Patent Grant
10503700
Example methods, apparatus, and products for on-demand content filtering of snapshots within a storage system in accordance with the present disclosure are described with reference to the accompanying drawings, beginning with
The storage system (100) depicted in
The example storage arrays (102, 104) depicted in
The computing devices (164, 166, 168, 170) depicted in
Each storage array (102, 104) depicted in
Each storage array controller (106, 112, 118, 120) may be implemented in a variety of ways, including as a Field Programmable Gate Array (‘FPGA’), a Programmable Logic Chip (‘PLC’), an Application Specific Integrated Circuit (‘ASIC’), or computing device that includes discrete components such as a central processing unit, computer memory, and various adapters. Each storage array controller (106, 112, 118, 120) may include, for example, a data communications adapter configured to support communications via the SAN (158) and the LAN (160). Although only one of the storage array controllers (120) in the example of
In the example depicted in
Consider an example in which a first storage array controller (106) in a first storage array (102) is the active storage array controller that is allowed to direct access requests to the storage devices (146) or write buffer devices (148) within the first storage array (102), while a second storage array controller (118) in the first storage array (102) is the passive storage array controller that is not allowed to direct access requests to the storage devices (146) or write buffer devices (148) within the first storage array (102). In such an example, the second storage array controller (118) may continue to receive access requests from the computing devices (164, 166, 168, 170) via the SAN (158) or LAN (160). Upon receiving access requests from the computing devices (164, 166, 168, 170), the second storage array controller (118) may be configured to forward such access requests to the first storage array controller (106) via a communications link between the first storage array controller (106) and the second storage array controller (118). Readers will appreciate that such an embodiment may reduce the amount of coordination that must occur between the first storage array controller (106) and the second storage array controller (118) relative to an embodiment where both storage array controllers (106, 118) are allowed to simultaneously modify the contents of the storage devices (146) or write buffer devices (148).
Although the example described above refers to an embodiment where the first storage array controller (106) is the active storage array controller while the second storage array controller (118) is the passive storage array controller, over time such designations may switch back and forth. For example, an expected or unexpected event may occur that results in a situation where the first storage array controller (106) is the passive storage array controller while the second storage array controller (118) is the active storage array controller. An example of an unexpected event that could cause a change in the roles of each storage array controller (106, 118) is the occurrence of a failure or error condition with the first storage array controller (106) that causes the storage array (102) to fail over to the second storage array controller (118). An example of an expected event that could cause a change in the roles of each storage array controller (106, 118) is the expiration of a predetermined period of time, as the first storage array controller (106) may be responsible for interacting with the storage devices (146) and the write buffer devices (148) during a first time period while the second storage array controller (118) may be responsible for interacting with the storage devices (146) and the write buffer devices (148) during a second time period. Readers will appreciate that although the preceding paragraphs describe active and passive storage array controllers with reference to the first storage array (102), the storage array controllers (112, 120) that are part of other storage arrays (104) in the storage system (100) may operate in a similar manner.
Each storage array (102, 104) depicted in
The presence of the write buffer devices (148, 152) may also improve the utilization of the storage devices (146, 150) as a storage array controller (106, 112, 118, 120) can accumulate more writes and organize writing to the storage devices (146, 150) for greater efficiency. Greater efficiency can be achieved, for example, as the storage array controller (106, 112, 118, 120) may have more time to perform deeper compression of the data, the storage array controller (106, 112, 118, 120) may be able to organize the data into write blocks that are in better alignment with the underlying physical storage on the storage devices (146, 150), the storage array controller (106, 112, 118, 120) may be able to perform deduplication operations on the data, and so on. Such write buffer devices (148, 152) effectively convert storage arrays of solid-state drives (e.g., “Flash drives”) from latency limited devices to throughput limited devices. In such a way, the storage array controller (106, 112, 118, 120) may be given more time to better organize what is written to the storage devices (146, 150), but after doing so, are not then mechanically limited like disk-based arrays are.
Each storage array (102, 104) depicted in
The storage array controllers (106, 112) of
On-demand content filtering of snapshots within a storage system in accordance with embodiments of the present disclosure is generally implemented with computers. In the system of
The storage array controller (202) of
The storage array controller (202) of
Stored in RAM (236) is an operating system (246). Examples of operating systems useful in storage array controllers (202) configured for on-demand content filtering of snapshots within a storage system according to some embodiments of the present disclosure include UNIX™, Linux™, Microsoft Windows™, and others as will occur to those of skill in the art. The operating system (246) depicted in
The storage array controller (202) detailed in
Also stored in RAM (236) is a snapshot filtering module (250), a module that includes computer program instructions useful in on-demand content filtering of snapshots within a storage system according to some embodiments of the present disclosure. The snapshot filtering module (250) may perform on-demand content filtering of snapshots within a storage system by: associating an access policy with a snapshot, the access policy specifying a transformation to apply to a predefined data object; receiving a first request to access a portion of the snapshot; and responsive to receiving the first request: creating a transformed snapshot portion by applying the transformation specified in the access policy to one or more data objects contained within the portion of the snapshot; and presenting the transformed snapshot portion. Readers will appreciate that snapshot filtering module (250) may be further useful in on-demand content filtering of snapshots within a storage system according to some embodiments of the present disclosure by performing other functions as will be described in greater detail below, including all of the steps and functions described in the flowcharts that are included below.
The storage array controller (202) of
The storage array controller (202) of
The storage array controller (202) of
Readers will recognize that these components, protocols, adapters, and architectures are for illustration only, not limitation. Such a storage array controller may be implemented in a variety of different ways, each of which is well within the scope of the present disclosure.
