Abstract

Allocation of data to parallel disk using redundant storage and random placement of blocks can be exploited to achieve low access delays. New algorithms are proposed which improve the previously known shortest queue algorithm by systematically exploiting that scheduling decisions can be deferred until a block access is actually started on a disk. These algorithms are also generalized for coding schemes with low redundancy. Using extensive simulations, practically important quantities are measured which have so far eluded an analytical treatment: The delay distribution when a stream of requests approaches the limit of the sytem capacity, the system efficiency for parallel disk applications with bounded prefetching buffers, and the combination of both for mixed traffic. A further step towards practice is taken by outlining the system design for a: automatically load-balanced parallel hard-disk array. Additional algorithmic measures are proposed for a that allow variable sized blocks, seek time reduction, fault tolerance, inhomogeneous systems, and flexible priorization schemes.

Citations