Abstract: Embodiments relate to policy-based, multi-scheme data reduction for a computer memory. An aspect includes receiving a plurality of policy rules by a policy engine of the computer memory, wherein a first policy rule specifies applying a first data reduction scheme to data in the computer memory based on the data matching first characteristics, wherein a second policy rule specifies applying a second data reduction scheme to data in the computer memory based on the data matching second characteristics, wherein the first data reduction scheme is different from the second data reduction scheme. Another aspect includes determining, by the policy engine, that first data in the computer memory matches the first characteristics, and that second data in the computer memory matches the second characteristics. Yet another aspect includes applying the first data reduction scheme to the first data, and applying the second data reduction scheme to the second data.

Abstract: Embodiments relate to policy-based, multi-scheme data reduction for a computer memory. An aspect includes receiving a plurality of policy rules by a policy engine of the computer memory, wherein a first policy rule specifies applying a first data reduction scheme to data in the computer memory based on the data matching first characteristics, wherein a second policy rule specifies applying a second data reduction scheme to data in the computer memory based on the data matching second characteristics, wherein the first data reduction scheme is different from the second data reduction scheme. Another aspect includes determining, by the policy engine, that first data in the computer memory matches the first characteristics, and that second data in the computer memory matches the second characteristics. Yet another aspect includes applying the first data reduction scheme to the first data, and applying the second data reduction scheme to the second data.

Abstract: Embodiments relate to policy-based, multi-scheme data reduction for a computer memory. An aspect includes receiving a plurality of policy rules by a policy engine of the computer memory, wherein a first policy rule specifies applying a first data reduction scheme to data in the computer memory based on the data matching first characteristics, wherein a second policy rule specifies applying a second data reduction scheme to data in the computer memory based on the data matching second characteristics, wherein the first data reduction scheme is different from the second data reduction scheme. Another aspect includes determining, by the policy engine, that first data in the computer memory matches the first characteristics, and that second data in the computer memory matches the second characteristics. Yet another aspect includes applying the first data reduction scheme to the first data, and applying the second data reduction scheme to the second data.

Abstract: A method for early compression related processing in a file system with offline compression. The method includes receiving a data file in a buffer. A processor detects that at least a portion of a data block of the data file resides in the buffer. A compressibility indication of the data block is determined based on performing at least one compressibility analysis operation on the data block. The compressibility indication of the data block is stored. A background compression task is performed on the data block based on: determining a compression decision for the data block based on the compressibility indication, and compressing the data block based on the compression decision.

Abstract: Embodiments relate to policy-based, multi-scheme data reduction for a computer memory. An aspect includes receiving a plurality of policy rules by a policy engine of the computer memory, wherein a first policy rule specifies applying a first data reduction scheme to data in the computer memory based on the data matching first characteristics, wherein a second policy rule specifies applying a second data reduction scheme to data in the computer memory based on the data matching second characteristics, wherein the first data reduction scheme is different from the second data reduction scheme. Another aspect includes determining, by the policy engine, that first data in the computer memory matches the first characteristics, and that second data in the computer memory matches the second characteristics. Yet another aspect includes applying the first data reduction scheme to the first data, and applying the second data reduction scheme to the second data.

Abstract: A system and method is disclosed for maintaining, in a Storage Area Network (SAN), the consistency of a local copy of a remote file system sub-tree obtained from a remote source. Directory structure of the remote file system sub-tree is mapped to a remote container attached to the SAN and each remote object of the remote file system sub-tree is represented as a local object component of the remote container. Next, each of the local objects are labeled with attributes associated with the represented remote object, and metadata describing each of the local objects is stored in a metadata server. Also, a consistency policy is associated with each of the local objects in the remote container (wherein the policy defines conditions for checking freshness of said labeled attributes), and the local object components of remote container is updated in accordance with the consistency policy.

Abstract: Network latencies are reduced by detecting a metadata access call for filesystem metadata contained in a filesystem node of remotely located filesystem. The metadata corresponding to the metadata access call is fetched when the metadata corresponding to the metadata access call is not contained in a local filesystem cache that has a hierarchical structure corresponding to a hierarchical structure of the remotely located filesystem. Metadata related to the metadata corresponding to the metadata access call from the remotely located filesystem is prefetched when the related metadata is not contained in the local filesystem cache. The metadata related to the metadata corresponding to the access call can be contained in a child node or a parent node of the node containing the metadata corresponding to the access call, or the descendants of such nodes.

Abstract: Addressed is a system and method for remote data caching and replication by local copy maintenance of remote data within a SAN file system. Distributed Storage Tank (DST), an extension to a SAN file system, provides for transparent SAN client access of local copies by importing, exporting, and storing data using network file access protocols as well as by providing assurance of metadata and file content validity. A Remote Access Agent (RAA) handles protocol implementation and conversion necessary for communication with remote data sources. Controlled by a consistency policy, consistency is maintained by RAA fetching and updating local copies if modifications have occurred to a file since it was first stored as a local copy in local storage. Additionally, RAA returns metadata pertaining to the requested data. A SAN client obtains metadata corresponding to the requested data and utilizes it to directly access locally stored copies of remote data.