general, the replication process 300 is executed by embodiments of the data replication systems described herein to perform intelligent replication of data in a storage management environment. For exemplary purposes, the replication process 300 will be described hereinafter with reference to the components of the data replication system 200 of FIG. 2.


The replication process 300 begins with Block 305, during which the replication system 200 performs a full backup of data stored on the source storage volume 214. For instance, the full backup operation can comprise the copying of the entire file system on the source storage volume 214 to the replication volume 232. In other embodiments, the full backup can be directed to application-specific data or one or more particular files on the source storage volume 214.


In certain embodiments, the destination system 204 communicates with at least one of the source devices 210, 222 (e.g., with data agent 226) to verify that the source storage volume 214 and the replication volume 232 are synchronized following the full backup or related copy operation.


At Block 310, the journal file 227 tracks logical changes to data on the source storage volume 214. For instance, such changes can comprise modification of the data itself, attribute changes, security changes, combinations of the same or the like. In certain embodiments, the journal file 227 does not maintain a record of the actual change, but only which files were changed without storing additional information. Such embodiments can advantageously conserve memory and/or resources by maintaining relatively small amounts of data in the journal file 227.


At Block 315, the replication system 200 performs a snapshot of the source storage volume 214. In certain embodiments, this process is advantageously performed at a determined replication point, when synchronization of the source storage volume 214 and the replication volume 232 is desired. For example, in certain embodiments, the snapshot is performed in response to instructions received from the data agent 226. In yet other embodiments, the snapshot is performed in response to a call made by one of the source devices 210, 212 to a Microsoft Volume Shadow Copy Service (VSS) driver, a QSNAP driver, or other software-based snapshot implementation.


In certain embodiments, the snapshot of Block 315 can be triggered according to one or more storage policies, such as stored in the preference database 234, that dictate the timing of storage operations between the source storage volume 214 and the replication volume 232. For instance, replication points can be determined by preset copying intervals, time lapsed since the last copy/replication operation, thresholds reached in the journal file 227, replication agent 230 requests for a copy operation, user input, specific parameters or requirements associated with a particular application 220, 222, monitored and/or predicted health of the servers, combinations of the same or the like.


For instance, in certain embodiments, replication can be performed every eight hours, once a day, or the like. In yet other embodiments, certain data-sensitive application data may be copied more frequently than other applications in order to reduce the amount of potential data loss due to a failure occurring between copy operations.


In certain embodiments, during Block 315, writes to the source storage volume 214 are temporarily quiesced, buffered, or otherwise halted during the performance of the snapshot. Once the snapshot is complete, the writes to the source storage volume 214 can immediately resume.


At Block 320, the replication system 200 mounts the snapshot to present a full logical file system to the source devices 210, 212. In certain embodiments, this process comprises mounting or mapping a prepared disk volume onto a standard mount point or mount location, but with a special option that specifies the original file system. For instance, in certain embodiments of the invention, a data agent on either of the source devices 210, 212 can instruct the mounting of the snapshot of the source volume.


At Block 325, the replication process 300 accesses the journal file 227 in view of the mounted snapshot to determine which source files have changed between the time of the full backup (Block 300), or last re-sync, and the capturing of the snapshot (Block 315). In certain embodiments, the data agent on either of the source devices 210, 212 can access the journal file 227 to determine the changed files.


Moreover, in certain embodiments of the invention, the replication process 300 can utilize customized change journal filter drivers executing on each of the source devices 210, 212 to track writes to a given set of files. A list of all changed files can then be consolidated between the devices to determine which extents and/or files have changed during the select period of time. Such a consolidated list can be maintained on one or more source devices, the source storage volume, a storage management module, the replication agent 230 or the like.


Based on the changed files and the mounted snapshot, the replication process 300 then determines the particular blocks that were modified within the changed files (Block 330). In certain embodiments, the replication system 200 compares each modified file on the source storage volume 214 with the corresponding file on the replication volume 232. For instance, the replication system 200 can parse each modified file into chunks (e.g., 64 KB chunks) and compare the chunks with the corresponding destination file via a message-digest algorithm (e.g., MD5) or secure hash algorithm (e.g., SHA-1). In yet other embodiments, other types of checksum algorithms or means for comparison can be used.


At Block 335, the replication system 200 replicates only the changed blocks from the source storage volume 214 to the replication volume 232. Because only changed blocks of the file are replicated, as opposed to the entire file, the replication process 300 advantageously reduces the use of valuable processing power, replication time, and/or network bandwidth.


Following Block 335, the replication process 300 returns to Block 310 to track additional logical changes to files on the source storage volume 214.


Although the replication process 300 has been described with respect to particular arrangements, it will be understood that blocks of the replication process 300 can be combined, divided and/or executed in parallel. For instance, in certain embodiments, the replication system 200 continues to track logical changes to the source storage volume(s) (Block 310) during one or more of the Blocks 320-335.



FIG. 4 illustrates a diagram of block level changes replicated from a single file, according to certain embodiments of the invention. As shown, at time T0, File A is stored on a storage volume 440. In particular, File A comprises four blocks stored in non-contiguous memory locations on the storage volume 440. At this point, the storage volume 440 and a replication volume are preferably synchronized such that a corresponding copy of File A also exists on the replication volume.


Between time T0 and T1, changes are made to the data on the storage volume 440, thereby resulting in a storage volume 440′ with, among other data, File A′. At this point, the journal file (e.g., NTFS change journal) of the particular storage volume indicates that File A′ has been modified twice between time T0 and T1. In order to determine the specific changed blocks, File A′ is compared with the file corresponding to File A on the replication volume, such as via Blocks 315-330 of the replication process 300 of FIG. 3. From this comparison, the replication system determines that block 4 has been modified to block 4′ and that block 5 has been added to File A′.


Based on this comparison, only changed blocks 444 (i.e., blocks 4′ and 5) are sent to the destination system to update the replication volume. Other unchanged blocks of File A′, or other files, are not replicated.



FIG. 5 illustrates a flowchart of another data replication process 500, according to certain embodiments of the invention. In general, the replication process 500 is executed by embodiments of the data replication systems described herein to perform one or more storage operations on replicated data. For exemplary purposes, the replication process 500 will be described hereinafter with reference to the components of the data replication system 200 of FIG. 2.


At Block 505, the replication process 500 determines if application data on the source storage volume 214 is in a consistent or recoverable state. In certain embodiments, such a state may be defined as when particular computing operations of the respective application(s) 220, 222 are complete to a point such that further operation, recovery and/or rolling back of the application data may occur, based on the recorded data, without the loss of critical information or computing operations needed for operation of the application(s) 220, 222.


In certain embodiments, data agents residing on the source devices 210, 212 can determine if the particular application(s) associated with the data are in a known good state. At the known good state, write requests to the source storage volume 214 are quiesced (Block 510) and a snapshot is taken of the source storage volume 214 (Block 515). In yet other embodiments, the data agents can instruct the applications 220, 222 to place themselves in the known good state and to temporarily suspend data management operations to the source storage volume 214 in order to prepare for replication. For instance, in certain embodiments, the data agent utilizes the VSS driver or QSNAP driver to quiesce the applications 220, 222.


In certain embodiments, the data agent instructs the quiescing of the applications 220, 222 through an application programming interface (API). For instance, the data agent 226 may execute a command or process (e.g., FLRSNAP.TOOL) that causes the application 220 to quiesce. When the application 220 has placed itself in a known good state, the application 220 may send an acknowledgment to the data agent 226.


The frequency of known good states can vary and may depend on one or more system factors or user-selectable parameters. For instance, storage policies stored in one or more databases of the replication system 200 (e.g., the preference database 234) can dictate the frequency at which the discrete data replication process is performed. Moreover, it should be recognized that each point of data replication need not be performed at a known good state of the application. Rather, discrete data replication (including the taking of snapshots of the source storage volume 214) can also be performed when the source data is not in a known good state.


In certain embodiments, once the data management operations are suspended, the I/O buffers in the data path of the applications 220, 222 are flushed (and/or the writes in the queues are flushed). For example, some or all of the pending data management operations (e.g., as of the time of the quiescing of the application) may be allowed to complete and/or percolate through the data paths. In certain embodiments, this ensures that the snapshot 228 of the source storage volume 214 captures the application data in a known good state.