For further explanation,
The write buffer device (312) depicted in
The write buffer device (312) depicted in
The write buffer device (312) depicted in
The write buffer device (312) depicted in
The write buffer device (312) depicted in
The write buffer device (312) depicted in
In the example depicted in
In the example depicted in
In the example depicted in
In the example depicted in
Readers will appreciate that although the examples described above include various system configurations, device configurations, and so on, the examples described above are included only for explanatory purposes. In fact, on-demand content filtering of snapshots within a storage system according to some embodiments of the present disclosure may be carried out on storage devices that are different than the storage devices described above and on storage systems that are different than the storage systems described above. For example, storage systems configured for on-demand content filtering of snapshots within a storage system according to some embodiments of the present disclosure may be carried out in storage systems that include no write cache, in storage systems that do not include a non-volatile write cache, on storage systems that where the components of the storage system are in the form factor of a blade computing device that includes processing resources, storage resources, or any combination thereof.
Readers will appreciate that the storage systems and the components that are contained in such storage systems, as described in the present disclosure, are included for explanatory purposes and do not represent limitations as to the types of systems that may be configured for on-demand content filtering of snapshots. In fact, storage systems configured for on-demand content filtering of snapshots may be embodied in many other ways and may include fewer, additional, or different components. For example, storage within storage systems configured for on-demand content filtering of snapshots may be embodied as block storage where data is stored in blocks, and each block essentially acts as an individual hard drive. Alternatively, storage within storage systems configured for on-demand content filtering of snapshots may be embodied as object storage, where data is managed as objects. Each object may include the data itself, a variable amount of metadata, and a globally unique identifier, where object storage can be implemented at multiple levels (e.g., device level, system level, interface level). In addition, storage within storage systems configured for on-demand content filtering of snapshots may be embodied as file storage in which data is stored in a hierarchical structure. Such data may be saved in files and folders, and presented to both the system storing it and the system retrieving it in the same format. Such data may be accessed using the Network File System (‘NFS’) protocol for Unix or Linux, Server Message Block (‘SMB’) protocol for Microsoft Windows, or in some other manner.
For further explanation,
The example method depicted in
In the example method depicted in
Consider an example in which a particular access policy (414) specifies a transformation to apply to a predefined data object that adheres to the following predefined formats: ###-##-####, ##/##/####, and (###)###-####, where ‘#” represents a wildcard character. In such an example, the predefined formats may represent standard formats for confidential information in the form of a social security number, a date of birth, and a telephone number. In such an example, the access policy (414) may include a rule specifying that, when data in one of the predefined formats is discovered within a snapshot (416), each wildcard character should be replaced by a value of ‘1’.
Consider an additional example in which a particular access policy (414) specifies a transformation to apply to a predefined data object that is of a particular data type such as integer data. In such an example, integer data may be viewed as a data type whose contents are more likely to represent standard formats for confidential information such as credit card numbers, social security numbers, and so on. In such an example, the access policy (414) may include a rule specifying that, when integer data is discovered within a snapshot (416), each integer should be replaced by a value of ‘1’.
Readers will appreciate that an access policy (414) may also specify a transformation to apply to a predefined data object that is of a particular subject matter type. For example, the access policy (414) may include a rule specifying that, when financial data is discovered within a snapshot (416), each integer should be replaced by a value of ‘1’, each letter should be replaced by a value of ‘X’, and so on. Likewise, another access policy (414) may include a rule specifying that, when healthcare data is discovered within a snapshot (416), each integer should be replaced by a value of ‘1’, each letter should be replaced by a value of ‘X’, and so on. In such a way, general categories of data may be masked regardless of the particular format that the data takes.
The example method depicted in
The example method depicted in
Consider the example described above in which a particular access policy (414) specifies that for predefined data objects that adhere to the following predefined formats: ###-##-####, ##/##/####, and (###)###-####, each wildcard should be replaced by a value of ‘1’. In such an example, creating (406) a transformed snapshot portion (408) may be carried out by searching the portion of the snapshot (416) to identify data that adheres to the predefined formats described above. Upon discovering data that adheres to the predefined formats described above in the portion of the snapshot (416), a transformed snapshot portion (408) may be created (406) by replacing each wildcard character with a value of ‘1’. For example, the discovery of data such as ‘123-45-6789’ would result in a transformed snapshot portion (408) where such data would be transformed to ‘111-11-1111’.
The example method depicted in
For further explanation,
The example method depicted in
The example method depicted in
Readers will appreciate that in alternative embodiments where the underlying storage devices do not support the in-place overwrite of data, the modified versions of the one or more data objects within the portion of the snapshot (416) that match the predefined data object specified in the access policy (414) may be stored at a location within the storage device (412) or at some other location within the read path that is distinct from the location at which the unmodified version of the one or more data objects within the portion of the snapshot (416) that match the predefined data object specified in the access policy (414) are stored. Consider an example in which the portion of the snapshot (416) resides at addresses 9000-10000 of a first volume. In such an example, assume that data that takes the format of “(123)456-7890” is discovered at addresses 9101-9112 of the first volume. In such an example, by applying the transformations described above, a modified version of such a data object can be created that takes the format of “(111)111-1111” and is stored at addresses 10001-10012 of the first volume. In this example, mapping tables or other internal data structures may be updated such that the portion of the snapshot (416) is specified as including the content of addresses 9000-9100 of the first volume, followed by the contents of addresses 10001-10012 of the first volume, followed by the content of addresses 9113-10000 of the first volume.
For further explanation,
The example method depicted in
Readers will appreciate that the transformed snapshot portion (408) may include portions of the snapshot (416) that were not transformed as well as portions of the snapshot (416) that were transformed by applying a transformation specified in the access policy (414) to one or more data objects contained within the snapshot (416). In such an example, storing (602) the transformed snapshot portion (408) can include modifying mapping tables or other data structures that are used to map logical or physical addresses of data to a particular snapshot, thereby defining the transformed snapshot portion (408) as a collection of data stored at the logical or physical addresses specified in the mapping tables or other data structure utilized by a particular storage system.
