International Business Machines Corporation

Leo S Luan

Frank Bernhard Schmuck

Wayne A Sawdon

Marc Adam Kaplan

M Corneliu Constantinescu

Sven Oehme

Binny Sher Gill

Owen Theodore Anderson

Geoffrey Albert Riegel

Manuel Vasconcellos Pereira, Iii

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.

Policy-based, multi-scheme data reduction for computer memory

Embodiments relate to granular management of data storage blocks in a data storage system. In one aspect, status values are employed to track 'used', 'free', and &#x201c;claimed free&#x201d; storage blocks. A storage block having stored data is identified as used, a storage block available to store data is identified as free, and a storage block having previously stored data removed that has not been reclaimed is identified as claimed free. These values are maintained on a map to track each data block within the data storage system. One or more used blocks are de-allocated, which includes changing the status value of each used block to claimed free Available claimed free data blocks are prioritized for data block allocation over available free data blocks for efficient storage, including enabling efficient reclamation of data blocks and minimizing data movement needed for reclamation-oriented de-fragmentation.

Efficient allocation and reclamation of thin-provisioned storage

Embodiments of the inventions relate to granular management of data storage blocks in a data storage system. In one aspect, status values are employed to track 'used', 'free', and &#x201c;claimed free&#x201d; storage blocks. A storage block having stored data is identified as used, a storage block available to store data is identified as free, and a storage block having previously stored data removed that has not been reclaimed is identified as claimed free. These values are maintained on a map to track each data block within the data storage system. Available claimed free data blocks are prioritized for data block allocation over available free data blocks for efficient storage, including enabling efficient reclamation of data blocks and minimizing data movement needed for reclamation-oriented de-fragmentation.

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.

Growing community of inventors

Saratoga, CA, United States of America

Leo S Luan