Setting up a file server may be done according to policies of a client and may include specifying a MAC (media access control) address, an IP (Internet Protocol) address and a LAN (local area network) configuration. Changes to hardware, such as for an upgrade, can be problematic and involve changes to the MAC address, as well as various routing rules that have been set up and that reference MAC addresses. These disruptions can affect file servers using various types of memory. Solid-state memory, such as flash, is currently in use in solid-state drives (SSD) to augment or replace conventional hard disk drives (HDD), writable CD (compact disk) or writable DVD (digital versatile disk) drives, collectively known as spinning media, and tape drives, for storage of large amounts of data. Flash and other solid-state memories have characteristics that differ from spinning media. Yet, many solid-state drives are designed to conform to hard disk drive standards for compatibility reasons, which makes it difficult to provide enhanced features or take advantage of unique aspects of flash and other solid-state memory.
It is within this context that the embodiments arise.
In some embodiments, a method for preserving a media access control (MAC) address of a virtual server is provided. The method includes assigning a physical computing resource to a virtual server, assigning a physical storage memory resource to the virtual server, and assigning a physical network resource to the virtual server. The method includes assigning a virtual MAC address to the virtual server, the virtual MAC address to remain with the virtual server despite reassignment of one or more of the physical computing resource, the physical storage memory resource or the physical network resource, wherein at least one method operation is performed by a processor.
Other aspects and advantages of the embodiments will become apparent from the following detailed description taken in conjunction with the accompanying drawings which illustrate, by way of example, the principles of the described embodiments.
The described embodiments and the advantages thereof may best be understood by reference to the following description taken in conjunction with the accompanying drawings. These drawings in no way limit any changes in form and detail that may be made to the described embodiments by one skilled in the art without departing from the spirit and scope of the described embodiments.
The embodiments below describe a storage cluster that stores user data, such as user data originating from one or more user or client systems or other sources external to the storage cluster. The storage cluster distributes user data across storage nodes housed within a chassis, using erasure coding and redundant copies of metadata. Erasure coding refers to a method of data protection in which data is broken into fragments, expanded and encoded with redundant data pieces and stored across a set of different locations, such as disks, storage nodes or geographic locations. Flash memory is one type of solid-state memory that may be integrated with the embodiments, although the embodiments may be extended to other types of solid-state memory or other storage medium, including non-solid state memory. Control of storage locations and workloads are distributed across the storage locations in a clustered peer-to-peer system. Tasks such as mediating communications between the various storage nodes, detecting when a storage node has become unavailable, and balancing I/Os (inputs and outputs) across the various storage nodes, are all handled on a distributed basis. Data is laid out or distributed across multiple storage nodes in data fragments or stripes that support data recovery in some embodiments. Ownership of data can be reassigned within a cluster, independent of input and output patterns. This architecture described in more detail below allows a storage node in the cluster to fail, with the system remaining operational, since the data can be reconstructed from other storage nodes and thus remain available for input and output operations. In various embodiments, a storage node may be referred to as a cluster node, a blade, or a server.
The storage cluster is contained within a chassis, i.e., an enclosure housing one or more storage nodes. A mechanism to provide power to each storage node, such as a power distribution bus, and a communication mechanism, such as a communication bus that enables communication between the storage nodes are included within the chassis. The storage cluster can run as an independent system in one location according to some embodiments. In one embodiment, a chassis contains at least two instances of both the power distribution and the communication bus which may be enabled or disabled independently. The internal communication bus may be an Ethernet bus, however, other technologies such as Peripheral Component Interconnect (PCI) Express, InfiniBand, and others, are equally suitable. The chassis provides a port for an external communication bus for enabling communication between multiple chassis, directly or through a switch, and with client systems. The external communication may use a technology such as Ethernet, InfiniBand, Fibre Channel, etc. In some embodiments, the external communication bus uses different communication bus technologies for inter-chassis and client communication. If a switch is deployed within or between chassis, the switch may act as a translation between multiple protocols or technologies. When multiple chassis are connected to define a storage cluster, the storage cluster may be accessed by a client using either proprietary interfaces or standard interfaces such as network file system (NFS), common internet file system (CIFS), small computer system interface (SCSI) or hypertext transfer protocol (HTTP). Translation from the client protocol may occur at the switch, chassis external communication bus or within each storage node.
Each storage node may be one or more storage servers and each storage server is connected to one or more non-volatile solid state memory units, which may be referred to as storage units. One embodiment includes a single storage server in each storage node and between one to eight non-volatile solid state memory units, however this one example is not meant to be limiting. The storage server may include a processor, dynamic random access memory (DRAM) and interfaces for the internal communication bus and power distribution for each of the power buses. Inside the storage node, the interfaces and storage unit share a communication bus, e.g., PCI Express, in some embodiments. The non-volatile solid state memory units may directly access the internal communication bus interface through a storage node communication bus, or request the storage node to access the bus interface. The non-volatile solid state memory unit contains an embedded central processing unit (CPU), solid state storage controller, and a quantity of solid state mass storage, e.g., between 2-32 terabytes (TB) in some embodiments. An embedded volatile storage medium, such as DRAM, and an energy reserve apparatus are included in the non-volatile solid state memory unit. In some embodiments, the energy reserve apparatus is a capacitor, super-capacitor, or battery that enables transferring a subset of DRAM contents to a stable storage medium in the case of power loss. In some embodiments, the non-volatile solid state memory unit is constructed with a storage class memory, such as phase change or magnetoresistive random access memory (MRAM) that substitutes for DRAM and enables a reduced power hold-up apparatus.
One of many features of the storage cluster, storage nodes and non-volatile solid-state storages disclosed herein is the ability to create virtual file servers with preserved MAC (media access control) addresses. By assigning virtual MAC addresses to virtual file servers, a computing and storage system or cluster can create Internet Protocol (IP) addresses, MAC addresses and VLAN (virtual local area network) configurations that remain permanent or persistent while hardware underneath can change.
Each storage node 150 can have multiple components. In the embodiment shown here, the storage node 150 includes a printed circuit board 158 populated by a CPU 156, i.e., processor, a memory 154 coupled to the CPU 156, and a non-volatile solid state storage 152 coupled to the CPU 156, although other mountings and/or components could be used in further embodiments. The memory 154 has instructions which are executed by the CPU 156 and/or data operated on by the CPU 156. As further explained below, the non-volatile solid state storage 152 includes flash or, in further embodiments, other types of solid-state memory.
Storage cluster 160 is scalable, meaning that storage capacity with non-uniform storage sizes is readily added, as described above. One or more storage nodes 150 can be plugged into or removed from each chassis and the storage cluster self-configures in some embodiments. Plug-in storage nodes 150, whether installed in a chassis as delivered or later added, can have different sizes. For example, in one embodiment a storage node 150 can have any multiple of 4 TB, e.g., 8 TB, 12 TB, 16 TB, 32 TB, etc. In further embodiments, a storage node 150 could have any multiple of other storage amounts or capacities. Storage capacity of each storage node 150 is broadcast, and influences decisions of how to stripe the data. For maximum storage efficiency, an embodiment can self-configure as wide as possible in the stripe, subject to a predetermined requirement of continued operation with loss of up to one, or up to two, non-volatile solid state storage units 152 or storage nodes 150 within the chassis.
Every piece of data, and every piece of metadata, has redundancy in the system in some embodiments. In addition, every piece of data and every piece of metadata has an owner, which may be referred to as an authority. If that authority is unreachable, for example through failure of a storage node, there is a plan of succession for how to find that data or that metadata. In various embodiments, there are redundant copies of authorities 168. Authorities 168 have a relationship to storage nodes 150 and non-volatile solid state storage 152 in some embodiments. Each authority 168, covering a range of data segment numbers or other identifiers of the data, may be assigned to a specific non-volatile solid state storage 152. In some embodiments the authorities 168 for all of such ranges are distributed over the non-volatile solid state storages 152 of a storage cluster. Each storage node 150 has a network port that provides access to the non-volatile solid state storage(s) 152 of that storage node 150. Data can be stored in a segment, which is associated with a segment number and that segment number is an indirection for a configuration of a RAID (redundant array of independent disks) stripe in some embodiments. The assignment and use of the authorities 168 thus establishes an indirection to data. Indirection may be referred to as the ability to reference data indirectly, in this case via an authority 168, in accordance with some embodiments. A segment identifies a set of non-volatile solid state storage 152 and a local identifier into the set of non-volatile solid state storage 152 that may contain data. In some embodiments, the local identifier is an offset into the device and may be reused sequentially by multiple segments. In other embodiments the local identifier is unique for a specific segment and never reused. The offsets in the non-volatile solid state storage 152 are applied to locating data for writing to or reading from the non-volatile solid state storage 152 (in the form of a RAID stripe). Data is striped across multiple units of non-volatile solid state storage 152, which may include or be different from the non-volatile solid state storage 152 having the authority 168 for a particular data segment.