For further explanation,
In the example method depicted in
For further explanation,
The example method depicted in
Readers will appreciate that although the example method depicted in
The example method depicted in
Readers will further appreciate that although the preceding paragraphs describe an embodiment where a first request (418) to access a portion of the snapshot (416) is received (404) and a second request (802) to access the same portion of the snapshot (416) is subsequently received (804), requests to access partially overlapping portions of the snapshot (416) may also be handled in a way where providing access to the overlapping portions of the snapshot (416) may be carried out without performing the steps required to recreate the overlapping portions of the transformed snapshot portion (408). Consider an example in which the first request (418) includes a request to access a portion of the snapshot (416) that is stored at addresses 0-1000 within a particular volume. Assume in such an example, that a second request (802) includes a request to access a portion of the snapshot (416) that is stored at addresses 500-1500 within the same particular volume. In such an example, the portion of the snapshot (416) that is stored at addresses 1001-1500 may undergo the transformation processes in response to the second request (802), but the previously generated transformed snapshot portion (408) that represents the portion of the snapshot (416) that is stored at addresses 500-1000 may be retrieved from the storage system (400) without needing to again performing the steps required to recreate the overlapping portions of the transformed snapshot portion (408) that represents the portion of the snapshot (416) that is stored at addresses 500-1000.
For further explanation,
In the example method depicted in
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 can distribute user data across storage nodes housed within a chassis, for example, using erasure coding and redundant copies of metadata. Erasure coding refers to a method of data protection or reconstruction in which data is stored across a set of different locations, such as disks, storage nodes, geographic locations, and so on. 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 may be 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, may all be handled on a distributed basis. Data may be 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 may be 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 may be 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 suitable. The chassis can provide 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), hypertext transfer protocol (HTTP), or other suitable interface. 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 may be connected to one or more non-volatile solid state memory units, which may be referred to as storage units or storage devices. 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, 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 may 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 may contain an embedded 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 may be 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 nodes and non-volatile solid state storage may be the ability to proactively rebuild data in a storage cluster. The storage nodes and non-volatile solid state storage may be able to determine when a storage node or non-volatile solid state storage in the storage cluster is unreachable, independent of whether there is an attempt to read data involving that storage node or non-volatile solid state storage. The storage nodes and non-volatile solid state storage may then cooperate to recover and rebuild the data in at least partially new locations. This constitutes a proactive rebuild, in that the system rebuilds data without waiting until the data is needed for a read access initiated from a client system employing the storage cluster. These and further details of the storage memory and operation thereof are discussed below.
Each storage node (1012) can have multiple components. In the embodiment shown here, the storage node (1012) includes a printed circuit board (1022) populated by a CPU (1016), i.e., processor, a memory (1014) coupled to the CPU (1016), and a non-volatile solid state storage (1018) coupled to the CPU (1016), although other mountings and/or components could be used in further embodiments. The memory (1014) may include instructions which are executed by the CPU (1016) and/or data operated on by the CPU (1016). As further explained below, the non-volatile solid state storage (1018) may include flash or, in further embodiments, other types of solid-state memory.
Referring to
Every piece of data, and every piece of metadata, may have redundancy in the system in some embodiments. In addition, every piece of data and every piece of metadata may have an owner, which may be referred to as an authority (1102). If that authority (1102) is unreachable, for example through failure of a storage node (1012), there may be a plan of succession for how to find that data or that metadata. In various embodiments, there are redundant copies of authorities (1102). Authorities (1102) may have a relationship to storage nodes (1012) and to non-volatile solid state storage (1018) in some embodiments. Each authority (1102), covering a range of data segment numbers or other identifiers of the data, may be assigned to a specific non-volatile solid state storage (1018). In some embodiments the authorities (1102) for all of such ranges are distributed over the non-volatile solid state storage (1018) of a storage cluster. Each storage node (1012) may have a network port that provides access to the non-volatile solid state storage (1018) of that storage node (1012). 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 stripe in some embodiments. The assignment and use of the authorities (1102) may therefore establish an indirection to data. Indirection may be referred to as the ability to reference data indirectly, in this case via an authority (1102), in accordance with some embodiments. A segment may identify a set of non-volatile solid state storage (1018) and a local identifier into the set of non-volatile solid state storage (1018) 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 (1018) may be applied to locating data for writing to or reading from the non-volatile solid state storage (1018) (in the form of a RAID stripe). Data may be striped across multiple units of non-volatile solid state storage (1018), which may include or be different from the non-volatile solid state storage (1018) having the authority (1102) 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 (1102) for that data segment may be consulted, at that non-volatile solid state storage (1018) or storage node (1012) having that authority (1102). 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 (1018) having the authority (1102) 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 (1018), 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 (1018) having that authority (1102). 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 (1018) for an authority in the presence of a set of non-volatile solid state storage (1018) that are reachable and constitute the same cluster. The calculation also determines an ordered set of peer non-volatile solid state storage (1018) 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 (1102) may be consulted if a specific authority (1102) is unavailable in some embodiments.
With reference to
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 may be 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 may be grouped into sets called authorities. Each authority may have 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 may contain the authority, and that the authority may, in turn, contain entities.
A segment may be a logical container of data in accordance with some embodiments. A segment may be 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 meta-data, 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 may be 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 may be distributed, i.e., striped, across non-volatile solid state storage (1018) coupled to the host CPUs (1016) 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 may take place across an entire storage system. At the top may be the directory entries (file names) which link to an inode. Inodes may 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 may then be translated into physical flash locations. Physical flash locations may have an address range bounded by the amount of flash in the system in accordance with some embodiments. Medium addresses and segment addresses may be 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 (1018) unit may be assigned a range of address space. Within this assigned range, the non-volatile solid state storage (1018) may be able to allocate addresses without synchronization with other non-volatile solid state storage (1018).
