Emc Corporation

Vmware, Inc.

Emc IP Holding Company LLC

Datrium, Inc.

Other

Data Domain, Inc.

Springpath, Inc.

Datrium, Linc.

Sazzala Reddy

R Hugo Patterson, Iii

Umesh Maheshwari

Edward Kihyen Lee

R Hugo Patterson

Boris Weissman

Ganesh Venkitachalam

Dheer Moghe

Kai Yi Li

Ming Benjamin Zhu

Hua Zhong

Brian Biles

Sandip Agarwala

Shravan Gaonkar

Lakshmi Narayanan Bairavasundaram

Garrett Cale Smith

Krishna Yadappanavar

Faraz Ahmed Shaikh

Vijayan Prabhakaran

Praveen Vegulla

Mallikarjunan Mahalingam

Smit Shah

Srikant Varadan

Abhishek Chaturvedi

Allan J Bricker

Richard Johnsson

Jeffrey Zabarsky

Jeffery Zabarsky

R Hugo Patterson Iii

Data in a storage system is deduplicated after receiving from at least one writing entity requests for a plurality of write operations for a corresponding plurality of data blocks in a storage object. The received blocks are buffered and sorted in order and a sequence of clumps is created from the buffered blocks, where each clump comprises a grouping of at least one of the sorted, buffered blocks. A boundary is determined between at least one pair of clumps based at least in part on the content of at least one of the buffered blocks, and it is then determined whether at least one of the clumps is a duplicate of a previously stored clump.

System and methods for storage data deduplication

Techniques for replicating virtual machine data is provided. A plurality of compute nodes running on a primary cluster determine the amount of virtual machine data cached within each compute node. Based on the amount of virtual machine data for a particular virtual machine, a particular compute node is assigned to replicate the data to a secondary cluster. The amount of particular virtual machine data copied to the secondary cluster is based on updated virtual machine data that belongs to a particular state of the virtual machine. The destination of the particular virtual machine data is based on available cache space and prior replication statistics for target compute nodes on the secondary cluster.

Elastic replication of virtual machines

Techniques for scheduling replication events may be based upon establishing a plurality of policy groups. Each policy group has a replication schedule that defines when to initiate replication events and a membership selection pattern used to determine which virtual machines belong to which policy group. The policy groups may contain a first policy group and a second policy group, where each policy group has a unique replication schedule and a unique selection pattern. The system may assign a first set of virtual machines to the first policy group based upon the first selection pattern. A second set of virtual machines may be assigned to a second policy group based upon the second selection pattern. Each of the virtual machines in the first policy group may be assigned a first replication schedule and each of the virtual machines in the second policy group may be assigned a second replication schedule.

Snapshot for grouping and elastic replication of virtual machines

A data storage system includes a plurality of hosts, each of which includes at least one processor and communicates over a network with a plurality of storage nodes, at least one of which has at least one storage device, at least one storage controller, and at least one non-volatile memory. At least one process within a host issues data storage read/write requests. At least one of the hosts has a cache for caching data stored in at least one of the plurality of storage nodes. The host writes data corresponding to a write request to at least one remote non-volatile memory and carries out at least one storage processing function; data in the written-to node may then be made available for subsequent reading by a different one of the hosts. Examples of the storage processing function include compression, ECC computation, deduplicating, garbage collection, write logging, reconstruction, rebalancing, and scrubbing.

Data storage with a distributed virtual array

Exemplary methods, apparatuses, and systems maintain a plurality of summary data structures corresponding to a plurality of logical file system namespaces representing a plurality of hierarchies of one or more directories having one or more files, each file being stored in the storage system as a plurality of segments in a deduplicated manner. In response to a request to estimate a storage usage by a first of the file system namespace, identify a first of the summary data structures corresponding to the first file system namespace, wherein the first summary data structure stores information summarizing deduplicated segments referenced by one or more files of the first file system namespace. Estimate the storage usage of the first file system namespace based on the first summary data structure and a global summary data structure, wherein the global summary data structure stores information summarizing deduplicated segments referenced by all of the file system namespaces.