Notwithstanding the foregoing, it will be understood that, in certain embodiments, although applications 220, 222 are quiesced, they need not actually pause or suspend operation during the quiescent period. Rather, the applications 220, 222 may continue to operate substantially normally but may queue internally, or otherwise buffer, data management operations intended for the source storage volume 214. After the quiescent period, the buffered modification operations may be allowed to complete (i.e., be sent to the source storage volume 214).


In yet other embodiments, quiescing of the application 220 may be performed based on an automatic reporting procedure. For instance, a module of the replication system 200 may be configured to gather, receive and/or analyze information associated with a failure rate and/or health of applicable servers. Additional details of such status monitoring are provided in U.S. patent application Ser. No. 11/120,619, filed May 2, 2005, now U.S. Pat. No. 7,343,453, issued Mar. 11, 2008, which is hereby incorporated herein by reference in its entirety.


For example, the frequency of replication points may be selected or adjusted to mitigate risks detected in a storage network. In certain embodiments, one or more management components of the replication system 200 may identify a storage-related characteristic and may modify the frequency of replication points if the storage-related characteristic satisfies one or more particular risk criteria. For instance, risk criteria may be indicated by storage policies, storage definitions, a service level agreement (“SLA”) or other information located in a management component database or other component of the replication system 200. In certain further embodiments, the frequency of replication points may be based at least in part on a level of data protection or data availability in the replication system 200.


The process 500 then replicates the blocks of data that have changed since the previous known good state (Block 520). For instance, in certain embodiments, the process 500 can follow Blocks 310-335 of the replication process 300 of FIG. 3. In certain embodiments, such replication further includes the transmission of time information indicative of the source system time of the known good state of the application data (e.g., time of replication point at which snapshot is taken of source storage volume 214). Such time information can be in the form of a time stamp, a log entry, or like information associated with a clock of the source system and/or source storage volume 214.


Because replication of the changed blocks can advantageously be performed at a time at which the source storage volume data is in a consistent state, Block 520 results in the data on the replication volume 232 also being in a consistent state. At Block 525, one or more storage operations can then be performed on the replicated data. For instance, the replication agent 230 or other module can cause a snapshot operation to be performed on the data of the replication volume 232.


At Block 530, the snapshot of the replicated data is associated with a time stamp representing the time of the known good state of the application(s). In certain preferred embodiments, when the snapshot, or other storage operation, is performed, the time of the snapshot is logically associated with the source system time of the known good state of the application data. For instance, a time stamp generated by the source system can be used to logically assign a “time” to the snapshot of the replicated data. In such a process, the snapshot of the replicated data then appears as if the snapshot was directly taken of the data in the source system.


In certain embodiments, the logical associations of time with respect to the snapshot 236 may be stored jointly with the snapshot and/or in a separate database. For instance, the logical time associations may be stored in an index on one or more replication volumes, on the replication agent 230, in the preference database 234, in a storage manager database index, by the data agent 226, combinations of the same or the like. In certain embodiments, stored jointly with the “updated” time data may also be the actual location of the snapshot 236 on the replication volume 232 or other storage device(s).


The process 500 also resumes writes to the source storage volume 214 (Block 535). In certain embodiments, Block 535 can be performed at any time after the snapshot is taken of the source storage volume 214 (Block 515). Thus, because the storage operations of Blocks 525 and 530 are performed on the replicated data of the replication volume 232, the production or primary data on the source storage volume 214 is not needed or affected by such operations. This also advantageously allows for writes to resume from the applications 220, 222 without needing to wait for performance of the one or more storage operations.


Although the replication process 500 has been described with reference to particular arrangements, various alternative embodiments can also be used. For instance, a wide variety of other storage operations other than, or in addition to snapshots, can be performed on the replication data, such as, but not limited to, creation, storage, retrieval, backup, migration, deletion, auxiliary copies, incremental copies, differential copies, hierarchical storage management (“HSM”) copies, archive copies, information lifecycle management (“ILM”) copies, other types of copies and versions of electronic data or the like.


In yet other embodiments, the replication system 200 may use the replication data to create a shadow version of the data on the source storage volume 214. In such embodiments, if there is a failure and/or overload of the source storage volume 214, the source devices 210, 212 can be redirected to the shadowed version of the data.


In yet other embodiments, different types of data management operations may be performed on the replication data depending on one or more schedule policies. For example, a snapshot storage operation may be scheduled to be performed on the replication data every five minutes, while a differential backup may be performed on the replication data every hour. Furthermore, a full backup may be scheduled to be performed once a day. Such scheduling policies may be advantageously determined to satisfy the needs of the user while reducing the impact on system resources.



FIG. 6 illustrates a block diagram of a data replication system 600 having a single source system, according to certain embodiments of the invention. In certain embodiments, the data replication system 600 can perform similar data replication processes as those described herein with reference to FIGS. 1-5, except that the system 600 does not comprise a clustered file system arrangement. Thus, to simplify the description, components of the replication system 600 will not be redescribed in detail if they were described above. Moreover, the components will be given a reference numeral that retains the same last two digits as the reference numeral used to describe the replication system 200 of FIG. 2 and will be preceded with a numeral “6.”


As illustrated, the replication system 600 comprises a source system 602 that communicates with a destination system 604 over a network 606. In general, the data replication system 600 is configured to perform discrete data replication with respect to data stored on a source storage device 614.


The source system 602 further comprises application(s) 620 that access data stored on the source storage device 614. In certain embodiments, such access is via a file system that organizes files and directories accessible by the source system 602. The file system may include, for example, a local file system, a network file system, a file server, a management program or the like, or may include multiple file systems accessible by an operating system. For instance, in embodiments wherein the source storage device 614 is associated with multiple volumes, each volume may be associated with its own file system, or a single file system may span across the multiple volumes.


The source system 602 further comprises a data agent 626 responsible for performing data and/or storage tasks related to the source system 602. For example, the data agent 626 can manage and/or coordinate replication, archiving, migrating, and/or recovery of the source system data.


In certain embodiments, the source system 602 comprises a plurality of data agents 626, each of which performs data management operations related to data associated with each application. In such embodiments, each data agent 626 can monitor various files, folders, registry files and/or system resources that are impacted by a particular application. For instance, the data agent 626 can be programmed to detect data management requests by a particular application and determine which files, folders and/or system resources are associated with the data management requests. In yet other embodiments, the data agent 626 can work with data from multiple applications 620.


The source storage device 614 further comprises a journal file 627 that tracks when a particular file on the storage device has been changed or modified. In certain embodiments, the journal file 627 comprises a change journal or other journaling module as disclosed herein. In yet other embodiments, such tracking can be performed by the source system 602, such as through the data agent 626 and/or a filter driver on the source system 602. Examples of such tracking are described in more detail in U.S. patent application Ser. No. 11/640,829, filed Dec. 18, 2006, now U.S. Pat. No. 7,617,262, issued Nov. 10, 2009, which is hereby incorporated herein by reference in its entirety.


As further illustrated, the source storage device 614 also comprises one or more snapshots 628 or other means for providing a point-in-time image of the data on the source storage device 614.


The destination system 604 comprises a replication agent 630 in communication with a replication volume 632. In certain embodiments, the replication agent 630 comprises any computing device and/or software modules that coordinate the transfer of data to the replication volume 632. The illustrated data replication system 600 further comprises an optional preference database 634 in communication with the network 606.


Like certain replication systems disclosed herein, the replication system 600 is configured to perform intelligent data replication of data on a storage volume. In certain embodiments, the data replication is performed at discrete points in time and comprises copying only changed blocks of data to a destination system. This process can be performed, for example, by comparing, on a block-by-block basis, modified files with corresponding files on a destination system (e.g., via the replication processes 300, 500).


Although data replication systems have been disclosed herein with reference to certain embodiments, other embodiments can take on different arrangements or include more or fewer components without departing from the scope of the disclosure. For example, any of the replication systems 100, 200 or 600 can further include a storage manager that communicates with source and replication systems (e.g., through a network).


In certain embodiments, the storage manager is a software module or application configured to direct the performance of one or more storage operations and, in particular, the replication of data from the source system(s) to the replication system(s). In further embodiments, the storage manager may perform one or more of the operations or functions described above with respect to the data agents and/or the replication agents. For instance, the storage manager may direct and/or coordinate the performance of one or more storage operations on replicated data (e.g., snapshots of the replicated data).