Data and metadata may be stored by a set of underlying storage layouts that are optimized for varying workload patterns and storage devices. These layouts may incorporate multiple redundancy schemes, compression formats and index algorithms. Some of these layouts may store information about authorities and authority masters, while others may store file metadata and file data. The redundancy schemes may 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 may be used within a storage cluster, and mirroring may be 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 may 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 pseudo randomly 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 may 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 may be independent of the placement of authorities for data consistency. In some embodiments, storage nodes that contain authorities may not contain any persistent storage. Instead, the storage nodes may be 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 can consist 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 Ethernet backplane, and chassis are connected together to form a storage cluster. Storage clusters may be 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 may 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 may be transferred to a new storage node. Transient failures can 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 may go into a self-preservation mode and halt replication and data movement activities until an administrator intervenes in accordance with some embodiments.
Persistent messages may be persistently stored prior to being transmitted. 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 may virtualize addresses. These virtualized addresses may 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 may correlate 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 may also enable 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.
Storage clusters, in various embodiments as disclosed herein, can be contrasted with storage arrays in general. The storage nodes (1012) may be part of a collection that creates the storage cluster. Each storage node (1012) may own a slice of data and computing required to provide the data. Multiple storage nodes (1012) can cooperate to store and retrieve the data. Storage memory or storage devices, as used in storage arrays in general, may be less involved with processing and manipulating the data. Storage memory or storage devices in a storage array may receive commands to read, write, or erase data. The storage memory or storage devices in a storage array may not be aware of a larger system in which they are embedded, or what the data means. Storage memory or storage devices in storage arrays can include various types of storage memory, such as RAM, solid state drives, hard disk drives, etc. The non-volatile solid state storage (1018) units described herein may have multiple interfaces active simultaneously and serving multiple purposes. In some embodiments, some of the functionality of a storage node (1012) is shifted into a non-volatile solid state storage (1018) unit, transforming the non-volatile solid state storage (1018) unit into a combination of non-volatile solid state storage (1018) unit and storage node (1012). Placing computing (relative to storage data) into the non-volatile solid state storage (1018) unit places this computing closer to the data itself. The various system embodiments have a hierarchy of storage node layers with different capabilities. By contrast, in a storage array, a controller may own and know everything about all of the data that the controller manages in a shelf or storage devices. In a storage cluster, as described herein, multiple controllers in multiple non-volatile solid state storage (1018) units and/or storage nodes (1012) may cooperate in various ways (e.g., for erasure coding, data sharding, metadata communication and redundancy, storage capacity expansion or contraction, data recovery, and so on).
The physical storage may be divided into named regions based on application usage in some embodiments. The NVRAM (1304) may be a contiguous block of reserved memory in the storage unit (1352) DRAM that is backed by NAND flash. The NVRAM (1304) may be logically divided into multiple memory regions written for two as spool (e.g., spool region). Space within the NVRAM (1352) spools may be managed by each authority independently. Each device can provide an amount of storage space to each authority. That authority can further manage lifetimes and allocations within that space. Examples of a spool include distributed transactions or notions. When the primary power to a storage unit (1352) fails, onboard super-capacitors can provide a short duration of power hold up. During this holdup interval, the contents of the NVRAM (1304) may be flushed to flash memory (1306). On the next power-on, the contents of the NVRAM (1304) may be recovered from the flash memory (1306).
As for the storage unit controller, the responsibility of the logical “controller” may be distributed across each of the blades containing authorities. This distribution of logical control is shown in
In the compute plane (1406) and storage planes (1408), the authorities (1410) may interact with the underlying physical resources (i.e., devices). From the point of view of an authority (1410), its resources may be striped over multiple the physical devices. From the point of view of a device, it provides resources to multiple authorities (1410), irrespective of where the authorities happen to run. In order to communicate and represent the ownership of an authority (1410), including the right to record persistent changes on behalf of that authority (1410), the authority (1410) may provide some evidence of authority ownership that can be independently verifiable. A token, for example, may be employed for this purpose and function in one embodiment.
Each authority (1410) may have allocated or have been allocated one or more partitions (1416) of storage memory in the storage units, e.g. partitions (1416) in flash memory (1412) and NVRAM (1414). Each authority (1410) may use those allocated partitions (1416) that belong to it, for writing or reading user data. Authorities can be associated with differing amounts of physical storage of the system. For example, one authority (1410) could have a larger number of partitions (1416) or larger sized partitions (1416) in one or more storage units than one or more other authority (1410).
Readers will appreciate that although the example methods described above are depicted in a way where a series of steps occurs in a particular order, no particular ordering of the steps is required unless explicitly stated. Example embodiments of the present disclosure are described largely in the context of a fully functional computer system for on-demand content filtering of snapshots. Readers of skill in the art will recognize, however, that the present disclosure also may be embodied in a computer program product disposed upon computer readable storage media for use with any suitable data processing system. Such computer readable storage media may be any storage medium for machine-readable information, including magnetic media, optical media, or other suitable media. Examples of such media include magnetic disks in hard drives or diskettes, compact disks for optical drives, magnetic tape, and others as will occur to those of skill in the art. Persons skilled in the art will immediately recognize that any computer system having suitable programming means will be capable of executing the steps of the method of the disclosure as embodied in a computer program product. Persons skilled in the art will recognize also that, although some of the example embodiments described in this specification are oriented to software installed and executing on computer hardware, nevertheless, alternative embodiments implemented as firmware or as hardware are well within the scope of the present disclosure. In fact, embodiments may include a system, a method, a computer program product, or others. The computer program product may include a computer readable storage medium (or media) having computer readable program instructions thereon for causing a processor to carry out aspects of the present disclosure.