If there is a change in where a particular segment of data is located, e.g., during a data move or a data reconstruction, the authority 168 for that data segment should be consulted, at that non-volatile solid state storage 152 or storage node 150 having that authority 168. In order to locate a particular piece of data, embodiments calculate a hash value for a data segment or apply an inode number or a data segment number. The output of this operation points to a non-volatile solid state storage 152 having the authority 168 for that particular piece of data. In some embodiments there are two stages to this operation. The first stage maps an entity identifier (ID), e.g., a segment number, inode number, or directory number to an authority identifier. This mapping may include a calculation such as a hash or a bit mask. The second stage is mapping the authority identifier to a particular non-volatile solid state storage 152, which may be done through an explicit mapping. The operation is repeatable, so that when the calculation is performed, the result of the calculation repeatably and reliably points to a particular non-volatile solid state storage 152 having that authority 168. The operation may include the set of reachable storage nodes as input. If the set of reachable non-volatile solid state storage units changes the optimal set changes. In some embodiments, the persisted value is the current assignment (which is always true) and the calculated value is the target assignment the cluster will attempt to reconfigure towards. This calculation may be used to determine the optimal non-volatile solid state storage 152 for an authority in the presence of a set of non-volatile solid state storage 152 that are reachable and constitute the same cluster. The calculation also determines an ordered set of peer non-volatile solid state storage 152 that will also record the authority to non-volatile solid state storage mapping so that the authority may be determined even if the assigned non-volatile solid state storage is unreachable. A duplicate or substitute authority 168 may be consulted if a specific authority 168 is unavailable in some embodiments.
Two of the many tasks of the CPU 156 on a storage node 150 are to break up write data, and reassemble read data. When the system has determined that data is to be written, the authority 168 for that data is located as above. When the segment ID for data is already determined the request to write is forwarded to the non-volatile solid state storage 152 currently determined to be the host of the authority 168 determined from the segment. The host CPU 156 of the storage node 150, on which the non-volatile solid state storage 152 and corresponding authority 168 reside, then breaks up or shards the data and transmits the data out to various non-volatile solid state storage 152. The transmitted data is written as a data stripe in accordance with an erasure coding scheme. In some embodiments, data is requested to be pulled, and in other embodiments, data is pushed. In reverse, when data is read, the authority 168 for the segment ID containing the data is located as described above. The host CPU 156 of the storage node 150 on which the non-volatile solid state storage 152 and corresponding authority 168 reside requests the data from the non-volatile solid state storage and corresponding storage nodes pointed to by the authority. In some embodiments the data is read from flash storage as a data stripe. The host CPU 156 of storage node 150 then reassembles the read data, correcting any errors (if present) according to the appropriate erasure coding scheme, and forwards the reassembled data to the network. In further embodiments, some or all of these tasks can be handled in the non-volatile solid state storage 152. In some embodiments, the segment host requests the data be sent to storage node 150 by requesting pages from storage and then sending the data to the storage node making the original request.
In some systems, for example in UNIX-style file systems, data is handled with an index node or inode, which specifies a data structure that represents an object in a file system. The object could be a file or a directory, for example. Metadata may accompany the object, as attributes such as permission data and a creation timestamp, among other attributes. A segment number could be assigned to all or a portion of such an object in a file system. In other systems, data segments are handled with a segment number assigned elsewhere. For purposes of discussion, the unit of distribution is an entity, and an entity can be a file, a directory or a segment. That is, entities are units of data or metadata stored by a storage system. Entities are grouped into sets called authorities. Each authority has an authority owner, which is a storage node that has the exclusive right to update the entities in the authority. In other words, a storage node contains the authority, and that the authority, in turn, contains entities.
A segment is a logical container of data in accordance with some embodiments. A segment is an address space between medium address space and physical flash locations, i.e., the data segment number, are in this address space. Segments may also contain metadata, which enable data redundancy to be restored (rewritten to different flash locations or devices) without the involvement of higher level software. In one embodiment, an internal format of a segment contains client data and medium mappings to determine the position of that data. Each data segment is protected, e.g., from memory and other failures, by breaking the segment into a number of data and parity shards, where applicable. The data and parity shards are distributed, i.e., striped, across non-volatile solid state storage 152 coupled to the host CPUs 156 in accordance with an erasure coding scheme. Usage of the term segments refers to the container and its place in the address space of segments in some embodiments. Usage of the term stripe refers to the same set of shards as a segment and includes how the shards are distributed along with redundancy or parity information in accordance with some embodiments.
A series of address-space transformations takes place across an entire storage system. At the top is the directory entries (file names) which link to an inode. Inodes point into medium address space, where data is logically stored. Medium addresses may be mapped through a series of indirect mediums to spread the load of large files, or implement data services like deduplication or snapshots. Medium addresses may be mapped through a series of indirect mediums to spread the load of large files, or implement data services like deduplication or snapshots. Segment addresses are then translated into physical flash locations. Physical flash locations have an address range bounded by the amount of flash in the system in accordance with some embodiments. Medium addresses and segment addresses are logical containers, and in some embodiments use a 128 bit or larger identifier so as to be practically infinite, with a likelihood of reuse calculated as longer than the expected life of the system. Addresses from logical containers are allocated in a hierarchical fashion in some embodiments. Initially, each non-volatile solid state storage 152 may be assigned a range of address space. Within this assigned range, the non-volatile solid state storage 152 is able to allocate addresses without synchronization with other non-volatile solid state storage 152.
Data and metadata is stored by a set of underlying storage layouts that are optimized for varying workload patterns and storage devices. These layouts incorporate multiple redundancy schemes, compression formats and index algorithms. Some of these layouts store information about authorities and authority masters, while others store file metadata and file data. The redundancy schemes include error correction codes that tolerate corrupted bits within a single storage device (such as a NAND flash chip), erasure codes that tolerate the failure of multiple storage nodes, and replication schemes that tolerate data center or regional failures. In some embodiments, low density parity check (LDPC) code is used within a single storage unit. Reed-Solomon encoding is used within a storage cluster, and mirroring is used within a storage grid in some embodiments. Metadata may be stored using an ordered log structured index (such as a Log Structured Merge Tree), and large data may not be stored in a log structured layout.
In order to maintain consistency across multiple copies of an entity, the storage nodes agree implicitly on two things through calculations: (1) the authority that contains the entity, and (2) the storage node that contains the authority. The assignment of entities to authorities can be done by pseudorandomly assigning entities to authorities, by splitting entities into ranges based upon an externally produced key, or by placing a single entity into each authority. Examples of pseudorandom schemes are linear hashing and the Replication Under Scalable Hashing (RUSH) family of hashes, including Controlled Replication Under Scalable Hashing (CRUSH). In some embodiments, pseudo-random assignment is utilized only for assigning authorities to nodes because the set of nodes can change. The set of authorities cannot change so any subjective function may be applied in these embodiments. Some placement schemes automatically place authorities on storage nodes, while other placement schemes rely on an explicit mapping of authorities to storage nodes. In some embodiments, a pseudorandom scheme is utilized to map from each authority to a set of candidate authority owners. A pseudorandom data distribution function related to CRUSH may assign authorities to storage nodes and create a list of where the authorities are assigned. Each storage node has a copy of the pseudorandom data distribution function, and can arrive at the same calculation for distributing, and later finding or locating an authority. Each of the pseudorandom schemes requires the reachable set of storage nodes as input in some embodiments in order to conclude the same target nodes. Once an entity has been placed in an authority, the entity may be stored on physical devices so that no expected failure will lead to unexpected data loss. In some embodiments, rebalancing algorithms attempt to store the copies of all entities within an authority in the same layout and on the same set of machines.