In certain embodiments, the storage manager maintains an index, such as in a cache, for storing information relating to: logical relationships and associations between components of the replication systems, user preferences, management tasks, and/or other useful data. For example, the storage manager may use its index to track the location and timestamps of one or more snapshots of the replicated data.


The storage manager may also use its index to track the status of data management operations to be performed, storage patterns associated with the system components such as media use, storage growth, network bandwidth, Service Level Agreement (“SLA”) compliance levels, data protection levels, storage policy information, storage criteria associated with user preferences, retention criteria, storage operation preferences, and other storage-related information. The index may typically reside on the storage manager's hard disk and/or other database.


In other embodiments, the storage manager may alert the user or system when a particular resource of the replication system is unavailable or congested or when components are unavailable due to hardware failure, software problems, or other reasons. In certain embodiments, the storage manager may utilize replication system data to suggest solutions to such problems when they occur or even before they occur. For example, the storage manager might alert the user that a storage device in the replication system was full or otherwise congested, and then suggest, based on job and data storage information contained in its index cache, an alternate storage device. In yet further embodiments, the storage manager or other system component may take action to remedy the problem at issue. For example, the storage manager may perform load balancing, error correction, or the like, based on information received regarding the replication system.


Moreover, the storage manager may include an interface agent module (not shown). In certain embodiments, the interface agent module may provide presentation logic, such as a graphical user interface (“GUI”), an API, or other interface by which users and system processes may be able to retrieve information about the status of storage operations and issue instructions to the replication systems regarding the performance of storage operations. For example, a user may modify the schedule of a number of pending snapshot copies or other types of copies. As another example, a user may use the GUI to view the status of all storage operations currently pending in the replication system or the status of particular components in the replication system.


Additional details of storage manager modules useful with embodiments of the replication systems disclosed herein are described in U.S. Pat. No. 7,389,311, issued Jun. 17, 2008, which is hereby incorporated herein by reference in its entirety.


Moreover, in certain embodiments of the invention, data replication 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, which is hereby incorporated herein by reference in its entirety. For example, the data replication system may be part of a storage operation cell 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 include CommCells as embodied in the SIMPANA, QNET, and/or QINETIX storage management systems by. CommVault Systems, Inc. (Oceanport, N.J.), and as further described in U.S. Pat. No. 7,454,569, issued Nov. 18, 2008, which is hereby incorporated herein by reference in its entirety.


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 flowchart illustrations and/or block diagrams of methods, apparatus (systems) and computer program products. It will be understood that each block of the flowchart illustrations and/or block diagrams, and combinations of blocks in the flowchart 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 flowchart 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 flowchart 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 that execute on the computer or other programmable apparatus provide steps for implementing the acts specified in the flowchart 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.

Claims
  • 1. A method for replicating data in a computer network from a source storage device to a destination storage device, the method comprising: replicating at a first time source data by copying the source data to create replication data, wherein the source data is stored on at least one source storage device associated with a source system, the source system comprising one or more source computer devices, the source data comprising a plurality of source files generated by one or more applications executing on the source system, andwherein the replication data is stored on at least one destination storage device associated with a replication system comprising one or more replication computer devices, wherein the one or more replication computer devices are different than the one or more source computer devices, the replication data comprising a plurality of destination files corresponding to the plurality of source files;following the replicating, identifying, by the source system, changed source files by tracking at a logical file level which of the plurality of source files changed between the first time and a second time after the first time, wherein said tracking comprises maintaining a journal file on the source storage device with entries identifying the changed source files at the logical file level;providing from the source system to the replication system, the changed source files at the logical file level by mounting the changed source files on the replication system wherein the replication system uses the mounting to obtain the logical file level associated with the changed source files;using the one or more replication computer devices associated with the replication system to identify, based on the changed source files at the logical file level, previously replicated destination files that are related to the changed source files;performing with one or more of the source computer devices associated with the source system, a source snapshot of the source data to capture a point-in-time copy of the source data on a block-by-block basis at the second time;accessing, with the one or more replication computer devices associated with the replication system, data blocks in the source snapshot with the mounting;comparing, with the one or more replication computer devices associated with the replication system, the data blocks in the source snapshot with data blocks in the previously replicated destination files stored on the at least one destination storage device on a block-by-block basis to identify changed blocks in the changed source files in the source data;replicating, with the one or more replication computer devices associated with the replication system, the changed blocks of the changed source files by determining with the one or more replication computer devices which copies of the changed data blocks to replicate from the source system to the at least one destination storage device; andnot replicating unchanged blocks associated with the changed source files.
  • 2. The method of claim 1, additionally comprising, prior to performing the snapshot, quiescing one or more applications having access to the source data on the source storage device.
  • 3. The method of claim 2, wherein said quiescing is performed at a known good state of the one or more applications.
  • 4. The method of claim 2, additionally comprising instructing the one or more applications to assume a known good state.
  • 5. The method of claim 1, wherein the source storage device comprises a shared storage device.
  • 6. The method of claim 1, additionally comprising transmitting with the changed blocks time information indicative of the second time, wherein the time information is relative to a clock associated with the source storage device.
  • 7. The method of claim 6, additionally comprising, following said replicating the changed blocks: performing a storage operation on the replication data to generate copied data; andlogically associating the copied data with the time information indicative of the second time.
  • 8. The method of claim 1, wherein the duration between the first time and the second time is based on a storage policy stored in a preference database.
  • 9. A system for performing data replication in a computer network environment, the data replication from a first storage device to a replication storage device, the system comprising: a source system comprising one or more source computer devices and at least a first storage device configured to store source data as a plurality of source files, the source system having one or more applications executing thereon and operative to write data to the plurality of source files stored on the first storage device;a replication system comprising one or more replication computer devices, wherein the one or more replication computer devices are different than the one or more source computer devices, the replication system configured to store replication data that is a replication of the source data at a first time, the replication data stored on at least one replication storage device associated with the replication system, the replication data comprising a plurality of destination files corresponding to the plurality of source filesa journal module configured to identify changed source files at a logical file level by tracking changes at the logical file level to the plurality of source files on the first storage device between a first time and a second time after the first time, the journal module tracking the changes at least partly by maintaining a journal file with entries identifying changed source files at the logical file level; andwherein the replication system receives a copy of the changed source files at the logical file level by mounting the changed source files on the replication system wherein the replication system uses the mounting to obtain the logical file level associated with the changed source files;a data agent module configured to execute on one or more of the first plurality of computer devices, the data agent module further configured to: instruct a creation of a source snapshot of the source data with the one or more source computer devcies to capture a point-in-time copy of the source data on a block-by-block basis at the second time;wherein the one or more replication computer devices associated with the replication system identify, based on the changed source files at the logical file level, the replication system identifies previously replicated destination files that are related to the changed source files;the one or more replication computers devices associated with the replication system accesses data blocks in the source snapshot with the mounting;the one or more replication computer devices associated with the replication system compares the data blocks in the source snapshot with data blocks in the replicated destination files stored on the at least one destination storage device on a block-by-block basis to identify changed blocks in the changed source files in the source data; andthe one or more replication computer devices associated with the replication system replicates the changed blocks of the changed source files to the replication copy on the replication storage device by determining with the one or more replication computer devices which copies of the changed data blocks to replicate from the source system to the at least one destination storage device and which unchanged blocks associated with the changed source files are not replicated.
  • 10. The system of claim 9, wherein the first storage device is a shared storage device.
  • 11. The system of claim 10, wherein the journal module comprises a new technology file system (NTFS) change journal.
  • 12. The system of claim 9, wherein the changed blocks are identified using a secure hash algorithm.
  • 13. The system of claim 9, wherein the source data consists essentially of application-specific data.
  • 14. The system of claim 9, wherein the replication system further comprises a replication module in communication with the replication storage device, the replication module being in network communication with the data agent.
  • 15. The system of claim 14, wherein the replication module is further configured to direct a storage operation to be performed on at least a portion of the replication files to generate copied data.
  • 16. The system of claim 15, wherein the replication module is further configured to logically associate the copied data with a time stamp indicative of the second time.
  • 17. The system of claim 16, wherein the second time identifies a time at which the source data is in a known good state.
RELATED APPLICATION

This application claims the benefit of priority under 35 U.S.C. §119(e) of U.S. Provisional Patent Application No. 61/121,438, entitled “Systems and Methods for Performing Discrete Data Replication,” filed Dec. 10, 2008, which is hereby incorporated herein by reference in its entirety to be considered part of this specification.