The computer readable storage medium can be a tangible device that can retain and store instructions for use by an instruction execution device. The computer readable storage medium may be, for example, but is not limited to, an electronic storage device, a magnetic storage device, an optical storage device, an electromagnetic storage device, a semiconductor storage device, or any suitable combination of the foregoing. A non-exhaustive list of more specific examples of the computer readable storage medium includes the following: a portable computer diskette, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or Flash memory), a static random access memory (SRAM), a portable compact disc read-only memory (CD-ROM), a digital versatile disk (DVD), a memory stick, a floppy disk, a mechanically encoded device such as punch-cards or raised structures in a groove having instructions recorded thereon, and any suitable combination of the foregoing. A computer readable storage medium, as used herein, is not to be construed as being transitory signals per se, such as radio waves or other freely propagating electromagnetic waves, electromagnetic waves propagating through a waveguide or other transmission media (e.g., light pulses passing through a fiber-optic cable), or electrical signals transmitted through a wire.
Computer readable program instructions described herein can be downloaded to respective computing/processing devices from a computer readable storage medium or to an external computer or external storage device via a network, for example, the Internet, a local area network, a wide area network and/or a wireless network. The network may comprise copper transmission cables, optical transmission fibers, wireless transmission, routers, firewalls, switches, gateway computers and/or edge servers. A network adapter card or network interface in each computing/processing device receives computer readable program instructions from the network and forwards the computer readable program instructions for storage in a computer readable storage medium within the respective computing/processing device.
Computer readable program instructions for carrying out operations of the present disclosure may be assembler instructions, instruction-set-architecture (ISA) instructions, machine instructions, machine dependent instructions, microcode, firmware instructions, state-setting data, or either source code or object code written in any combination of one or more programming languages, including an object oriented programming language such as Smalltalk, C++ or the like, and conventional procedural programming languages, such as the “C” programming language or similar programming languages. The computer readable program instructions may execute entirely on the user's computer, partly on the user's computer, as a stand-alone software package, partly on the user's computer and partly on a remote computer or entirely on the remote computer or server. In the latter scenario, the remote computer may be connected to the user's computer through any type of network, including a local area network (LAN) or a wide area network (WAN), or the connection may be made to an external computer (for example, through the Internet using an Internet Service Provider). In some embodiments, electronic circuitry including, for example, programmable logic circuitry, field-programmable gate arrays (FPGA), or programmable logic arrays (PLA) may execute the computer readable program instructions by utilizing state information of the computer readable program instructions to personalize the electronic circuitry, in order to perform aspects of the present disclosure.
Aspects of the present disclosure are described herein with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the disclosure. 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, can be implemented by computer readable program instructions.
These computer readable 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 functions/acts specified in the flowchart and/or block diagram block or blocks. These computer readable program instructions may also be stored in a computer readable storage medium that can direct a computer, a programmable data processing apparatus, and/or other devices to function in a particular manner, such that the computer readable storage medium having instructions stored therein comprises an article of manufacture including instructions which implement aspects of the function/act specified in the flowchart and/or block diagram block or blocks.
The computer readable program instructions may also be loaded onto a computer, other programmable data processing apparatus, or other device to cause a series of operational steps to be performed on the computer, other programmable apparatus or other device to produce a computer implemented process, such that the instructions which execute on the computer, other programmable apparatus, or other device implement the functions/acts specified in the flowchart and/or block diagram block or blocks.
The flowchart and block diagrams in the Figures illustrate the architecture, functionality, and operation of possible implementations of systems, methods, and computer program products according to various embodiments of the present disclosure. In this regard, each block in the flowchart or block diagrams may represent a module, segment, or portion of instructions, which comprises one or more executable instructions for implementing the specified logical function(s). In some alternative implementations, the functions noted in the block may occur out of the order noted in the figures. For example, two blocks shown in succession may, in fact, be executed substantially concurrently, or the blocks may sometimes be executed in the reverse order, depending upon the functionality involved. It will also be noted that each block of the block diagrams and/or flowchart illustration, and combinations of blocks in the block diagrams and/or flowchart illustration, can be implemented by special purpose hardware-based systems that perform the specified functions or acts or carry out combinations of special purpose hardware and computer instructions.
Readers will appreciate that the steps described herein may be carried out in a variety ways and that no particular ordering is required. It will be further understood from the foregoing description that modifications and changes may be made in various embodiments of the present disclosure without departing from its true spirit. The descriptions in this specification are for purposes of illustration only and are not to be construed in a limiting sense. The scope of the present disclosure is limited only by the language of the following claims.