Examples of expected failures include device failures, stolen machines, datacenter fires, and regional disasters, such as nuclear or geological events. Different failures lead to different levels of acceptable data loss. In some embodiments, a stolen storage node impacts neither the security nor the reliability of the system, while depending on system configuration, a regional event could lead to no loss of data, a few seconds or minutes of lost updates, or even complete data loss.
In the embodiments, the placement of data for storage redundancy is independent of the placement of authorities for data consistency. In some embodiments, storage nodes that contain authorities do not contain any persistent storage. Instead, the storage nodes are connected to non-volatile solid state storage units that do not contain authorities. The communications interconnect between storage nodes and non-volatile solid state storage units consists of multiple communication technologies and has non-uniform performance and fault tolerance characteristics. In some embodiments, as mentioned above, non-volatile solid state storage units are connected to storage nodes via PCI express, storage nodes are connected together within a single chassis using an Ethernet backplane, and chassis are connected together to form a storage cluster. Storage clusters are connected to clients using Ethernet or fiber channel in some embodiments. If multiple storage clusters are configured into a storage grid, the multiple storage clusters are connected using the Internet or other long-distance networking links, such as a “metro scale” link or private link that does not traverse the internet.
Authority owners have the exclusive right to modify entities, to migrate entities from one non-volatile solid state storage unit to another non-volatile solid state storage unit, and to add and remove copies of entities. This allows for maintaining the redundancy of the underlying data. When an authority owner fails, is going to be decommissioned, or is overloaded, the authority is transferred to a new storage node. Transient failures make it non-trivial to ensure that all non-faulty machines agree upon the new authority location. The ambiguity that arises due to transient failures can be achieved automatically by a consensus protocol such as Paxos, hot-warm failover schemes, via manual intervention by a remote system administrator, or by a local hardware administrator (such as by physically removing the failed machine from the cluster, or pressing a button on the failed machine). In some embodiments, a consensus protocol is used, and failover is automatic. If too many failures or replication events occur in too short a time period, the system goes into a self-preservation mode and halts replication and data movement activities until an administrator intervenes in accordance with some embodiments.
As authorities are transferred between storage nodes and authority owners update entities in their authorities, the system transfers messages between the storage nodes and non-volatile solid state storage units. With regard to persistent messages, messages that have different purposes are of different types. Depending on the type of the message, the system maintains different ordering and durability guarantees. As the persistent messages are being processed, the messages are temporarily stored in multiple durable and non-durable storage hardware technologies. In some embodiments, messages are stored in RAM, NVRAM and on NAND flash devices, and a variety of protocols are used in order to make efficient use of each storage medium. Latency-sensitive client requests may be persisted in replicated NVRAM, and then later NAND, while background rebalancing operations are persisted directly to NAND.
Persistent messages are persistently stored prior to being replicated. This allows the system to continue to serve client requests despite failures and component replacement. Although many hardware components contain unique identifiers that are visible to system administrators, manufacturer, hardware supply chain and ongoing monitoring quality control infrastructure, applications running on top of the infrastructure address virtualize addresses. These virtualized addresses do not change over the lifetime of the storage system, regardless of component failures and replacements. This allows each component of the storage system to be replaced over time without reconfiguration or disruptions of client request processing.
In some embodiments, the virtualized addresses are stored with sufficient redundancy. A continuous monitoring system correlates hardware and software status and the hardware identifiers. This allows detection and prediction of failures due to faulty components and manufacturing details. The monitoring system also enables the proactive transfer of authorities and entities away from impacted devices before failure occurs by removing the component from the critical path in some embodiments.
In addition to component redundancy in the communication channel, storage cluster 160 is configured to allow for the loss of one or more storage nodes 150. In some embodiments this cluster redundancy level may be one for relatively small storage clusters 160 (less than 8 storage nodes 150) and two for relatively larger storage clusters 160 (8 or more storage nodes 150) although any number would be suitable for the cluster redundancy level. In some embodiments, where more storage nodes 150 than the redundancy level are lost, the storage cluster 160 cannot guarantee availability of data or integrity of future updates. As mentioned above, data redundancy is implemented via segments. A segment is formed by selecting equal sized shards from a subset of the non-volatile solid state storage 152, each within a different storage node 150. Shards are reserved to establish the redundancy level, e.g., one or two, and then a remainder constitutes the data (the data shards). The shards are encoded using an ECC scheme such as parity or Reed-Soloman (RAID 6), so that any subset of the shards equal in count to the data shards may be used to reconstruct the complete data. The storage cluster redundancy represents a minimum level of redundancy and it may be exceeded for any individual data element. Segments are stored as a set of non-volatile solid state storage units, roles (data position or parity) and allocation unit local to each non-volatile solid state storage unit. The allocation units may be a physical address or an indirection determined within the non-volatile solid state storage 152. Each shard may be portioned into pages and each page into code words. In some embodiments, the pages are between about 4 kilobytes (kB) and 64 kB, e.g., 16 kB, while the code words are between about 512 bytes to 4 kB, e.g., 1 kB. These sizes are one example and not meant to be limiting as any suitable size for the code words and the pages may be utilized. The code words contain local error correction and a checksum to verify the error correction was successful. This checksum is “salted” with the logical address of the contents meaning that a failure to match the checksum may occur if the data is uncorrectable or misplaced. In some embodiments, when a code word fails a checksum it is converted to an “erasure” for purpose of the error correction algorithm so that the code word may be rebuilt.
Still referring to
A virtual server 184 of
The processing controller 110 can assign physical computing resources to the virtual server 17, while networking controller 112 can assign network resources to the virtual server 184, and assign a virtual MAC address to the virtual server 184. The storage controller 114 assigns storage memory resources to the virtual server 184. For example, an IP address and a MAC address for a virtual server 184 could be assigned to one or more storage nodes 150 having associated MAC addresses of physical hardware. A network access to a file stored on the virtual server 184 is via the IP address corresponding to the virtual MAC address in some embodiments. A storage node 150 may be swapped out, or the virtual server 184 may be reconfigured for a differing amount of resources. In these instances one or more differing storage nodes 150 with associated MAC addresses of physical hardware could be assigned to the virtual server 184, which would retain the IP address and the MAC address originally assigned to the virtual server 184. A virtual server 184 can include an assignment of physical resources for a virtual Ethernet adapter 182, which could be associated with the virtual MAC address assigned to the virtual server 184 even though the actual hardware could include an actual (physical) Ethernet adapter with a differing MAC address. Alternatively, a virtual Ethernet adapter 182 could be configured from other hardware such as a programmable logic device (PLD), or firmware. The MAC address is preserved when storage nodes 150 and/or non-volatile solid-state storages 152 self-configure or self-reconfigure, and when physical changes are made to a computing and storage system in the above embodiments. In other words, changes to the physical computing resources, the network resources and/or the storage memory resources assigned to a virtual server 184 leave the virtual MAC address of the virtual server 184 unchanged. The virtual MAC address is thus a virtual entity that hides the underlying physical structure in a virtualized environment, which can change during operation.
In various scenarios, each of the processing controller 110, the networking controller 112 and the storage controller 114 could be dedicated physical servers or portions of one or more physical servers, or could be allocated as virtual servers 184 or other virtual resources from physical computing resources. For example, one, two or all three of these controllers 110, 112, 114 could be allocated as one or more virtual servers 184 using the resources of a storage cluster 160. Or, the roles of the processing controller 110, the networking controller 112 in the storage controller 114 could be flexibly allocated among the storage nodes 150 in a storage cluster 160, so that the responsibilities for some of the virtual servers 184 are performed by some of the storage nodes 150, and the responsibilities for others of the virtual servers 184 are performed by others of the storage nodes 150, and these may change during operation. The same storage cluster 160, or another storage cluster 160, could allocate resources for one or more virtual servers 184, as shown in
With reference to
In decision action 608, it is determined if the virtual server is previously assigned. If the answer is no, the virtual server is not previously assigned and may be a new virtual server, flow continues to action 610. If the answer is yes, the virtual server is previously assigned, flow continues to action 614. In action 610, a new virtual MAC address is assigned to the virtual server. This could include tracking the correspondence between the virtual MAC address and one or more physical MAC addresses of hardware resources assigned to the virtual server. In action 612, a new IP address is assigned to the virtual server and may include tracking the correspondence between the IP address and the hardware resources assigned to the virtual server, or tracking the correspondence between the IP address and one or more physical MAC addresses of hardware resources assigned to the virtual server. Flow continues to decision action 618.