US Referenced Citations (654)
Number Name Date Kind
4296465 Lemak Oct 1981 A
4686620 Ng Aug 1987 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
5231668 Kravitz Jul 1993 A
5239647 Anglin et al. Aug 1993 A
5241668 Eastridge et al. Aug 1993 A
5241670 Eastridge et al. Aug 1993 A
5263154 Eastridge et al. Nov 1993 A
5265159 Kung Nov 1993 A
5276860 Fortier et al. Jan 1994 A
5276867 Kenley et al. Jan 1994 A
5287500 Stoppani, Jr. Feb 1994 A
5301351 Jippo Apr 1994 A
5311509 Heddes et al. May 1994 A
5317731 Dias et al. May 1994 A
5321816 Rogan et al. Jun 1994 A
5333315 Saether et al. Jul 1994 A
5347653 Flynn et al. Sep 1994 A
5369757 Spiro et al. Nov 1994 A
5403639 Belsan et al. Apr 1995 A
5410700 Fecteau et al. Apr 1995 A
5448724 Hayashi et al. Sep 1995 A
5455926 Keele et al. Oct 1995 A
5487072 Kant 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
5546536 Davis et al. Aug 1996 A
5555404 Torbjornsen et al. Sep 1996 A
5559957 Balk Sep 1996 A
5559991 Kanfi Sep 1996 A
5598546 Blomgren Jan 1997 A
5604862 Midgely et al. Feb 1997 A
5606693 Nilsen et al. Feb 1997 A
5615392 Harrison et al. Mar 1997 A
5619644 Crockett et al. Apr 1997 A
5638509 Dunphy et al. Jun 1997 A
5642496 Kanfi Jun 1997 A
5668986 Nilsen et al. Sep 1997 A
5673381 Huai et al. Sep 1997 A
5675511 Prasad et al. Oct 1997 A
5677900 Nishida et al. Oct 1997 A
5682513 Candelaria et al. Oct 1997 A
5687343 Fecteau et al. Nov 1997 A
5689706 Rao et al. Nov 1997 A
5699361 Ding et al. Dec 1997 A
5719786 Nelson et al. Feb 1998 A
5720026 Uemura et al. Feb 1998 A
5729743 Squibb Mar 1998 A
5737747 Vishlitsky et al. Apr 1998 A
5742792 Yanai et al. Apr 1998 A
5745753 Mosher, Jr. Apr 1998 A
5751997 Kullick et al. May 1998 A
5758359 Saxon May 1998 A
5761677 Senator et al. Jun 1998 A
5761734 Pfeffer et al. Jun 1998 A
5764972 Crouse et al. Jun 1998 A
5765173 Cane et al. Jun 1998 A
5778395 Whiting et al. Jul 1998 A
5790114 Geaghan et al. Aug 1998 A
5790828 Jost Aug 1998 A
5802265 Bressoud et al. Sep 1998 A
5805920 Sprenkle et al. Sep 1998 A
5812398 Nielsen Sep 1998 A
5813009 Johnson et al. Sep 1998 A
5813017 Morris Sep 1998 A
5829046 Tzelnic et al. Oct 1998 A
5860104 Witt et al. Jan 1999 A
5875478 Blumenau Feb 1999 A
5875481 Ashton et al. Feb 1999 A
5878408 Van Huben et al. Mar 1999 A
5887134 Ebrahim Mar 1999 A
5901327 Ofek May 1999 A
5907621 Bachman et al. May 1999 A
5907672 Matze et al. May 1999 A
5924102 Perks Jul 1999 A
5926836 Blumenau Jul 1999 A
5933104 Kimura Aug 1999 A
5933601 Fanshier et al. Aug 1999 A
5950205 Aviani, Jr. Sep 1999 A
5956519 Wise et al. Sep 1999 A
5958005 Thorne et al. Sep 1999 A
5970233 Lie et al. Oct 1999 A
5970255 Tran et al. Oct 1999 A
5974563 Beeler, Jr. Oct 1999 A
5987478 See et al. Nov 1999 A
5991779 Bejar Nov 1999 A
5995091 Near et al. Nov 1999 A
6003089 Shaffer et al. Dec 1999 A
6009274 Fletcher et al. Dec 1999 A
6012090 Chung et al. Jan 2000 A
6021415 Cannon et al. Feb 2000 A
6021475 Nguyen et al. Feb 2000 A
6023710 Steiner et al. Feb 2000 A
6026414 Anglin Feb 2000 A
6049889 Steely, Jr. et al. Apr 2000 A
6052735 Ulrich et al. Apr 2000 A
6058066 Norris et al. May 2000 A
6061692 Thomas et al. May 2000 A
6072490 Bates et al. Jun 2000 A
6076148 Kedem et al. Jun 2000 A
6088697 Crockett et al. Jul 2000 A
6094416 Ying Jul 2000 A
6105129 Meier et al. Aug 2000 A
6112239 Kenner et al. Aug 2000 A
6122668 Teng et al. Sep 2000 A
6131095 Low et al. Oct 2000 A
6131148 West et al. Oct 2000 A
6131190 Sidwell Oct 2000 A
6137864 Yaker Oct 2000 A
6148377 Carter et al. Nov 2000 A
6148412 Cannon et al. Nov 2000 A
6154787 Urevig et al. Nov 2000 A
6154852 Amundson et al. Nov 2000 A
6158044 Tibbetts Dec 2000 A
6161111 Mutalik et al. Dec 2000 A
6163856 Dion et al. Dec 2000 A
6167402 Yeager Dec 2000 A
6175829 Li et al. Jan 2001 B1
6195695 Cheston et al. Feb 2001 B1
6205450 Kanome et al. Mar 2001 B1
6212512 Barney et al. Apr 2001 B1
6212521 Minami et al. Apr 2001 B1
6230164 Rikieta et al. May 2001 B1
6260068 Zalewski et al. Jul 2001 B1
6260069 Anglin Jul 2001 B1
6269431 Dunham Jul 2001 B1
6275953 Vahalia et al. Aug 2001 B1
6279078 Sicola et al. Aug 2001 B1
6292783 Rohler Sep 2001 B1
6301592 Aoyama et al. Oct 2001 B1
6304880 Kishi Oct 2001 B1
6311193 Sekido et al. Oct 2001 B1
6324581 Xu et al. Nov 2001 B1
6328766 Long Dec 2001 B1
6330570 Crighton et al. Dec 2001 B1
6330642 Carteau Dec 2001 B1
6343324 Hubis et al. Jan 2002 B1
6350199 Williams et al. Feb 2002 B1
RE37601 Eastridge et al. Mar 2002 E
6353878 Dunham Mar 2002 B1
6356801 Goodman et al. Mar 2002 B1
6363464 Mangione Mar 2002 B1
6366986 St. Pierre et al. Apr 2002 B1
6366988 Skiba et al. Apr 2002 B1
6374336 Peters et al. Apr 2002 B1
6374363 Wu et al. Apr 2002 B1
6389432 Pothapragada et al. May 2002 B1
6397308 Ofek et al. May 2002 B1
6418478 Ignatius et al. Jul 2002 B1
6421711 Blumenau et al. Jul 2002 B1
6434681 Armangau Aug 2002 B1
6438595 Blumenau et al. Aug 2002 B1
6466950 Ono Oct 2002 B1
6473775 Kusters et al. Oct 2002 B1
6487561 Ofek et al. Nov 2002 B1
6487644 Huebsch et al. Nov 2002 B1
6487645 Clark et al. Nov 2002 B1
6502205 Yanai et al. Dec 2002 B1
6516314 Birkler et al. Feb 2003 B1
6516327 Zondervan et al. Feb 2003 B1
6516348 MacFarlane et al. Feb 2003 B1
6519679 Devireddy et al. Feb 2003 B2
6538669 Lagueux, Jr. et al. Mar 2003 B1
6539462 Mikkelsen et al. Mar 2003 B1
6542468 Hatakeyama Apr 2003 B1
6542909 Tamer et al. Apr 2003 B1
6542972 Ignatius et al. Apr 2003 B2
6564228 O'Connor May 2003 B1
6564229 Baweja et al. May 2003 B1
6564271 Micalizzi, Jr. et al. May 2003 B2
6581143 Gagne et al. Jun 2003 B2
6604118 Kleinman et al. Aug 2003 B2
6604149 Deo et al. Aug 2003 B1
6611849 Raff et al. Aug 2003 B1
6615223 Shih et al. Sep 2003 B1
6629189 Sandstrom Sep 2003 B1
6631477 LeCrone et al. Oct 2003 B1
6631493 Ottesen et al. Oct 2003 B2
6647396 Parnell et al. Nov 2003 B2
6647473 Golds et al. Nov 2003 B1
6651075 Kusters et al. Nov 2003 B1