| Number | Name | Date | Kind |
|---|---|---|---|
| 5706210 | Kumano et al. | Jan 1998 | A |
| 5799200 | Brant et al. | Aug 1998 | A |
| 5933598 | Scales et al. | Aug 1999 | A |
| 6012032 | Donovan et al. | Jan 2000 | A |
| 6085333 | DeKoning et al. | Jul 2000 | A |
| 6643641 | Snyder | Nov 2003 | B1 |
| 6647514 | Umberger et al. | Nov 2003 | B1 |
| 6789162 | Talagala et al. | Sep 2004 | B1 |
| 7089272 | Garthwaite et al. | Aug 2006 | B1 |
| 7107389 | Inagaki et al. | Sep 2006 | B2 |
| 7146521 | Nguyen | Dec 2006 | B1 |
| 7334124 | Pham et al. | Feb 2008 | B2 |
| 7437530 | Rajan | Oct 2008 | B1 |
| 7493424 | Bali et al. | Feb 2009 | B1 |
| 7669029 | Mishra et al. | Feb 2010 | B1 |
| 7689609 | Lango et al. | Mar 2010 | B2 |
| 7743191 | Liao | Jun 2010 | B1 |
| 7899780 | Shmuylovich et al. | Mar 2011 | B1 |
| 8042163 | Karr et al. | Oct 2011 | B1 |
| 8086585 | Brashers et al. | Dec 2011 | B1 |
| 8271700 | Annem et al. | Sep 2012 | B1 |
| 8387136 | Lee et al. | Feb 2013 | B2 |
| 8437189 | Montierth et al. | May 2013 | B1 |
| 8465332 | Hogan et al. | Jun 2013 | B2 |
| 8527544 | Colgrove et al. | Sep 2013 | B1 |
| 8566546 | Marshak et al. | Oct 2013 | B1 |
| 8578442 | Banerjee | Nov 2013 | B1 |
| 8613066 | Brezinski et al. | Dec 2013 | B1 |
| 8620970 | English et al. | Dec 2013 | B2 |
| 8751463 | Chamness | Jun 2014 | B1 |
| 8762642 | Bates et al. | Jun 2014 | B2 |
| 8769622 | Chang et al. | Jul 2014 | B2 |
| 8800009 | Beda, III et al. | Aug 2014 | B1 |
| 8812860 | Bray | Aug 2014 | B1 |
| 8850546 | Field et al. | Sep 2014 | B1 |
| 8898346 | Simmons | Nov 2014 | B1 |
| 8909854 | Yamagishi et al. | Dec 2014 | B2 |
| 8931041 | Banerjee | Jan 2015 | B1 |
| 8949863 | Coatney et al. | Feb 2015 | B1 |
| 8984602 | Bailey et al. | Mar 2015 | B1 |
| 8990905 | Bailey et al. | Mar 2015 | B1 |
| 9124569 | Hussain et al. | Sep 2015 | B2 |
| 9134922 | Rajagopal et al. | Sep 2015 | B2 |
| 9209973 | Aikas et al. | Dec 2015 | B2 |
| 9250823 | Kamat et al. | Feb 2016 | B1 |
| 9300660 | Borowiec et al. | Mar 2016 | B1 |
| 9444822 | Borowiec et al. | Sep 2016 | B1 |
| 9507532 | Colgrove et al. | Nov 2016 | B1 |
| 20020013802 | Mori et al. | Jan 2002 | A1 |
| 20030145172 | Galbraith et al. | Jul 2003 | A1 |
| 20030191783 | Wolczko et al. | Oct 2003 | A1 |
| 20030225961 | Chow et al. | Dec 2003 | A1 |
| 20040080985 | Chang et al. | Apr 2004 | A1 |
| 20040111573 | Garthwaite | Jun 2004 | A1 |
| 20040153844 | Ghose et al. | Aug 2004 | A1 |
| 20040193814 | Erickson et al. | Sep 2004 | A1 |
| 20040260967 | Guha et al. | Dec 2004 | A1 |
| 20050160416 | Jamison | Jul 2005 | A1 |
| 20050188246 | Emberty et al. | Aug 2005 | A1 |
| 20050216800 | Bicknell et al. | Sep 2005 | A1 |
| 20060015771 | Vana Gundy et al. | Jan 2006 | A1 |
| 20060129817 | Borneman et al. | Jun 2006 | A1 |
| 20060161726 | Lasser | Jul 2006 | A1 |
| 20060230245 | Gounares et al. | Oct 2006 | A1 |
| 20060239075 | Williams et al. | Oct 2006 | A1 |
| 20070022227 | Miki | Jan 2007 | A1 |
| 20070028068 | Golding et al. | Feb 2007 | A1 |
| 20070055702 | Fridella et al. | Mar 2007 | A1 |
| 20070109856 | Pellicone et al. | May 2007 | A1 |
| 20070150689 | Pandit et al. | Jun 2007 | A1 |
| 20070168321 | Saito et al. | Jul 2007 | A1 |
| 20070220227 | Long | Sep 2007 | A1 |
| 20070294563 | Bose | Dec 2007 | A1 |
| 20070294564 | Reddin et al. | Dec 2007 | A1 |
| 20080005587 | Ahlquist | Jan 2008 | A1 |
| 20080077825 | Bello et al. | Mar 2008 | A1 |
| 20080162674 | Dahiya | Jul 2008 | A1 |
| 20080195833 | Park | Aug 2008 | A1 |
| 20080270678 | Cornwell et al. | Oct 2008 | A1 |
| 20080282045 | Biswas et al. | Nov 2008 | A1 |
| 20090077340 | Johnson et al. | Mar 2009 | A1 |
| 20090100115 | Park et al. | Apr 2009 | A1 |
| 20090198889 | Ito et al. | Aug 2009 | A1 |
| 20100042643 | Pattabhi | Feb 2010 | A1 |
| 20100052625 | Cagno et al. | Mar 2010 | A1 |
| 20100211723 | Mukaida | Aug 2010 | A1 |
| 20100246266 | Park et al. | Sep 2010 | A1 |
| 20100257142 | Murphy et al. | Oct 2010 | A1 |
| 20100262764 | Liu et al. | Oct 2010 | A1 |
| 20100325345 | Ohno et al. | Dec 2010 | A1 |
| 20100332754 | Lai et al. | Dec 2010 | A1 |
| 20110072290 | Davis et al. | Mar 2011 | A1 |
| 20110125955 | Chen | May 2011 | A1 |
| 20110131231 | Haas et al. | Jun 2011 | A1 |
| 20110167221 | Pangal et al. | Jul 2011 | A1 |
| 20120023144 | Rub | Jan 2012 | A1 |
| 20120054264 | Haugh et al. | Mar 2012 | A1 |
| 20120079318 | Colgrove et al. | Mar 2012 | A1 |