Flow arrives at action 614 if the determination from the decision action 608 is that the virtual server is previously assigned. In action 614, the same virtual MAC address is assigned to the virtual server. The same IP address is assigned to the virtual server, in action 616. Flow continues to decision action 618. In decision action 618, it is determined if there are changes to the physical resources. If the answer is no, there are no changes to the physical resources, the flow continues to decision action 620. If the answer is yes, there are changes to the physical resources, flow continues to action 602, in order to assign physical computing resources, physical storage memory resources, and physical network resources to the virtual server. In turn, the virtual server will have the same virtual MAC address and the same IP address reassigned to it. In decision action 620, it is determined if there are changes to the configuration of the virtual server. If the answer is no, there are no changes to the configuration of the virtual sever, the flow continues to decision action 622. If the answer is yes, there are changes to the configuration of the virtual sever, flow continues to action 602, in order to assign physical computing resources, physical storage memory resources, and physical network resources to the virtual server, which maintains the same virtual MAC address and the same IP address. In decision action 622, it is determined if an additional virtual server is created. If the answer is no, there is no additional virtual server created, the flow proceeds back to decision action 618, and repeats a loop until or unless there is a change to physical resources, a change to a configuration of a virtual server, or the creation of an additional virtual server. If the answer in decision action 622 is yes, there is an additional virtual server created, the flow branches back to action 602, in order to assign physical resources to the new virtual server, and repeats as described above. In variations to the method, the decision actions 618, 620, 622 could be performed in various differing orders or in parallel, with exits to the decision actions 618, 620, 622 branching the flow accordingly. Assigning physical resources to a new virtual server might affect the assignment of physical resources to the virtual server previously configured. However, the previously created virtual server retains the previously assigned MAC address, and the new virtual server would get a new, differing MAC address which is retained over time.
It should be appreciated that the methods described herein may be performed with a digital processing system, such as a conventional, general-purpose computer system. Special purpose computers, which are designed or programmed to perform only one function may be used in the alternative.
Display 711 is in communication with CPU 701, memory 703, and mass storage device 707, through bus 705. Display 711 is configured to display any visualization tools or reports associated with the system described herein. Input/output device 709 is coupled to bus 705 in order to communicate information in command selections to CPU 701. It should be appreciated that data to and from external devices may be communicated through the input/output device 709. CPU 701 can be defined to execute the functionality described herein to enable the functionality described with reference to
Detailed illustrative embodiments are disclosed herein. However, specific functional details disclosed herein are merely representative for purposes of describing embodiments. Embodiments may, however, be embodied in many alternate forms and should not be construed as limited to only the embodiments set forth herein.
It should be understood that although the terms first, second, etc. may be used herein to describe various steps or calculations, these steps or calculations should not be limited by these terms. These terms are only used to distinguish one step or calculation from another. For example, a first calculation could be termed a second calculation, and, similarly, a second step could be termed a first step, without departing from the scope of this disclosure. As used herein, the term “and/or” and the “/” symbol includes any and all combinations of one or more of the associated listed items.
As used herein, the singular forms “a”, “an” and “the” are intended to include the plural forms as well, unless the context clearly indicates otherwise. It will be further understood that the terms “comprises”, “comprising”, “includes”, and/or “including”, when used herein, specify the presence of stated features, integers, steps, operations, elements, and/or components, but do not preclude the presence or addition of one or more other features, integers, steps, operations, elements, components, and/or groups thereof. Therefore, the terminology used herein is for the purpose of describing particular embodiments only and is not intended to be limiting.
It should also be noted that in some alternative implementations, the functions/acts noted may occur out of the order noted in the figures. For example, two figures shown in succession may in fact be executed substantially concurrently or may sometimes be executed in the reverse order, depending upon the functionality/acts involved.
With the above embodiments in mind, it should be understood that the embodiments might employ various computer-implemented operations involving data stored in computer systems. These operations are those requiring physical manipulation of physical quantities. Usually, though not necessarily, these quantities take the form of electrical or magnetic signals capable of being stored, transferred, combined, compared, and otherwise manipulated. Further, the manipulations performed are often referred to in terms, such as producing, identifying, determining, or comparing. Any of the operations described herein that form part of the embodiments are useful machine operations. The embodiments also relate to a device or an apparatus for performing these operations. The apparatus can be specially constructed for the required purpose, or the apparatus can be a general-purpose computer selectively activated or configured by a computer program stored in the computer. In particular, various general-purpose machines can be used with computer programs written in accordance with the teachings herein, or it may be more convenient to construct a more specialized apparatus to perform the required operations.
A module, an application, a layer, an agent or other method-operable entity could be implemented as hardware, firmware, or a processor executing software, or combinations thereof. It should be appreciated that, where a software-based embodiment is disclosed herein, the software can be embodied in a physical machine such as a controller. For example, a controller could include a first module and a second module. A controller could be configured to perform various actions, e.g., of a method, an application, a layer or an agent.
The embodiments can also be embodied as computer readable code on a non-transitory computer readable medium. The computer readable medium is any data storage device that can store data, which can be thereafter read by a computer system. Examples of the computer readable medium include hard drives, network attached storage (NAS), read-only memory, random-access memory, CD-ROMs, CD-Rs, CD-RWs, magnetic tapes, and other optical and non-optical data storage devices. The computer readable medium can also be distributed over a network coupled computer system so that the computer readable code is stored and executed in a distributed fashion. Embodiments described herein may be practiced with various computer system configurations including hand-held devices, tablets, microprocessor systems, microprocessor-based or programmable consumer electronics, minicomputers, mainframe computers and the like. The embodiments can also be practiced in distributed computing environments where tasks are performed by remote processing devices that are linked through a wire-based or wireless network.
Although the method operations were described in a specific order, it should be understood that other operations may be performed in between described operations, described operations may be adjusted so that they occur at slightly different times or the described operations may be distributed in a system which allows the occurrence of the processing operations at various intervals associated with the processing.
In various embodiments, one or more portions of the methods and mechanisms described herein may form part of a cloud-computing environment. In such embodiments, resources may be provided over the Internet as services according to one or more various models. Such models may include Infrastructure as a Service (IaaS), Platform as a Service (PaaS), and Software as a Service (SaaS). In IaaS, computer infrastructure is delivered as a service. In such a case, the computing equipment is generally owned and operated by the service provider. In the PaaS model, software tools and underlying equipment used by developers to develop software solutions may be provided as a service and hosted by the service provider. SaaS typically includes a service provider licensing software as a service on demand. The service provider may host the software, or may deploy the software to a customer for a given period of time. Numerous combinations of the above models are possible and are contemplated.
Various units, circuits, or other components may be described or claimed as “configured to” perform a task or tasks. In such contexts, the phrase “configured to” is used to connote structure by indicating that the units/circuits/components include structure (e.g., circuitry) that performs the task or tasks during operation. As such, the unit/circuit/component can be said to be configured to perform the task even when the specified unit/circuit/component is not currently operational (e.g., is not on). The units/circuits/components used with the “configured to” language include hardware—for example, circuits, memory storing program instructions executable to implement the operation, etc. Reciting that a unit/circuit/component is “configured to” perform one or more tasks is expressly intended not to invoke 35 U.S.C. 112, sixth paragraph, for that unit/circuit/component. Additionally, “configured to” can include generic structure (e.g., generic circuitry) that is manipulated by software and/or firmware (e.g., an FPGA or a general-purpose processor executing software) to operate in manner that is capable of performing the task(s) at issue. “Configured to” may also include adapting a manufacturing process (e.g., a semiconductor fabrication facility) to fabricate devices (e.g., integrated circuits) that are adapted to implement or perform one or more tasks.
The foregoing description, for the purpose of explanation, has been described with reference to specific embodiments. However, the illustrative discussions above are not intended to be exhaustive or to limit the invention to the precise forms disclosed. Many modifications and variations are possible in view of the above teachings. The embodiments were chosen and described in order to best explain the principles of the embodiments and its practical applications, to thereby enable others skilled in the art to best utilize the embodiments and various modifications as may be suited to the particular use contemplated. Accordingly, the present embodiments are to be considered as illustrative and not restrictive, and the invention is not to be limited to the details given herein, but may be modified within the scope and equivalents of the appended claims.
