Abstract: A storage controller for a storage area network that implements input-output commands in hardware is provided. Specific input-output commands are defined, including: a READ command, a WRITE command, a COPY command and a WRITE MIRROR command, all of which are implemented in hardware. A virtual logical unit table can be provided that enables the storage controller to implement a virtual storage management overlay function on top of a raw physical storage function.

Abstract: A storage controller for a storage area network that implements input-output commands in hardware is provided. Specific input-output commands are defined, including: a READ command, a WRITE command, a COPY command and a WRITE MIRROR command, all of which are implemented in hardware. A virtual logical unit table can be provided that enables the storage controller to implement a virtual storage management overlay function on top of a raw physical storage function.

Abstract: A decentralised computer storage network is described comprising a plurality of hypervisors or nodes HV1, HV2, HVn. Each storage region in a node is controlled by an associated software controller 11, 12. Each node is configured to prepare a compressed metadata file detailing a snapshot of the data stored in its storage drive. The nodes can broadcast their metadata files so that they can be received by other nodes in the network. This allows each node to be aware of the data stored in the other nodes. By maintaining a local record of metadata files received over the network, each storage node can establish a live picture of the data stored in other storage nodes. This can permit any individual storage node to take decisions that control the distribution of data in the network.

Abstract: A decentralised computer storage network is described comprising a plurality of hypervisors or nodes HV1, HV2, HVn. Each storage region in a node is controlled by an associated software controller 11, 12. Each node is configured to prepare a compressed metadata file detailing a snapshot of the data stored in its storage drive. The nodes can broadcast their metadata files so that they can be received by other nodes in the network. This allows each node to be aware of the data stored in the other nodes. By maintaining a local record of metadata files received over the network, each storage node can establish a live picture of the data stored in other storage nodes. This can permit any individual storage node to take decisions that control the distribution of data in the network.

Abstract: Efficient reconciliation of different versions of a target file or dataset can be facilitated using a hash hierarchy of a master version of the dataset. Each level of the hash hierarchy has hashes of blocks of the master version that may be sub-blocks of the hashes in the level above. The top level of the hash hierarchy, having the hashes of the largest blocks of the master, may be transmitted on a first communication channel, possibly a one-way or broadcast communication channel. Streams of encodings of each lower level of the hash hierarchy may be transmitted on respective communication channels. The encodings for a level of the hierarchy may be combinations, such as random linear combinations, of the hashes of that level. A receiver with a target dataset can receive the top level hashes from the first channel and use them to determine which lower hashes are needed to identify parts of the master missing from the target.

Abstract: Efficient reconciliation of different versions of a target file or dataset can be facilitated using a hash hierarchy of a master version of the dataset. Each level of the hash hierarchy has hashes of blocks of the master version that may be sub-blocks of the hashes in the level above. The top level of the hash hierarchy, having the hashes of the largest blocks of the master, may be transmitted on a first communication channel, possibly a one-way or broadcast communication channel. Streams of encodings of each lower level of the hash hierarchy may be transmitted on respective communication channels. The encodings for a level of the hierarchy may be combinations, such as random linear combinations, of the hashes of that level. A receiver with a target dataset can receive the top level hashes from the first channel and use them to determine which lower hashes are needed to identify parts of the master missing from the target.

Abstract: Efficient reconciliation of different versions of a target file or dataset can be facilitated using a hash hierarchy of a master version of the dataset. Each level of the hash hierarchy has hashes of blocks of the master version that may be sub-blocks of the hashes in the level above. The top level of the hash hierarchy, having the hashes of the largest blocks of the master, may be transmitted on a first communication channel, possibly a one-way or broadcast communication channel. Streams of encodings of each lower level of the hash hierarchy may be transmitted on respective communication channels. The encodings for a level of the hierarchy may be combinations, such as random linear combinations, of the hashes of that level. A receiver with a target dataset can receive the top level hashes from the first channel and use them to determine which lower hashes are needed to identify parts of the master missing from the target.

Abstract: Efficient reconciliation of different versions of a target file or dataset can be facilitated using a hash hierarchy of a master version of the dataset. Each level of the hash hierarchy has hashes of blocks of the master version that may be sub-blocks of the hashes in the level above. The top level of the hash hierarchy, having the hashes of the largest blocks of the master, may be transmitted on a first communication channel, possibly a one-way or broadcast communication channel. Streams of encodings of each lower level of the hash hierarchy may be transmitted on respective communication channels. The encodings for a level of the hierarchy may be combinations, such as random linear combinations, of the hashes of that level. A receiver with a target dataset can receive the top level hashes from the first channel and use them to determine which lower hashes are needed to identify parts of the master missing from the target.