6654825 Clapp et al. Nov 2003 B2
6658436 Oshinsky et al. Dec 2003 B2
6658526 Nguyen et al. Dec 2003 B2
6662198 Satyanarayanan et al. Dec 2003 B2
6665815 Goldstein et al. Dec 2003 B1
6681230 Blott et al. Jan 2004 B1
6691209 O'Connell Feb 2004 B1
6721767 De Meno et al. Apr 2004 B2
6728733 Tokui Apr 2004 B2
6732124 Koseki et al. May 2004 B1
6732125 Autrey et al. May 2004 B1
6742092 Huebsch et al. May 2004 B1
6748504 Sawdon et al. Jun 2004 B2
6751635 Chen et al. Jun 2004 B1
6757794 Cabrera et al. Jun 2004 B2
6760723 Oshinsky et al. Jul 2004 B2
6763351 Subramaniam et al. Jul 2004 B1
6789161 Blendermann et al. Sep 2004 B1
6792472 Otterness et al. Sep 2004 B1
6792518 Armangau et al. Sep 2004 B2
6799258 Linde Sep 2004 B1
6820035 Zahavi Nov 2004 B1
6836779 Poulin Dec 2004 B2
6839724 Manchanda et al. Jan 2005 B2
6871163 Hiller et al. Mar 2005 B2
6871271 Ohran et al. Mar 2005 B2
6880051 Timpanaro-Perrotta Apr 2005 B2
6886020 Zahavi et al. Apr 2005 B1
6892211 Hitz et al. May 2005 B2
6912482 Kaiser Jun 2005 B2
6925476 Multer et al. Aug 2005 B1
6925512 Louzoun et al. Aug 2005 B2
6938135 Kekre et al. Aug 2005 B1
6938180 Dysert et al. Aug 2005 B1
6941393 Secatch Sep 2005 B2
6944796 Joshi et al. Sep 2005 B2
6952705 Knoblock et al. Oct 2005 B2
6952758 Chron et al. Oct 2005 B2
6954834 Slater et al. Oct 2005 B2
6968351 Butterworth Nov 2005 B2
6973553 Archibald, Jr. et al. Dec 2005 B1
6978265 Schumacher Dec 2005 B2
6981177 Beattie Dec 2005 B2
6983351 Gibble et al. Jan 2006 B2
6993539 Federwisch et al. Jan 2006 B2
7003519 Biettron et al. Feb 2006 B1
7003641 Prahlad et al. Feb 2006 B2
7007046 Manley et al. Feb 2006 B2
7020669 McCann et al. Mar 2006 B2
7032131 Lubbers et al. Apr 2006 B2
7035880 Crescenti et al. Apr 2006 B1
7039661 Ranade May 2006 B1
7051050 Chen et al. May 2006 B2
7062761 Slavin et al. Jun 2006 B2
7065538 Aronoff et al. Jun 2006 B2
7068597 Fijolek et al. Jun 2006 B1
7082441 Zahavi et al. Jul 2006 B1
7085787 Beier et al. Aug 2006 B2
7085904 Mizuno et al. Aug 2006 B2
7093012 Olstad et al. Aug 2006 B2
7096315 Takeda et al. Aug 2006 B2
7103731 Gibble et al. Sep 2006 B2
7103740 Colgrove et al. Sep 2006 B1
7106691 Decaluwe et al. Sep 2006 B1
7107298 Prahlad et al. Sep 2006 B2
7107395 Ofek et al. Sep 2006 B1
7111021 Lewis et al. Sep 2006 B1
7120757 Tsuge Oct 2006 B2
7130860 Pachet Oct 2006 B2
7130970 Devassy et al. Oct 2006 B2
7139932 Watanabe Nov 2006 B2
7155465 Lee et al. Dec 2006 B2
7155633 Tuma et al. Dec 2006 B2
7158985 Liskov Jan 2007 B1
7177866 Holenstein et al. Feb 2007 B2
7181477 Saika et al. Feb 2007 B2
7188292 Cordina et al. Mar 2007 B2
7191198 Asano et al. Mar 2007 B2
7194454 Hansen et al. Mar 2007 B2
7194487 Kekre et al. Mar 2007 B1
7200620 Gupta Apr 2007 B2
7203807 Urabe et al. Apr 2007 B2
7209972 Ignatius et al. Apr 2007 B1
7225204 Manley et al. May 2007 B2
7225208 Midgley et al. May 2007 B2
7225210 Guthrie, II. May 2007 B2
7228456 Lecrone et al. Jun 2007 B2
7231391 Aronoff et al. Jun 2007 B2
7231544 Tan et al. Jun 2007 B2
7234115 Sprauve et al. Jun 2007 B1
7246140 Therrien et al. Jul 2007 B2
7246207 Kottomtharayil et al. Jul 2007 B2
7250963 Yuri et al. Jul 2007 B2
7257689 Baird Aug 2007 B1
7269612 Devarakonda et al. Sep 2007 B2
7269641 Powers et al. Sep 2007 B2
7272606 Borthakur et al. Sep 2007 B2
7275138 Saika Sep 2007 B2
7275177 Armangau et al. Sep 2007 B2
7278142 Bandhole et al. Oct 2007 B2
7284153 Okbay et al. Oct 2007 B2
7287047 Kavuri Oct 2007 B2
7293133 Colgrove et al. Nov 2007 B1
7296125 Ohran Nov 2007 B2
7315923 Retnamma et al. Jan 2008 B2
7318134 Oliveira et al. Jan 2008 B1
7340652 Jarvis et al. Mar 2008 B2
7343356 Prahlad et al. Mar 2008 B2
7343365 Farnham et al. Mar 2008 B2
7343453 Prahlad et al. Mar 2008 B2
7343459 Prahlad et al. Mar 2008 B2
7346623 Prahlad et al. Mar 2008 B2
7346751 Prahlad et al. Mar 2008 B2
7356657 Mikami Apr 2008 B2
7359917 Winter et al. Apr 2008 B2
7363444 Ji Apr 2008 B2
7370232 Safford May 2008 B2
7373364 Chapman May 2008 B1
7380072 Kottomtharayil et al. May 2008 B2
7383293 Gupta et al. Jun 2008 B2
7389311 Crescenti et al. Jun 2008 B1
7392360 Aharoni et al. Jun 2008 B1
7395282 Crescenti et al. Jul 2008 B1
7401064 Arone et al. Jul 2008 B1
7409509 Devassy et al. Aug 2008 B2
7415488 Muth et al. Aug 2008 B1
7428657 Yamasaki Sep 2008 B2
7430587 Malone et al. Sep 2008 B2
7433301 Akahane et al. Oct 2008 B2
7440982 Lu et al. Oct 2008 B2
7457980 Yang et al. Nov 2008 B2
7461230 Gupta et al. Dec 2008 B1
7464236 Sano et al. Dec 2008 B2
7467167 Patterson Dec 2008 B2
7467267 Mayock Dec 2008 B1
7469262 Baskaran et al. Dec 2008 B2
7472238 Gokhale Dec 2008 B1
7472312 Jarvis et al. Dec 2008 B2
7475284 Koike Jan 2009 B2
7490207 Amarendran et al. Feb 2009 B2
7496589 Jain et al. Feb 2009 B1
7496690 Beverly et al. Feb 2009 B2
7500053 Kavuri et al. Mar 2009 B1
7500150 Sharma et al. Mar 2009 B2
7502902 Sato Mar 2009 B2
7509316 Greenblatt et al. Mar 2009 B2
7512601 Cucerzan et al. Mar 2009 B2
7516088 Johnson et al. Apr 2009 B2
7523483 Dogan Apr 2009 B2
7529745 Ahluwalia et al. May 2009 B2
7529748 Wen et al. May 2009 B2
7529782 Prahlad et al. May 2009 B2
7529898 Nguyen et al. May 2009 B2
7532340 Koppich et al. May 2009 B2
7533181 Dawson et al. May 2009 B2
7536291 Retnamma et al. May 2009 B1
7539707 Prahlad et al. May 2009 B2
7539835 Kaiser May 2009 B2
7543125 Gokhale Jun 2009 B2
7546324 Prahlad et al. Jun 2009 B2
7546364 Raman et al. Jun 2009 B2
7552358 Asgar-Deen et al. Jun 2009 B1
7565572 Yamasaki Jul 2009 B2
7581077 Ignatius et al. Aug 2009 B2
7590668 Kathuria et al. Sep 2009 B2
7593966 Therrien et al. Sep 2009 B2
7596586 Gokhale et al. Sep 2009 B2
7606841 Ranade Oct 2009 B1
7606844 Kottomtharayil Oct 2009 B2
7607037 LeCrone et al. Oct 2009 B1
7613748 Brockway et al. Nov 2009 B2
7613750 Valiyaparambil et al. Nov 2009 B2
7617253 Prahlad et al. Nov 2009 B2
7617262 Prahlad et al. Nov 2009 B2