Number | Name | Date | Kind |
---|---|---|---|
5390327 | Lubbers et al. | Feb 1995 | A |
5450581 | Bergen et al. | Sep 1995 | A |
5479653 | Jones | Dec 1995 | A |
5488731 | Mendelsohn | Jan 1996 | A |
5504858 | Ellis et al. | Apr 1996 | A |
5564113 | Bergen et al. | Oct 1996 | A |
5574882 | Menon et al. | Nov 1996 | A |
5649093 | Hanke et al. | Jul 1997 | A |
5883909 | Dekoning et al. | Mar 1999 | A |
6000010 | Legg | Dec 1999 | A |
6260156 | Garvin et al. | Jul 2001 | B1 |
6269453 | Krantz | Jul 2001 | B1 |
6275898 | DeKoning | Aug 2001 | B1 |
6453428 | Stephenson | Sep 2002 | B1 |
6523087 | Busser | Feb 2003 | B2 |
6535417 | Tsuda | Mar 2003 | B2 |
6643748 | Wieland | Nov 2003 | B1 |
6725392 | Frey et al. | Apr 2004 | B1 |
6763455 | Hall | Jul 2004 | B2 |
6836816 | Kendall | Dec 2004 | B2 |
6985995 | Holland et al. | Jan 2006 | B2 |
7032125 | Holt et al. | Apr 2006 | B2 |
7047358 | Lee et al. | May 2006 | B2 |
7051155 | Talagala et al. | May 2006 | B2 |
7055058 | Lee et al. | May 2006 | B2 |
7065617 | Wang | Jun 2006 | B2 |
7069383 | Yamamoto et al. | Jun 2006 | B2 |
7076606 | Orsley | Jul 2006 | B2 |
7107480 | Moshayedi et al. | Sep 2006 | B1 |
7159150 | Kenchammana-Hosekote et al. | Jan 2007 | B2 |
7162575 | Dalal et al. | Jan 2007 | B2 |
7164608 | Lee | Jan 2007 | B2 |
7188270 | Nanda et al. | Mar 2007 | B1 |
7334156 | Land et al. | Feb 2008 | B2 |
7370220 | Nguyen et al. | May 2008 | B1 |
7386666 | Beauchamp et al. | Jun 2008 | B1 |
7398285 | Kisley | Jul 2008 | B2 |
7424498 | Patterson | Sep 2008 | B1 |
7424592 | Karr | Sep 2008 | B1 |
7444532 | Masuyama et al. | Oct 2008 | B2 |
7480658 | Heinla et al. | Jan 2009 | B2 |
7484056 | Madnani et al. | Jan 2009 | B2 |
7484057 | Madnani et al. | Jan 2009 | B1 |
7484059 | Ofer et al. | Jan 2009 | B1 |
7536506 | Ashmore et al. | May 2009 | B2 |
7558859 | Kasiolas | Jul 2009 | B2 |
7565446 | Talagala et al. | Jul 2009 | B2 |
7613947 | Coatney | Nov 2009 | B1 |
7634617 | Misra | Dec 2009 | B2 |
7634618 | Misra | Dec 2009 | B2 |
7681104 | Sim-Tang et al. | Mar 2010 | B1 |
7681105 | Sim-Tang et al. | Mar 2010 | B1 |
7681109 | Yang et al. | Mar 2010 | B2 |
7730257 | Franklin | Jun 2010 | B2 |
7730258 | Smith | Jun 2010 | B1 |
7730274 | Usgaonkar | Jun 2010 | B1 |
7743276 | Jacobsen et al. | Jun 2010 | B2 |
7752489 | Deenadhayalan et al. | Jul 2010 | B2 |
7757038 | Kitahara | Jul 2010 | B2 |
7757059 | Ofer et al. | Jul 2010 | B1 |
7778960 | Chatterjee et al. | Aug 2010 | B1 |
7783955 | Haratsch et al. | Aug 2010 | B2 |
7814272 | Barrail et al. | Oct 2010 | B2 |
7814273 | Barrail | Oct 2010 | B2 |
7818531 | Barrail | Oct 2010 | B2 |
7827351 | Suetsugu et al. | Nov 2010 | B2 |
7827439 | Matthew et al. | Nov 2010 | B2 |
7831768 | Ananthamurthy et al. | Nov 2010 | B2 |
7856583 | Smith | Dec 2010 | B1 |
7870105 | Arakawa et al. | Jan 2011 | B2 |
7873878 | Belluomini et al. | Jan 2011 | B2 |
7885938 | Greene et al. | Feb 2011 | B1 |
7886111 | Klemm et al. | Feb 2011 | B2 |
7908448 | Chatterjee et al. | Mar 2011 | B1 |
7916538 | Jeon et al. | Mar 2011 | B2 |
7921268 | Jakob | Apr 2011 | B2 |
7930499 | Duchesne | Apr 2011 | B2 |
7941697 | Mathew et al. | May 2011 | B2 |
7958303 | Shuster | Jun 2011 | B2 |
7971129 | Watson | Jun 2011 | B2 |
7984016 | Kisley | Jul 2011 | B2 |
7991822 | Bish et al. | Aug 2011 | B2 |
8006126 | Deenadhayalan et al. | Aug 2011 | B2 |
8010485 | Chatterjee et al. | Aug 2011 | B1 |
8010829 | Chatterjee et al. | Aug 2011 | B1 |
8020047 | Courtney | Sep 2011 | B2 |
8046548 | Chatterjee et al. | Oct 2011 | B1 |
8051361 | Sim-Tang et al. | Nov 2011 | B2 |
8051362 | Li et al. | Nov 2011 | B2 |
8074038 | Lionetti et al. | Dec 2011 | B2 |
8082393 | Galloway et al. | Dec 2011 | B2 |
8086603 | Nasre et al. | Dec 2011 | B2 |
8086634 | Mimatsu | Dec 2011 | B2 |
8086911 | Taylor | Dec 2011 | B1 |
8090837 | Shin et al. | Jan 2012 | B2 |
8108502 | Tabbara et al. | Jan 2012 | B2 |
8117388 | Jernigan, IV | Feb 2012 | B2 |
8117521 | Yang et al. | Feb 2012 | B2 |
8140821 | Raizen et al. | Mar 2012 | B1 |
8145838 | Miller et al. | Mar 2012 | B1 |
8145840 | Koul et al. | Mar 2012 | B2 |
8175012 | Haratsch et al. | May 2012 | B2 |
8176360 | Frost et al. | May 2012 | B2 |
8176405 | Hafner et al. | May 2012 | B2 |
8180855 | Aiello et al. | May 2012 | B2 |
8200922 | McKean et al. | Jun 2012 | B2 |
8209469 | Carpenter et al. | Jun 2012 | B2 |
8225006 | Karamcheti | Jul 2012 | B1 |
8239618 | Kotzur et al. | Aug 2012 | B2 |
8244999 | Chatterjee et al. | Aug 2012 | B1 |
8261016 | Goel | Sep 2012 | B1 |
8271455 | Kesselman | Sep 2012 | B2 |
8285686 | Kesselman | Oct 2012 | B2 |
8305811 | Jeon | Nov 2012 | B2 |
8315999 | Chatley et al. | Nov 2012 | B2 |
8327080 | Der | Dec 2012 | B1 |
8335769 | Kesselman | Dec 2012 | B2 |
8341118 | Drobychev et al. | Dec 2012 | B2 |
8351290 | Huang et al. | Jan 2013 | B1 |
8364920 | Parkison et al. | Jan 2013 | B1 |
8365041 | Chu et al. | Jan 2013 | B2 |
8375146 | Sinclair | Feb 2013 | B2 |
8397016 | Talagala et al. | Mar 2013 | B2 |
8402152 | Duran | Mar 2013 | B2 |
8412880 | Leibowitz et al. | Apr 2013 | B2 |
8423739 | Ash et al. | Apr 2013 | B2 |
8429436 | Filingim et al. | Apr 2013 | B2 |
8452928 | Ofer et al. | May 2013 | B1 |
8473698 | Lionetti et al. | Jun 2013 | B2 |
8473778 | Simitci | Jun 2013 | B2 |
8473815 | Yu et al. | Jun 2013 | B2 |
8479037 | Chatterjee et al. | Jul 2013 | B1 |
8484414 | Sugimoto et al. | Jul 2013 | B2 |
8498967 | Chatterjee et al. | Jul 2013 | B1 |
8522073 | Cohen | Aug 2013 | B2 |
8533408 | Madnani et al. | Sep 2013 | B1 |
8533527 | Daikokuya et al. | Sep 2013 | B2 |
8539177 | Ofer et al. | Sep 2013 | B1 |
8544029 | Bakke et al. | Sep 2013 | B2 |
8549224 | Zeryck et al. | Oct 2013 | B1 |
8583861 | Ofer et al. | Nov 2013 | B1 |