System and method for determining physical storage space of a deduplicated storage system

Cluster storage comprises an interface and a processor. The interface is to send a tag to a selected node and receive tags from the selected node. The tags received from the selected node comprise tags for likely similar segments stored on the selected node. The processor is to break a segment into subsegments, calculate subsegment tags for each subsegment, identify one or more references to one or more previously stored subsegments and/or one or more segment data using the tags from the selected node and the subsegment tags, and send the one or more references to the one or more previously stored subsegments and/or segment data and associated tags to the selected node.

Cluster storage using subsegmenting for efficient storage

A data storage system includes a plurality of hosts, each of which includes at least one processor and communicates over a network with a plurality of storage nodes, at least one of which has at least one storage device, at least one storage controller, and at least one non-volatile memory. At least one process within a host issues data storage read/write requests. At least one of the hosts has a cache for caching data stored in at least one of the storage nodes. The host writes data corresponding to a write request to at least one remote non-volatile memory and carries out at least one storage processing function; data in the written-to node may then be made available for subsequent reading by a different one of the hosts. Examples of the storage processing function include compression, ECC computation, deduplicating, garbage collection, write logging, reconstruction, rebalancing, and scrubbing.

Embodiments of a distributed virtual array data storage system and method are disclosed. Storage nodes made up of relatively unsophisticated disks with associated processors are scalable to store very large amounts of data. The storage nodes communicate with servers directly over a network through, for example, an Ethernet connection. Control of the storage nodes and access to the storage nodes is handled entirely on the server side of the system by distributed virtual array (DVA) software running on the server side and employing a particular protocol over the standard network connection. In an embodiment, server-side virtual machine (VM) hosts host application VMs that are associated with vDisks. The DVA software distributes data for the vDisk over the storage nodes. In the case of failure of one or more of the storage nodes, the DVA software reconstructs the data, for example by reading redundant data from surviving storage nodes.

Distributed virtual array data storage system and method

A distributed storage system that dispatches an input/output request is described. In an exemplary embodiment, a storage controller client receives the input/output request, wherein the distributed storage system includes the storage controller client, a plurality of storage controller servers, a plurality of virtual nodes distributed among a plurality of physical nodes, and each of the plurality of physical nodes is hosted on one of the plurality of storage controller servers. The storage controller client further computes a target virtual node for the input/output request, where the target virtual node is one of the plurality of virtual nodes. Using the computed target virtual node, the storage controller client determines a target physical node that corresponds to the target virtual node, where the target physical node is one of the plurality of physical nodes. In addition, the storage controller client dispatches the input/output request to a target storage controller that corresponds to the target physical node, wherein the target storage controller server is one of the plurality of storage controller servers. In addition, the virtual node includes a set of one or more mirrored copies across different fault domains for ensuring resiliency and high availability.

Systems and methods for implementing an enterprise-class converged compute-network-storage appliance

Cluster storage is disclosed. A data stream or a data block is received. The data stream or the data block is broken into segments. For each segment, a cluster node is selected, and a portion of the segment smaller than the segment is identified that is a duplicate of a portion of a segment already managed by the cluster node.

Data replication is disclosed. Originator data subsets are redistributed among a plurality of originator nodes from an initial distribution arrangement to a new distribution arrangement. Data redistribution information is determined. The redistribution information includes identification information of the originator data subsets, identification information of originator nodes comprising the initial distribution arrangement, and identification information of originator nodes comprising the new distribution arrangement. The redistribution information is sent to a replica system comprising a plurality of replica nodes. The redistribution information is used by the replica system to redistribute corresponding replica data subsets among a plurality of replica nodes from a previously replicated arrangement to a new replicated arrangement.

Data redistribution in data replication systems

Data replication comprises: redistributing one or more originator data subsets among a plurality of originator nodes; determining data redistribution information pertaining to redistribution of the one or more originator data subsets among the plurality of originator nodes; and sending data redistribution information to a replica system. The data redistribution information is used by the replica system to redistribute one or more corresponding replica data subsets among a plurality of replica nodes; and the one or more corresponding replica data subsets are redistributed among the plurality of replica nodes without requiring the one or more originator data subsets to be sent to the replica system during redistribution.

Growing community of inventors

Los Altos, CA, United States of America

Sazzala Reddy