7617321 Clark Nov 2009 B2
7617369 Bezbaruah et al. Nov 2009 B1
7617541 Plotkin et al. Nov 2009 B2
7627598 Burke Dec 2009 B1
7627617 Kavuri et al. Dec 2009 B2
7634477 Hinshaw Dec 2009 B2
7636743 Erofeev Dec 2009 B2
7651593 Prahlad et al. Jan 2010 B2
7661028 Erofeev Feb 2010 B2
7668798 Scanlon et al. Feb 2010 B2
7669029 Mishra et al. Feb 2010 B1
7672979 Appellof et al. Mar 2010 B1
7673000 Smoot et al. Mar 2010 B2
7685126 Patel Mar 2010 B2
7689467 Belanger et al. Mar 2010 B1
7694086 Bezbaruah et al. Apr 2010 B1
7702533 Barnard et al. Apr 2010 B2
7702670 Duprey et al. Apr 2010 B1
7707184 Zhang et al. Apr 2010 B1
7716171 Kryger May 2010 B2
7734715 Hyakutake et al. Jun 2010 B2
7739235 Rousseau et al. Jun 2010 B2
7809691 Karmarkar et al. Oct 2010 B1
7810067 Kaelicke et al. Oct 2010 B2
7831553 Prahlad et al. Nov 2010 B2
7831622 Prahlad et al. Nov 2010 B2
7840533 Prahlad et al. Nov 2010 B2
7870355 Erofeev Jan 2011 B2
7904681 Bappe Mar 2011 B1
7930476 Castelli et al. Apr 2011 B1
7962455 Erofeev Jun 2011 B2
7962709 Agrawal Jun 2011 B2
8005795 Galipeau et al. Aug 2011 B2
8024294 Kottomtharayil Sep 2011 B2
8121983 Prahlad et al. Feb 2012 B2
8190565 Prahlad et al. May 2012 B2
8195623 Prahlad et al. Jun 2012 B2
8271830 Erofeev Sep 2012 B2
8285684 Prahlad et al. Oct 2012 B2
8291101 Yan et al. Oct 2012 B1
8352422 Prahlad et al. Jan 2013 B2
8463751 Kottomtharayil Jun 2013 B2
8489656 Erofeev Jul 2013 B2
8504515 Prahlad et al. Aug 2013 B2
8504517 Agrawal Aug 2013 B2
8572038 Erofeev Oct 2013 B2
8589347 Erofeev Nov 2013 B2
8655850 Ngo et al. Feb 2014 B2
8656218 Erofeev Feb 2014 B2
8666942 Ngo Mar 2014 B2
8725694 Kottomtharayil May 2014 B2
8725698 Prahlad et al. May 2014 B2
8726242 Ngo May 2014 B2
8745105 Erofeev Jun 2014 B2
8793221 Prahlad et al. Jul 2014 B2
8805818 Zane et al. Aug 2014 B2
8868494 Agrawal Oct 2014 B2
8935210 Kottomtharayil Jan 2015 B2
9002785 Prahlad et al. Apr 2015 B2
9002799 Ngo et al. Apr 2015 B2
9003374 Ngo Apr 2015 B2
9020898 Prahlad et al. Apr 2015 B2
9047357 Ngo Jun 2015 B2
9208210 Erofeev Dec 2015 B2
9298382 Kottomtharayil Mar 2016 B2
20010029512 Oshinsky et al. Oct 2001 A1
20010029517 De Meno et al. Oct 2001 A1
20010032172 Moulinet et al. Oct 2001 A1
20010035866 Finger et al. Nov 2001 A1
20010042222 Kedem et al. Nov 2001 A1
20010044807 Kleiman et al. Nov 2001 A1
20020002557 Straube et al. Jan 2002 A1
20020004883 Nguyen et al. Jan 2002 A1
20020019909 D'Errico Feb 2002 A1
20020023051 Kunzle et al. Feb 2002 A1
20020040376 Yamanaka et al. Apr 2002 A1
20020042869 Tate et al. Apr 2002 A1
20020049626 Mathias et al. Apr 2002 A1
20020049718 Kleiman et al. Apr 2002 A1
20020049738 Epstein Apr 2002 A1
20020049778 Bell et al. Apr 2002 A1
20020062230 Morag et al. May 2002 A1
20020069324 Gerasimov et al. Jun 2002 A1
20020083055 Pachet et al. Jun 2002 A1
20020091712 Martin et al. Jul 2002 A1
20020103848 Giacomini et al. Aug 2002 A1
20020107877 Whiting et al. Aug 2002 A1
20020112134 Ohran et al. Aug 2002 A1
20020120741 Webb et al. Aug 2002 A1
20020124137 Ulrich et al. Sep 2002 A1
20020133511 Hostetter Sep 2002 A1
20020133512 Milillo et al. Sep 2002 A1
20020161753 Inaba et al. Oct 2002 A1
20020174107 Poulin Nov 2002 A1
20020174139 Midgley et al. Nov 2002 A1
20020174416 Bates et al. Nov 2002 A1
20020181395 Foster et al. Dec 2002 A1
20030005119 Mercier et al. Jan 2003 A1
20030018657 Monday Jan 2003 A1
20030023893 Lee et al. Jan 2003 A1
20030028736 Berkowitz et al. Feb 2003 A1
20030033308 Patel et al. Feb 2003 A1
20030061491 Jaskiewicz et al. Mar 2003 A1
20030079018 Lolayekar et al. Apr 2003 A1
20030097296 Putt May 2003 A1
20030126200 Wolff Jul 2003 A1
20030131278 Fujibayashi Jul 2003 A1
20030135783 Martin et al. Jul 2003 A1
20030161338 Ng et al. Aug 2003 A1
20030167380 Green et al. Sep 2003 A1
20030177149 Coombs Sep 2003 A1
20030177321 Watanabe Sep 2003 A1
20030182312 Chen Sep 2003 A1
20030187847 Lubbers et al. Oct 2003 A1
20030225800 Kavuri Dec 2003 A1
20040006572 Hoshino et al. Jan 2004 A1
20040006578 Yu Jan 2004 A1
20040010487 Prahlad et al. Jan 2004 A1
20040015468 Beier et al. Jan 2004 A1
20040039679 Norton et al. Feb 2004 A1
20040078632 Infante et al. Apr 2004 A1
20040098425 Wiss et al. May 2004 A1
20040107199 Dalrymple et al. Jun 2004 A1
20040117438 Considine et al. Jun 2004 A1
20040117572 Welsh et al. Jun 2004 A1
20040133634 Luke et al. Jul 2004 A1
20040139128 Becker et al. Jul 2004 A1
20040158588 Pruet Aug 2004 A1
20040193625 Sutoh Sep 2004 A1
20040193953 Callahan et al. Sep 2004 A1
20040205206 Naik et al. Oct 2004 A1
20040212639 Smoot et al. Oct 2004 A1
20040215724 Smoot et al. Oct 2004 A1
20040225437 Endo et al. Nov 2004 A1
20040230615 Blanco et al. Nov 2004 A1
20040230829 Dogan et al. Nov 2004 A1
20040236958 Teicher et al. Nov 2004 A1
20040249883 Srinivasan et al. Dec 2004 A1
20040250033 Prahlad et al. Dec 2004 A1
20040254919 Giuseppini Dec 2004 A1
20040260678 Verbowski et al. Dec 2004 A1
20040267777 Sugimura et al. Dec 2004 A1
20040267835 Zwilling et al. Dec 2004 A1
20040267836 Armangau et al. Dec 2004 A1
20050015409 Cheng et al. Jan 2005 A1
20050027892 McCabe et al. Feb 2005 A1
20050033800 Kavuri et al. Feb 2005 A1
20050044114 Kottomtharayil et al. Feb 2005 A1
20050055445 Gupta et al. Mar 2005 A1
20050060613 Cheng Mar 2005 A1
20050071389 Gupta et al. Mar 2005 A1
20050071391 Fuerderer et al. Mar 2005 A1
20050080928 Beverly et al. Apr 2005 A1
20050086443 Mizuno et al. Apr 2005 A1
20050108292 Burton et al. May 2005 A1
20050114406 Borthakur et al. May 2005 A1
20050131900 Palliyll et al. Jun 2005 A1
20050138306 Panchbudhe et al. Jun 2005 A1
20050144202 Chen Jun 2005 A1
20050172073 Voigt Aug 2005 A1
20050187982 Sato Aug 2005 A1
20050187992 Prahlad et al. Aug 2005 A1
20050188109 Shiga et al. Aug 2005 A1
20050188254 Urabe et al. Aug 2005 A1
20050193026 Prahlad et al. Sep 2005 A1
20050198083 Saika et al. Sep 2005 A1
20050228875 Monitzer et al. Oct 2005 A1