8589625 | Colgrove et al. | Nov 2013 | B2 |
8595455 | Chatterjee et al. | Nov 2013 | B2 |
8615599 | Takefman et al. | Dec 2013 | B1 |
8627136 | Shankar et al. | Jan 2014 | B2 |
8627138 | Clark | Jan 2014 | B1 |
8639669 | Douglis et al. | Jan 2014 | B1 |
8639863 | Kanapathippillai et al. | Jan 2014 | B1 |
8640000 | Cypher | Jan 2014 | B1 |
8650343 | Kanapathippillai et al. | Feb 2014 | B1 |
8660131 | Vermont et al. | Feb 2014 | B2 |
8661218 | Piszczek et al. | Feb 2014 | B1 |
8671072 | Shah et al. | Mar 2014 | B1 |
8689042 | Kanapathippillai et al. | Apr 2014 | B1 |
8700875 | Barron et al. | Apr 2014 | B1 |
8706694 | Chatterjee et al. | Apr 2014 | B2 |
8706914 | Duchesneau | Apr 2014 | B2 |
8706932 | Kanapathippillai et al. | Apr 2014 | B1 |
8712963 | Douglis et al. | Apr 2014 | B1 |
8713405 | Healey et al. | Apr 2014 | B2 |
8719621 | Karmarkar | May 2014 | B1 |
8725730 | Keeton et al. | May 2014 | B2 |
8751859 | Becker-szendy et al. | Jun 2014 | B2 |
8756387 | Frost et al. | Jun 2014 | B2 |
8762793 | Grube et al. | Jun 2014 | B2 |
8838541 | Camble et al. | Jun 2014 | B2 |
8769232 | Suryabudi et al. | Jul 2014 | B2 |
8775858 | Gower et al. | Jul 2014 | B2 |
8775868 | Colgrove et al. | Jul 2014 | B2 |
8788913 | Xin et al. | Jul 2014 | B1 |
8793447 | Usgaonkar et al. | Jul 2014 | B2 |
8799746 | Baker et al. | Aug 2014 | B2 |
8819311 | Liao | Aug 2014 | B2 |
8819383 | Jobanputra et al. | Aug 2014 | B1 |
8824261 | Miller et al. | Sep 2014 | B1 |
8832528 | Thatcher et al. | Sep 2014 | B2 |
8838892 | Li | Sep 2014 | B2 |
8843700 | Salessi et al. | Sep 2014 | B1 |
8850108 | Hayes et al. | Sep 2014 | B1 |
8850288 | Lazier et al. | Sep 2014 | B1 |
8856593 | Eckhardt et al. | Oct 2014 | B2 |
8856619 | Cypher | Oct 2014 | B1 |
8862617 | Kesselman | Oct 2014 | B2 |
8862847 | Feng et al. | Oct 2014 | B2 |
8862928 | Xavier et al. | Oct 2014 | B2 |
8868825 | Hayes | Oct 2014 | B1 |
8874836 | Hayes | Oct 2014 | B1 |
8880793 | Nagineni | Nov 2014 | B2 |
8880825 | Lionetti et al. | Nov 2014 | B2 |
8886778 | Nedved et al. | Nov 2014 | B2 |
8898383 | Yamamoto et al. | Nov 2014 | B2 |
8898388 | Kimmel | Nov 2014 | B1 |
8904231 | Coatney et al. | Dec 2014 | B2 |
8918478 | Ozzie et al. | Dec 2014 | B2 |
8930307 | Colgrove et al. | Jan 2015 | B2 |
8930633 | Amit et al. | Jan 2015 | B2 |
8943357 | Atzmony | Jan 2015 | B2 |
8949502 | McKnight et al. | Feb 2015 | B2 |
8959110 | Smith et al. | Feb 2015 | B2 |
8959388 | Kuang et al. | Feb 2015 | B1 |
8972478 | Storer et al. | Mar 2015 | B1 |
8972779 | Lee et al. | Mar 2015 | B2 |
8977597 | Ganesh et al. | Mar 2015 | B2 |
8996828 | Kalos et al. | Mar 2015 | B2 |
9003144 | Hayes et al. | Apr 2015 | B1 |
9009724 | Gold et al. | Apr 2015 | B2 |
9021053 | Bernbo et al. | Apr 2015 | B2 |
9021215 | Meir et al. | Apr 2015 | B2 |
9025393 | Wu | May 2015 | B2 |
9043372 | Makkar et al. | May 2015 | B2 |
9047214 | Sharon et al. | Jun 2015 | B1 |
9053808 | Sprouse | Jun 2015 | B2 |
9058155 | Cepulis et al. | Jun 2015 | B2 |
9063895 | Madnani et al. | Jun 2015 | B1 |
9063896 | Madnani et al. | Jun 2015 | B1 |
9098211 | Madnani et al. | Aug 2015 | B1 |
9110898 | Chamness et al. | Aug 2015 | B1 |
9110964 | Shilane et al. | Aug 2015 | B1 |
9116819 | Cope et al. | Aug 2015 | B2 |
9117536 | Yoon | Aug 2015 | B2 |
9122401 | Zaltsman et al. | Sep 2015 | B2 |
9123422 | Sharon et al. | Sep 2015 | B2 |
9124300 | Olbrich et al. | Sep 2015 | B2 |
9134908 | Hom et al. | Sep 2015 | B2 |
9153337 | Sutardja | Oct 2015 | B2 |
9158472 | Kesselman et al. | Oct 2015 | B2 |
9159422 | Lee et al. | Oct 2015 | B1 |
9164891 | Karamcheti et al. | Oct 2015 | B2 |
9183136 | Kawamura et al. | Nov 2015 | B2 |
9189650 | Jaye et al. | Nov 2015 | B2 |
9201733 | Verma | Dec 2015 | B2 |
9207876 | Shu et al. | Dec 2015 | B2 |
9229656 | Contreras et al. | Jan 2016 | B1 |
9229810 | He et al. | Jan 2016 | B2 |
9235475 | Shilane et al. | Jan 2016 | B1 |
9244626 | Shah et al. | Jan 2016 | B2 |
9250999 | Barroso | Feb 2016 | B1 |
9251066 | Colgrove et al. | Feb 2016 | B2 |
9268648 | Barash et al. | Feb 2016 | B1 |
9268806 | Kesselman et al. | Feb 2016 | B1 |
9286002 | Karamcheti et al. | Mar 2016 | B1 |
9292214 | Kalos et al. | Mar 2016 | B2 |
9298760 | Li et al. | Mar 2016 | B1 |
9304908 | Karamcheti et al. | Apr 2016 | B1 |
9311969 | Murin | Apr 2016 | B2 |
9311970 | Sharon et al. | Apr 2016 | B2 |
9323663 | Karamcheti et al. | Apr 2016 | B2 |
9323667 | Bennett | Apr 2016 | B2 |
9323681 | Apostolides et al. | Apr 2016 | B2 |
9335942 | Kumar et al. | May 2016 | B2 |
9348538 | Mallaiah et al. | May 2016 | B2 |
9355022 | Ravimohan et al. | May 2016 | B2 |
9384082 | Lee et al. | Jul 2016 | B1 |
9384252 | Akirav et al. | Jul 2016 | B2 |
9389958 | Sundaram et al. | Jul 2016 | B2 |
9390019 | Patterson et al. | Jul 2016 | B2 |
9396202 | Drobychev et al. | Jul 2016 | B1 |
9400828 | Kesselman et al. | Jul 2016 | B2 |
9405478 | Koseki et al. | Aug 2016 | B2 |
9411685 | Lee | Aug 2016 | B2 |
9417960 | Klein | Aug 2016 | B2 |
9417963 | He et al. | Aug 2016 | B2 |
9430250 | Hamid et al. | Aug 2016 | B2 |
9430542 | Akirav et al. | Aug 2016 | B2 |
9432541 | Ishida | Aug 2016 | B2 |
9454434 | Sundaram et al. | Sep 2016 | B2 |
9471579 | Natanzon | Oct 2016 | B1 |
9477554 | Chamness et al. | Oct 2016 | B2 |
9477632 | Du | Oct 2016 | B2 |
9501398 | George et al. | Nov 2016 | B2 |
9525737 | Friedman | Dec 2016 | B2 |
9529542 | Friedman et al. | Dec 2016 | B2 |
9535631 | Fu et al. | Jan 2017 | B2 |
9552248 | Miller et al. | Jan 2017 | B2 |
9552291 | Munetoh et al. | Jan 2017 | B2 |
9552299 | Stalzer | Jan 2017 | B2 |
9563517 | Natanzon et al. | Feb 2017 | B1 |
9588698 | Karamcheti et al. | Mar 2017 | B1 |
9588712 | Kalos et al. | Mar 2017 | B2 |
