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Please use this identifier to cite or link to this item: http://hdl.handle.net/2005/50

Title: Adaptive Hierarchial RAID
Authors: Muppalaneni, Nitin
Advisors: Gopinath, K
Submitted Date: Jan-1998
Publisher: Indian Institute of Science
Abstract: Redundant Arrays of Inexpensive Disks or RAID is a popular method of improving the reliability and performance of disk storage. Of various levels of RAID, mirrored or RAID1 and rotating parity or RAID5 configurations have become moat popular. Mirrored or RAID1 provides best overall performance and is easier to configure, but has 100 percent storage overhead for the redundancy. Rotating parity or RAID5, on the other hand, is quite inexpensive for the redundancy it provides, shorn impressive performance for reads and full-stripe writes in normal mode, but the small write performance is poor due to the read-modify-write cycle involved. The performance drops drastically when one of the disks fails and the system enters degraded mode. Also RAID5 is relatively difficult to configure. Typical non-scientific system disk access patterns exhibit very high locality of reference. This thesis presents the design and implementation of an Adaptive Hierarchical RAID array to exploit this high locality. Frequently accessed data is migrated towards the top of the hierarchy and not so frequently acee88ed data is moved down the hierarchy, thus adaptively rearranging itself to the access patterns. Previous work on Adaptive Hierarchical RAID such as HP AutoRAID has explored one part of the design space, namely design of configurable storage at the SGSI level with no interaction with higher level layers like volume manager. This thesis explores a different design point: namely, one that is centered at the volume manager layer. This is important also for the reason that with fibre channel disks and SCSI-3, Storage Area Networks (SAN) no longer need a conventional controller but a modified version of a controller that is more close to a volume manager.
URI: http://hdl.handle.net/2005/50
Appears in Collections:Computer Science and Automation (csa)

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