20050246376 Lu et al. Nov 2005 A1
20050246510 Retnamma et al. Nov 2005 A1
20050254456 Sakai Nov 2005 A1
20050268068 Ignatius et al. Dec 2005 A1
20060005048 Osaki et al. Jan 2006 A1
20060010154 Prahlad et al. Jan 2006 A1
20060010227 Atluri Jan 2006 A1
20060010341 Kodama Jan 2006 A1
20060020616 Hardy et al. Jan 2006 A1
20060034454 Damgaard et al. Feb 2006 A1
20060036901 Yang et al. Feb 2006 A1
20060047805 Byrd et al. Mar 2006 A1
20060047931 Saika Mar 2006 A1
20060092861 Corday et al. May 2006 A1
20060107089 Jansz et al. May 2006 A1
20060120401 Harada et al. Jun 2006 A1
20060129537 Torii et al. Jun 2006 A1
20060136685 Griv et al. Jun 2006 A1
20060155946 Ji Jul 2006 A1
20060171315 Choi et al. Aug 2006 A1
20060174075 Sutoh Aug 2006 A1
20060215564 Breitgand et al. Sep 2006 A1
20060230244 Amarendran et al. Oct 2006 A1
20060242371 Shono et al. Oct 2006 A1
20060242489 Brockway et al. Oct 2006 A1
20070033437 Kawamura Feb 2007 A1
20070043956 El Far et al. Feb 2007 A1
20070050547 Sano Mar 2007 A1
20070055737 Yamashita et al. Mar 2007 A1
20070094467 Yamasaki Apr 2007 A1
20070100867 Celik et al. May 2007 A1
20070112897 Asano et al. May 2007 A1
20070113006 Elliott et al. May 2007 A1
20070124347 Vivian et al. May 2007 A1
20070124348 Claborn et al. May 2007 A1
20070130373 Kalwitz Jun 2007 A1
20070143371 Kottomtharayil Jun 2007 A1
20070143756 Gokhale Jun 2007 A1
20070179990 Zimran et al. Aug 2007 A1
20070183224 Erofeev Aug 2007 A1
20070185852 Erofeev Aug 2007 A1
20070185937 Prahlad et al. Aug 2007 A1
20070185938 Prahlad et al. Aug 2007 A1
20070185939 Prahlad et al. Aug 2007 A1
20070185940 Prahlad et al. Aug 2007 A1
20070186042 Kottomtharayil et al. Aug 2007 A1
20070186068 Agrawal Aug 2007 A1
20070198602 Ngo et al. Aug 2007 A1
20070226438 Erofeev Sep 2007 A1
20070233756 D'Souza et al. Oct 2007 A1
20070244571 Wilson et al. Oct 2007 A1
20070260609 Tulyani Nov 2007 A1
20070276848 Kim Nov 2007 A1
20070288536 Sen et al. Dec 2007 A1
20080016126 Kottomtharayil et al. Jan 2008 A1
20080016293 Saika Jan 2008 A1
20080028009 Ngo Jan 2008 A1
20080059515 Fulton Mar 2008 A1
20080077634 Quakenbush Mar 2008 A1
20080077636 Gupta et al. Mar 2008 A1
20080103916 Camarador et al. May 2008 A1
20080104357 Kim et al. May 2008 A1
20080114815 Sutoh May 2008 A1
20080147878 Kottomtharayil et al. Jun 2008 A1
20080183775 Prahlad et al. Jul 2008 A1
20080205301 Burton et al. Aug 2008 A1
20080208933 Lyon Aug 2008 A1
20080228987 Yagi Sep 2008 A1
20080229037 Bunte et al. Sep 2008 A1
20080243879 Gokhale et al. Oct 2008 A1
20080243914 Prahlad et al. Oct 2008 A1
20080243957 Prahlad et al. Oct 2008 A1
20080243958 Prahlad et al. Oct 2008 A1
20080244177 Crescenti et al. Oct 2008 A1
20080244205 Amano et al. Oct 2008 A1
20080250178 Haustein et al. Oct 2008 A1
20080306954 Hornqvist Dec 2008 A1
20080313497 Hirakawa Dec 2008 A1
20090013014 Kern Jan 2009 A1
20090044046 Yamasaki Feb 2009 A1
20090113056 Tameshige et al. Apr 2009 A1
20090150462 McClanahan et al. Jun 2009 A1
20090182963 Prahlad et al. Jul 2009 A1
20090187944 White et al. Jul 2009 A1
20090300079 Shitomi Dec 2009 A1
20090319534 Gokhale Dec 2009 A1
20090319585 Gokhale Dec 2009 A1
20100005259 Prahlad Jan 2010 A1
20100049753 Prahlad et al. Feb 2010 A1
20100094808 Erofeev Apr 2010 A1
20100100529 Erofeev Apr 2010 A1
20100122053 Prahlad et al. May 2010 A1
20100131461 Prahlad et al. May 2010 A1
20100131467 Prahlad et al. May 2010 A1
20100145909 Ngo Jun 2010 A1
20100153338 Ngo et al. Jun 2010 A1
20100179941 Agrawal et al. Jul 2010 A1
20100205150 Prahlad et al. Aug 2010 A1
20100211571 Prahlad et al. Aug 2010 A1
20110066599 Prahlad et al. Mar 2011 A1
20110238621 Agrawal Sep 2011 A1
20110246416 Prahlad et al. Oct 2011 A1
20110246429 Prahlad et al. Oct 2011 A1
20110246430 Prahlad et al. Oct 2011 A1
20110295804 Erofeev Dec 2011 A1
20110295806 Erofeev Dec 2011 A1
20120011336 Saika Jan 2012 A1
20120030171 Kottomtharayil Feb 2012 A1
20120317074 Ngo Dec 2012 A1
20130006926 Erofeev Jan 2013 A1
20130006938 Prahlad et al. Jan 2013 A1
20130006942 Prahlad et al. Jan 2013 A1
20140067764 Prahlad et al. Mar 2014 A1
20140074777 Agrawal Mar 2014 A1
20140164327 Ngo et al. Jun 2014 A1
20140181022 Ngo Jun 2014 A1
20140181029 Erofeev Jun 2014 A1
20140236900 Kottomtharayil Aug 2014 A1
20140244586 Ngo Aug 2014 A1
20150186061 Kottomtharayil Jul 2015 A1
20150199375 Prahlad et al. Jul 2015 A1
20150205853 Ngo Jul 2015 A1
20150248444 Prahlad et al. Sep 2015 A1
Foreign Referenced Citations (37)
Number Date Country
2006331932 Dec 2006 AU
2632935 Dec 2006 CA
0259912 Mar 1988 EP
0405926 Jan 1991 EP
0 467 546 Jan 1992 EP
0 774 715 May 1997 EP
0809184 Nov 1997 EP
0862304 Sep 1998 EP
0 899 662 Mar 1999 EP
0 981 090 Feb 2000 EP
0981090 Feb 2000 EP
1174795 Jan 2002 EP
1349089 Jan 2003 EP
1349088 Oct 2003 EP
1579331 Sep 2005 EP
1974296 Oct 2008 EP
2256952 Dec 1992 GB
2411030 Aug 2005 GB
05189281 Jul 1993 JP
06274605 Sep 1994 JP
09016463 Jan 1997 JP
11259348 Sep 1999 JP
200347811 Dec 2000 JP
WO 9303549 Feb 1993 WO
WO 9513580 May 1995 WO
WO 9839707 Sep 1998 WO
WO 9912098 Mar 1999 WO
WO 9914692 Mar 1999 WO
WO 9912098 Nov 1999 WO
WO 02095632 Nov 2002 WO
WO 03028183 Apr 2003 WO
WO 2004034197 Apr 2004 WO
WO 2005055093 Jun 2005 WO
WO 2005086032 Sep 2005 WO
WO 2007053314 May 2007 WO
WO 2007075587 Jul 2007 WO
WO 2010068570 Jun 2010 WO
Non-Patent Literature Citations (56)
Entry
Ashton, et al., “Two Decades of policy-based storage management for the IBM mainframe computer”, www.research.ibm.com, 19 pages, published Apr. 10, 2003, printed Jan. 3, 2009—cited in U.S. Appl. No. 12/276,868., www.research.ibm.com, Apr. 10, 2003, pp. 19.
Cabrera et al., “ADSM: A Multi-Platform, Scalable, Backup and Archive Mass Storage System,” Digest of Papers of the Computer Society Conference, IEEE Comp. Soc. Press, vol. Conf. (Mar. 5, 1995), pp. 420-427.