9594652 | Sathiamoorthy et al. | Mar 2017 | B1 |
9600193 | Ahrens et al. | Mar 2017 | B2 |
9619321 | Sharon et al. | Apr 2017 | B1 |
9619430 | Kannan et al. | Apr 2017 | B2 |
9645754 | Li et al. | May 2017 | B2 |
9667720 | Bent et al. | May 2017 | B1 |
9710535 | Aizman et al. | Jul 2017 | B2 |
9733840 | Karamcheti et al. | Aug 2017 | B2 |
9734225 | Akirav et al. | Aug 2017 | B2 |
9740403 | Storer et al. | Aug 2017 | B2 |
9740700 | Chopra et al. | Aug 2017 | B1 |
9740762 | Horowitz et al. | Aug 2017 | B2 |
9747319 | Bestler et al. | Aug 2017 | B2 |
9747320 | Kesselman | Aug 2017 | B2 |
9767130 | Bestler et al. | Sep 2017 | B2 |
9781227 | Friedman et al. | Oct 2017 | B2 |
9785498 | Misra et al. | Oct 2017 | B2 |
9798486 | Singh | Oct 2017 | B1 |
9804925 | Carmi et al. | Oct 2017 | B1 |
9811285 | Karamcheti et al. | Nov 2017 | B1 |
9811546 | Bent et al. | Nov 2017 | B1 |
9818478 | Chung | Nov 2017 | B2 |
9829066 | Thomas et al. | Nov 2017 | B2 |
9836245 | Hayes et al. | Dec 2017 | B2 |
9891854 | Munetoh et al. | Feb 2018 | B2 |
9891860 | Delgado et al. | Feb 2018 | B1 |
9892005 | Kedem et al. | Feb 2018 | B2 |
9892186 | Akirav et al. | Feb 2018 | B2 |
9904589 | Donlan et al. | Feb 2018 | B1 |
9904717 | Anglin et al. | Feb 2018 | B2 |
9952809 | Shah | Feb 2018 | B2 |
9910748 | Pan | Mar 2018 | B2 |
9910904 | Anglin et al. | Mar 2018 | B2 |
9934237 | Shilane et al. | Apr 2018 | B1 |
9940065 | Kalos et al. | Apr 2018 | B2 |
9946604 | Glass | Apr 2018 | B1 |
9959167 | Donlan et al. | May 2018 | B1 |
9965539 | D'halluin et al. | May 2018 | B2 |
9998539 | Brock et al. | Jun 2018 | B1 |
10007457 | Hayes et al. | Jun 2018 | B2 |
10013177 | Liu et al. | Jul 2018 | B2 |
10013311 | Sundaram et al. | Jul 2018 | B2 |
10019314 | Litsyn et al. | Jul 2018 | B2 |
10019317 | Usvyatsky et al. | Jul 2018 | B2 |
10031703 | Natanzon et al. | Jul 2018 | B1 |
10061512 | Chu et al. | Aug 2018 | B2 |
10073626 | Karamcheti et al. | Sep 2018 | B2 |
10082985 | Hayes et al. | Sep 2018 | B2 |
10089012 | Chen et al. | Oct 2018 | B1 |
10089174 | Lin | Oct 2018 | B2 |
10089176 | Donlan et al. | Oct 2018 | B1 |
10108819 | Donlan et al. | Oct 2018 | B1 |
10146787 | Bashyam et al. | Dec 2018 | B2 |
10152268 | Chakraborty et al. | Dec 2018 | B1 |
10157098 | Chung et al. | Dec 2018 | B2 |
10162704 | Kirschner et al. | Dec 2018 | B1 |
10180875 | Northcott | Jan 2019 | B2 |
10185730 | Bestler et al. | Jan 2019 | B2 |
10235065 | Miller et al. | Mar 2019 | B1 |
20020144059 | Kendall | Oct 2002 | A1 |
20020156613 | Geng | Oct 2002 | A1 |
20030105984 | Masuyama et al. | Jun 2003 | A1 |
20030110205 | Johnson | Jun 2003 | A1 |
20040161086 | Buntin et al. | Aug 2004 | A1 |
20050001652 | Malik et al. | Jan 2005 | A1 |
20050076228 | Davis et al. | Apr 2005 | A1 |
20050235132 | Karr et al. | Oct 2005 | A1 |
20050278460 | Shin et al. | Dec 2005 | A1 |
20050283649 | Turner et al. | Dec 2005 | A1 |
20060015683 | Ashmore et al. | Jan 2006 | A1 |
20060114930 | Lucas et al. | Jun 2006 | A1 |
20060174157 | Barrail et al. | Aug 2006 | A1 |
20060248294 | Nedved et al. | Nov 2006 | A1 |
20070079068 | Draggon | Apr 2007 | A1 |
20070214194 | Reuter | Sep 2007 | A1 |
20070214314 | Reuter | Sep 2007 | A1 |
20070234016 | Davis et al. | Oct 2007 | A1 |
20070268905 | Baker et al. | Nov 2007 | A1 |
20080080709 | Michtchenko et al. | Apr 2008 | A1 |
20080107274 | Worthy | May 2008 | A1 |
20080155191 | Anderson et al. | Jun 2008 | A1 |
20080295118 | Liao | Nov 2008 | A1 |
20090077208 | Nguyen et al. | Mar 2009 | A1 |
20090138654 | Sutardja | May 2009 | A1 |
20090216910 | Duchesneau | Aug 2009 | A1 |
20090216920 | Lauterbach et al. | Aug 2009 | A1 |
20090327462 | Adams | Dec 2009 | A1 |
20100017444 | Chatterjee et al. | Jan 2010 | A1 |
20100042636 | Lu | Feb 2010 | A1 |
20100094806 | Apostolides et al. | Apr 2010 | A1 |
20100115070 | Missimilly | May 2010 | A1 |
20100125695 | Wu et al. | May 2010 | A1 |
20100162076 | Sim-Tang et al. | Jun 2010 | A1 |
20100169707 | Mathew et al. | Jul 2010 | A1 |
20100174576 | Naylor | Jul 2010 | A1 |
20100268908 | Ouyang et al. | Oct 2010 | A1 |
20110040925 | Frost et al. | Feb 2011 | A1 |
20110060927 | Fillingim et al. | Mar 2011 | A1 |
20110119462 | Leach et al. | May 2011 | A1 |
20110219170 | Frost et al. | Sep 2011 | A1 |
20110238625 | Hamaguchi et al. | Sep 2011 | A1 |
20110264843 | Haines et al. | Oct 2011 | A1 |
20110302369 | Goto et al. | Dec 2011 | A1 |
20120011398 | Eckhardt | Jan 2012 | A1 |
20120079318 | Colgrove et al. | Mar 2012 | A1 |
20120089567 | Takahashi et al. | Apr 2012 | A1 |
20120110249 | Jeong et al. | May 2012 | A1 |
20120131253 | McKnight | May 2012 | A1 |
20120158923 | Mohamed et al. | Jun 2012 | A1 |
20120191900 | Kunimatsu et al. | Jul 2012 | A1 |
20120198152 | Terry et al. | Aug 2012 | A1 |
20120198261 | Brown et al. | Aug 2012 | A1 |
20120209943 | Jung | Aug 2012 | A1 |
20120226934 | Rao | Sep 2012 | A1 |
20120246435 | Meir et al. | Sep 2012 | A1 |
20120260055 | Murase | Oct 2012 | A1 |
20120311557 | Resch | Dec 2012 | A1 |
20130022201 | Glew et al. | Jan 2013 | A1 |
20130036314 | Glew et al. | Feb 2013 | A1 |
20130042056 | Shats | Feb 2013 | A1 |
20130060884 | Bernbo et al. | Mar 2013 | A1 |
20130067188 | Mehra et al. | Mar 2013 | A1 |
20130073894 | Xavier et al. | Mar 2013 | A1 |
20130124776 | Hallak et al. | May 2013 | A1 |
20130132800 | Healy et al. | May 2013 | A1 |
20130151653 | Sawiki | Jun 2013 | A1 |
20130151771 | Tsukahara et al. | Jun 2013 | A1 |
20130173853 | Ungureanu et al. | Jul 2013 | A1 |
20130238554 | Yucel et al. | Sep 2013 | A1 |
20130339314 | Carpenter et al. | Dec 2013 | A1 |
20130339635 | Amit et al. | Dec 2013 | A1 |
20130339818 | Baker et al. | Dec 2013 | A1 |
20140040535 | Lee | Feb 2014 | A1 |