| 20120131253 | McKnight et al. | May 2012 | A1 |
| 20120303919 | Hu et al. | Nov 2012 | A1 |
| 20120311000 | Post et al. | Dec 2012 | A1 |
| 20130007845 | Chang et al. | Jan 2013 | A1 |
| 20130031414 | Dhuse et al. | Jan 2013 | A1 |
| 20130036272 | Nelson | Feb 2013 | A1 |
| 20130071087 | Motiwala et al. | Mar 2013 | A1 |
| 20130145447 | Maron | Jun 2013 | A1 |
| 20130191555 | Liu | Jul 2013 | A1 |
| 20130198459 | Joshi et al. | Aug 2013 | A1 |
| 20130205173 | Yoneda | Aug 2013 | A1 |
| 20130219164 | Hamid | Aug 2013 | A1 |
| 20130227201 | Talagala et al. | Aug 2013 | A1 |
| 20130290607 | Chang et al. | Oct 2013 | A1 |
| 20130311434 | Jones | Nov 2013 | A1 |
| 20130318297 | Jibbe et al. | Nov 2013 | A1 |
| 20130332614 | Brunk et al. | Dec 2013 | A1 |
| 20140020083 | Fetik | Jan 2014 | A1 |
| 20140074850 | Noel et al. | Mar 2014 | A1 |
| 20140082715 | Grajek et al. | Mar 2014 | A1 |
| 20140086146 | Kim et al. | Mar 2014 | A1 |
| 20140090009 | Li et al. | Mar 2014 | A1 |
| 20140096220 | Da Cruz Pinto et al. | Apr 2014 | A1 |
| 20140101434 | Senthurpandi et al. | Apr 2014 | A1 |
| 20140164774 | Nord et al. | Jun 2014 | A1 |
| 20140173232 | Reohr et al. | Jun 2014 | A1 |
| 20140195636 | Karve et al. | Jul 2014 | A1 |
| 20140201512 | Seethaler et al. | Jul 2014 | A1 |
| 20140201541 | Paul et al. | Jul 2014 | A1 |
| 20140208155 | Pan | Jul 2014 | A1 |
| 20140215590 | Brand | Jul 2014 | A1 |
| 20140229654 | Goss et al. | Aug 2014 | A1 |
| 20140230017 | Saib | Aug 2014 | A1 |
| 20140258526 | Le Sant et al. | Sep 2014 | A1 |
| 20140282983 | Ju et al. | Sep 2014 | A1 |
| 20140285917 | Cudak et al. | Sep 2014 | A1 |
| 20140325262 | Cooper et al. | Oct 2014 | A1 |
| 20140351627 | Best et al. | Nov 2014 | A1 |
| 20140373104 | Gaddam et al. | Dec 2014 | A1 |
| 20140373126 | Hussain et al. | Dec 2014 | A1 |
| 20150026387 | Sheredy et al. | Jan 2015 | A1 |
| 20150074463 | Jacoby et al. | Mar 2015 | A1 |
| 20150089569 | Sondhi et al. | Mar 2015 | A1 |
| 20150095515 | Krithivas et al. | Apr 2015 | A1 |
| 20150113203 | Dancho et al. | Apr 2015 | A1 |
| 20150121137 | McKnight et al. | Apr 2015 | A1 |
| 20150134920 | Anderson et al. | May 2015 | A1 |
| 20150149822 | Coronado et al. | May 2015 | A1 |
| 20150193169 | Sundaram et al. | Jul 2015 | A1 |
| 20150378888 | Zhang et al. | Dec 2015 | A1 |
| 20160098323 | Mutha et al. | Apr 2016 | A1 |
| 20160350009 | Cerreta et al. | Dec 2016 | A1 |
| 20160352720 | Hu et al. | Dec 2016 | A1 |
| 20160352830 | Borowiec et al. | Dec 2016 | A1 |
| 20160352834 | Borowiec et al. | Dec 2016 | A1 |
| 20170171246 | Arumugam | Jun 2017 | A1 |
| Number | Date | Country |
|---|---|---|
| 0725324 | Aug 1996 | EP |
| WO-2012087648 | Jun 2012 | WO |
| WO2013071087 | May 2013 | WO |
| WO-2014110137 | Jul 2014 | WO |
| WO-2016015008 | Dec 2016 | WO |
| WO-2016190938 | Dec 2016 | WO |
| WO-2016195759 | Dec 2016 | WO |
| WO-2016195958 | Dec 2016 | WO |
| WO-2016195961 | Dec 2016 | WO |
| Entry |
|---|
| Wikipedia,“Snapshot (computer storage)”, Apr. 3, 2019, <https://en.wikipedia.org/wiki/Snapshot_(computer_storage)>. |
| Wikipedia, “State (computer science)”, Apr. 3, 2019, <https://en.wikipedia.org/wiki/State_(computer_science)>. |
| Kong, Using PCI Express as the Primary System Interconnect in Multiroot Compute, Storage, Communications and Embedded Systems, White Paper, IDT.com (online), Aug. 28, 2008, 12 pages, URL: www.idt.com/document/whp/idt-pcie-multi-root-white-paper. |
| Hu et al., Container Marking: Combining Data Placement, Garbage Collection and Wear Levelling for Flash, 19th Annual IEEE International Symposium on Modelling, Analysis, and Simulation of Computer and Telecommunications Systems, Jul. 25-27, 2011, 11 pages, ISBN: 978-0-7695-4430-4, DOI: 10.1109/MASCOTS.2011.50. |
| International Search Report and Written Opinion, PCT/US2016/036693, dated Aug. 29, 2016, 10 pages. |
| International Search Report and Written Opinion, PCT/US2016/038758, dated Oct. 7, 2016, 10 pages. |
| International Search Report and Written Opinion, PCT/US2016/040393, dated Sep. 22, 2016, 10 pages. |
| International Search Report and Written Opinion, PCT/US2016/044020, dated Sep. 30, 2016, 11 pages. |
| International Search Report and Written Opinion, PCT/US2016/044874, dated Oct. 7, 2016, 11 pages. |
| International Search Report and Written Opinion, PCT/US2016/044875, dated Oct. 5, 2016, 13 pages. |
| International Search Report and Written Opinion, PCT/US2016/044876, dated Oct. 21, 2016, 12 pages. |