European Examination Report; Application No. 06848901.2, Apr. 1, 2009, pp. 7.
http://en.wikipedia.org/wiki/Naive—Bayes—classifier.
International Search Report and Written Opinion; dated Mar. 25, 2010; International Application No. PCT/US2009/066880; 10 pages.
International Search Report from International Application No. PCT/US2006/048273, dated May 15, 2007.
Microsoft Corporation, “Microsoft Exchange Server: Best Practices for Exchange Database Management,” 1998.
PCT International Search Report and Written Opinion for International Application No. PCT/US07/81681, Mail Date Nov. 13, 2009, 8 pages.
GRAY (#2 of 2, pp. 604-609), Jim; Reuter Andreas, Transaction Processing Concepts and Techniques, Morgan Kaufmann Publisher, USA 1994, pp. 604-609.
International Search Report, PCT/US2004/038324, dated Dec. 28, 2009.
International Search Report, PCT/US2004/038455 dated Jan. 11, 2006.
International Search Report and Written Opinion dated Nov. 13, 2009, PCT/US2007/081681.
Second Examination Report in EU Appl. No. 06 848 901.2-2201 dated Dec. 3, 2010.
U.S. Appl. No. 12/433,238, filed Apr. 30, 2009, Prahlad et al.
Examiner's First Report ; Application No. 2006331932 May 11, 2011 in 2 pages.
Final Office Action for U.S. Appl. No. 12/407,906, mail date Jul. 11, 2011, 38 pages.
Gray, et al. “Transaction processing: concepts and techniques” 1994, Morgan Kaufmann Publishers, USA, pp. 604-609, 646-655.
Harrington, Lisa H., “The RFP Process: How to Hire a Third Party”, Transportation & Distribution, Sep. 1988, vol. 39, Issue 9, in 5 pages.
International Preliminary Report on Patentability, PCT Application No. PCT/US2009/066880, mailed Jun. 23, 2011, in 9 pages.
International Search Report and Written Opinion issued in PCT Application No. PCT/US2011/030396, mailed Jul. 18, 2011, in 20 pages.
International Search Report and Written Opinion issued in PCT Application No. PCT/US2011/38436, mailed Sep. 21, 2011, in 18 pages.
Kashyap, et al., “Professional Services Automation: A knowledge Management approach using LSI and Domain specific Ontologies”, FLAIRS-01 Proceedings, 2001, pp. 300-302.
Notice of Allowance for U.S. Appl. No. 12/581,297, Mail Date May 13, 2011, 23 pages.
Notice of Allowance for U.S. Appl. No. 12/951,773, Mail Date Oct. 4, 2011, 8 pages.
Armstead et al.; “Implementation of a Campus-wide Distributed Mass Storage Service: The Dream vs. Reality,” IEEE, 1995, pp. 190-199.
Arneson, “Mass Storage Archiving in Network Environments” IEEE, 1998, pp. 45-50.
Arneson, David A., Control Data Corporation, Development of Omniserver; Mass Storage Systems, 1990, pp. 88-93.
Cabrera et al., “ADSM: A Multi-Platform, Scalable, Backup and Archive Mass Storage System,” Digest of Papers, Compcon '95, Proceedings of the 40th IEEE Computer Society International Conference, Mar. 5-9, 1995, pp. 420-427, San Francisco, CA.
Eitel, “Backup and Storage Management in Distributed Heterogeneous Environments,” IEEE, 1994, pp. 124-126.
Gray, Jim, Reuter, Andreas: “Transaction Processing: Concepts and Techniques” 1994, Morgan Kaufmann Publisher, USA; pp. 646-655.
Jander, M., “Launching Storage-Area Net,” Data Communications, US, McGraw Hill, NY, vol. 27, No. 4 (Mar. 21, 1998), pp. 64-72.
Jason Gait, “The Optical File Cabinet: A Random-Access File system for Write-Once Optical Disks,” IEEE Computer, vol. 21, No. 6, pp. 11-22 (1988) (see in particular figure 5 in p. 15 and the recitation in claim 5).
Lyon J., Design considerations in replicated database systems for disaster protection, COMPCON 1988, Feb. 29, 1988, pp. 428-430.
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).
The Oracle8 Replication Manual, Part No. A58245-01; Chapters 1-2; Dec. 1, 1997; obtained from website: http://download-west.oracle.com/docs/cd/A64702—01/doc/server.805/a58245/toc.htm on May 20, 2009.
Wiesmann M, Database replication techniques: a three parameter classification, Oct. 16, 2000, pp. 206-215.
Armstead et al., “Implementation of a Campus-Wide Distributed Mass Storage Service: The Dream vs. Reality,” IEEE, 1995, pp. 190-199.
Arneson, “Development of Omniserver; Mass Storage Systems,” Control Data Corporation, 1990, pp. 88-93.
Calvert, Andrew, “SQL Server 2005 Snapshots”, published Apr. 3, 2006, http:/www.simple-talk.com/contnet/print.aspx?article=137, 6 pages.
Veritas Software Corporation, “Veritas Volume Manager 3.2, Administrator's Guide,” Aug. 2001, 360 pages.
Final Office Action for Japanese Application No. 2003531581, Mail Date Mar. 24, 2009, 6 pages.
First Office Action for Japanese Application No. 2003531581, Mail Date Jul. 8, 2008, 8 pages.
Canadian Office Action dated Sep. 24, 2012, Application No. 2,632,935, 2 pages.
Canadian Office Action dated Dec. 29, 2010, Application No. CA2546304.
Examiner's Report for Australian Application No. 2003279847, Dated Dec. 9, 2008, 4 pages.
First Office Action in Canadian application No. 2,632,935 dated Feb. 16, 2012, 5 pages.
International Preliminary Report on Patentability and Written Opinion in PCT/US2011/030396 mailed Oct. 2, 2012.
International Search Report dated Dec. 28, 2009, PCT/US204/038324.
IBM, “Intelligent Selection of Logs Required During Recovery Processing”, ip.com, Sep. 16, 2002, 4 pages.
IBM, “Near Zero Impact Backup and Data Replication Appliance”, ip.com, Oct. 18, 2004, 5 pages.
Park, et al., “An Efficient Logging Scheme for Recoverable Distributed Shared Memory Systems”, IEEE, 1997, 9 pages.
Exam Report in Australian Application No. 2009324800 dated Jun. 17, 2013.
U.S. Appl. No. 14/038,540, filed Sep. 26, 2013, Erofeev.
U.S. Appl. No. 14/592,770, filed Jan. 8, 2015, Kottomtharayil.
U.S. Appl. No. 14/645,982, filed Mar. 12, 2015, Prahlad, et al.
U.S. Appl. No. 14/668,752, filed Mar. 12, 2015, Prahlad, et al.
Related Publications (1)
Number Date Country
20100179941 A1 Jul 2010 US
Provisional Applications (1)
Number Date Country
61121438 Dec 2008 US