20140040702 | He et al. | Feb 2014 | A1 |
20140047263 | Coatney et al. | Feb 2014 | A1 |
20140047269 | Kim | Feb 2014 | A1 |
20140063721 | Herman et al. | Mar 2014 | A1 |
20140064048 | Cohen et al. | Mar 2014 | A1 |
20140068224 | Fan et al. | Mar 2014 | A1 |
20140075252 | Luo et al. | Mar 2014 | A1 |
20140122510 | Namkoong et al. | May 2014 | A1 |
20140136880 | Shankar et al. | May 2014 | A1 |
20140181402 | White | Jun 2014 | A1 |
20140237164 | Le et al. | Aug 2014 | A1 |
20140279936 | Bernbo et al. | Sep 2014 | A1 |
20140280025 | Eidson et al. | Sep 2014 | A1 |
20140289588 | Nagadomi et al. | Sep 2014 | A1 |
20140330785 | Isherwood et al. | Nov 2014 | A1 |
20140372838 | Lou et al. | Dec 2014 | A1 |
20140380125 | Calder et al. | Dec 2014 | A1 |
20140380126 | Yekhanin et al. | Dec 2014 | A1 |
20150032720 | James | Jan 2015 | A1 |
20150039645 | Lewis | Feb 2015 | A1 |
20150039849 | Lewis | Feb 2015 | A1 |
20150089283 | Kermarrec et al. | Mar 2015 | A1 |
20150100746 | Rychlik | Apr 2015 | A1 |
20150134824 | Mickens | May 2015 | A1 |
20150153800 | Lucas et al. | Jun 2015 | A1 |
20150180714 | Chunn | Jun 2015 | A1 |
20150280959 | Vincent | Oct 2015 | A1 |
20160246537 | Kim | Feb 2016 | A1 |
20160191508 | Bestler et al. | Jun 2016 | A1 |
20160378612 | Hipsh et al. | Dec 2016 | A1 |
20170091236 | Hayes et al. | Mar 2017 | A1 |
20170103092 | Hu et al. | Apr 2017 | A1 |
20170103094 | Hu et al. | Apr 2017 | A1 |
20170103098 | Hu et al. | Apr 2017 | A1 |
20170103116 | Hu et al. | Apr 2017 | A1 |
20170177236 | Haratsch et al. | Jun 2017 | A1 |
20180039442 | Shadrin et al. | Feb 2018 | A1 |
20180081958 | Akirav et al. | Mar 2018 | A1 |
20180101441 | Hyun et al. | Apr 2018 | A1 |
20180101587 | Anglin et al. | Apr 2018 | A1 |
20180101588 | Anglin et al. | Apr 2018 | A1 |
20180217756 | Liu et al. | Aug 2018 | A1 |
20180307560 | Vishnumolakala et al. | Oct 2018 | A1 |
20180321874 | Li et al. | Nov 2018 | A1 |
20190036703 | Bestler | Jan 2019 | A1 |
Number | Date | Country |
---|---|---|
2164006 | Mar 2010 | EP |
2256621 | Dec 2010 | EP |
WO 02-13033 | Feb 2002 | WO |
WO 2008103569 | Aug 2008 | WO |
WO 2008157081 | Dec 2008 | WO |
WO 2013032825 | Jul 2013 | WO |
Entry |
---|
Hwang, Kai, et al. “RAID-x: A New Distributed Disk Array for I/O-Centric Cluster Computing,” HPDC '00 Proceedings of the 9th IEEE International Symposium on High Performance Distributed Computing, IEEE, 2000, pp. 279-286. |
Schmid, Patrick: “RAID Scaling Charts, Part 3:4-128 kB Stripes Compared”, Tom's Hardware, Nov. 27, 2007 (http://www.tomshardware.com/reviews/RAID-SCALING-CHARTS.1735-4.html), See pp. 1-2. |
Storer, Mark W. et al., “Pergamum: Replacing Tape with Energy Efficient, Reliable, Disk-Based Archival Storage,” Fast '08: 6th USENIX Conference on File and Storage Technologies, San Jose, CA, Feb. 26-29, 2008 pp. 1-16. |
Ju-Kyeong Kim et al., “Data Access Frequency based Data Replication Method using Erasure Codes in Cloud Storage System”, Journal of the Institute of Electronics and Information Engineers, Feb. 2014, vol. 51, No. 2, pp. 85-91. |
International Search Report and the Written Opinion of the International Searching Authority, PCT/US2015/018169, dated May 15, 2015. |
International Search Report and the Written Opinion of the International Searching Authority, PCT/US2015/034302, dated Sep. 11, 2015. |
International Search Report and the Written Opinion of the International Searching Authority, PCT/US2015/039135, dated Sep. 18, 2015. |
International Search Report and the Written Opinion of the International Searching Authority, PCT/US2015/039136, dated Sep. 23, 2015. |
International Search Report, PCT/US2015/039142, dated Sep. 24, 2015. |
International Search Report, PCT/US2015/034291, dated Sep. 30, 2015. |
International Search Report and the Written Opinion of the International Searching Authority, PCT/US2015/039137, dated Oct. 1, 2015. |
International Search Report, PCT/US2015/044370, dated Dec. 15, 2015. |
International Search Report amd the Written Opinion of the International Searching Authority, PCT/US2016/031039, dated May 5, 2016. |
International Search Report, PCT/US2016/014604, dated May 19, 2016. |
International Search Report, PCT/US2016/014361, dated May 30, 2016. |
International Search Report, PCT/US2016/014356, dated Jun. 28, 2016. |
International Search Report, PCT/US2016/014357, dated Jun. 29, 2016. |
International Seach Report and the Written Opinion of the International Searching Authority, PCT/US2016/016504, dated Jul. 6, 2016. |
International Seach Report and the Written Opinion of the International Searching Authority, PCT/US2016/024391, dated Jul. 12, 2016. |
International Seach Report and the Written Opinion of the International Searching Authority, PCT/US2016/026529, dated Jul. 19, 2016. |
International Seach Report and the Written Opinion of the International Searching Authority, PCT/US2016/023485, dated Jul. 21, 2016. |
International Seach Report and the Written Opinion of the International Searching Authority, PCT/US2016/033306, dated Aug. 19, 2016. |
International Seach Report and the Written Opinion of the International Searching Authority, PCT/US2016/047808, dated Nov. 25, 2016. |
Stalzer, Mark A., “FlashBlades: System Architecture and Applications,” Proceedings of the 2nd Workshop on Architectures and Systems for Big Data, Association for Computing Machinery, New York, NY, 2012, pp. 10-14. |
International Seach Report and the Written Opinion of the International Searching Authority, PCT/US2016/042147, dated Nov. 30, 2016. |
Number | Date | Country | |
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Parent | 16050464 | Jul 2018 | US |
Child | 16700927 | US | |
Parent | 14464552 | Aug 2014 | US |
Child | 16050464 | US |