| International Search Report and Written Opinion, PCT/US2016/044877, dated Sep. 29, 2016, 13 pages. |
| Paul Sweere, Creating Storage Class Persistent Memory with NVDIMM, Published in Aug. 2013, Flash Memory Summit 2013, <http://ww.flashmemorysummit.com/English/Collaterals/Proceedings/2013/20130814_T2_Sweere.pdf>, 22 pages. |
| PCMag. “Storage Array Definition”. Published May 10, 2013. <http://web.archive.org/web/20130510121646/http://www.pcmag.com/encyclopedia/term/52091/storage-array>, 2 pages. |
| Google Search of “storage array define” on Nov. 4, 2015 for U.S. Appl. No. 14/725,278, Results limited to entries dated before 2012, 1 page. |
| Techopedia. “What is a disk array”. Published Jan. 13, 2012. <http://web.archive.org/web/20120113053358/http://www.techopedia.com/definition/1009/disk-array>, 1 page. |
| Webopedia. “What is a disk array”. Published May 26, 2011. <http://web/archive.org/web/20110526081214/http://www.webopedia.com/TERM/D/disk_array.html>, 2 pages. |
| Li et al., Access Control for the Services Oriented Architecture, Proceedings of the 2007 ACM Workshop on Secure Web Services (SWS '07), Nov. 2007, pp. 9-17, ACM New York, NY. |
| The International Search Report and the Written Opinion received from the International Searching Authority (ISA/EPO) for International Application No. PCT/US2016/015006, dated Apr. 29, 2016, 12 pages. |
| The International Search Report and the Written Opinion received from the International Searching Authority (ISA/EPO) for International Application No. PCT/US2016/015008, dated May 4, 2016, 12 pages. |
| C. Hota et al., Capability-based Cryptographic Data Access Control in Cloud Computing, Int. J. Advanced Networking and Applications, col. 1, Issue 1, dated Aug. 2011, 10 pages. |
| The International Search Report and the Written Opinion received from the International Searching Authority (ISA/EPO) for International Application No. PCT/US2016/020410, dated Jul. 8, 2016, 17 pages. |
| The International Search Report and the Written Opinion received from the International Searching Authority (ISA/EPO) for International Application No. PCT/US2016/032084, dated Jul. 18, 2016, 12 pages. |
| Faith, “dictzip file format”, GitHub.com (online). [Accessed Jul. 28, 2015], 1 page, URL: https://github.com/fidlej/idzip. |
| Wikipedia, “Convergent Encryption”, Wikipedia.org (online), accessed Sep. 8, 2015, 2 pages, URL: en.wikipedia.org/wiki/Convergent_encryption. |
| Storer et al., “Secure Data Deduplication”, Proceedings of the 4th ACM International Workshop on Storage Security and Survivability (StorageSS'08), Oct. 2008, 10 pages, ACM New York, NY. USA. DOI: 10.1145/1456469.1456471. |
| The International Search Report and the Written Opinion received from the International Searching Authority (ISA/EPO) for International Application No. PCT/US2016/016333, dated Jun. 8, 2016, 12 pages. |
| ETSI, Network Function Virtualisation (NFV); Resiliency Requirements, ETSI GS NFCV-REL 001, V1.1.1, http://www.etsi.org/deliver/etsi_gs/NFV-REL/001_099/001/01.01.01_60/gs_NFV-REL001v010101p.pdf (online), dated Jan. 2015, 82 pages. |
| The International Search Report and the Written Opinion received from the International Searching Authority (ISA/EPO) for International Application No. PCT/US2016/032052, dated Aug. 30, 2016, 17 pages. |
| Microsoft, “Hybrid for SharePoint Server 2013—Security Reference Architecture”, <http://hybrid.office.com/img/Security_Reference_Architecture.pdf> (online), dated Oct. 2014, 53 pages. |
| Microsoft, “Hybrid Identity”, <http://aka.ms/HybridIdentityWp> (online), dated Apr. 2014, 36 pages. |
| Microsoft, “Hybrid Identity Management”, <http://download.microsoft.com/download/E/A/E/EAE57CD1-A80B-423C-96BB-142FAAC630139/Hybrid_Identity_Datasheet.pdf> (online), published Apr. 2014, 17 pages. |
| Jacob Bellamy-McIntyre et al., “OpenID and the Enterprise: A Model-based Analysis of Single Sign-On Authentication”, 2011 15th IEEE International Enterprise Distributed Object Computing Conference (EDOC), DOI: 10.1109/EDOC.2011.26, ISBN: 978-1-4577-0362-1, <https://www.cs.auckland.ac.nz/˜lutteroth/publications/McIntyreLutterothWeber2011-OpenID.pdf> (online), dated Aug. 29, 2011, 10 pages. |
| The International Search Report and the Written Opinion received from the International Searching Authority (ISA/EPO) for International Application No. PCT/US2016/035492, dated Aug. 17, 2016, 10 pages. |
