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Adaptive Dvisible Load Scheduling Strategies for Workstation Clusters with Unknown Network Resources

Ghose, Debasish and Kim, Hyoung Joong and Kim, Tae Hoon (2005) Adaptive Dvisible Load Scheduling Strategies for Workstation Clusters with Unknown Network Resources. In: IEEE Transactions on Parallel and Distributed Systems, 16 (10). pp. 897-907.


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Conventional divisible load scheduling algorithms attempt to achieve optimal partitioning of massive loads to be distributed among processors in a distributed computing system in the presence of communication delays in the network. However, these algorithms depend strongly upon the assumption of prior knowledge of network parameters and cannot handle variations or lack of information about these parameters. In this paper, we present an adaptive strategy that estimates network parameter values using a probing technique and uses them to obtain optimal load partitioning. Three algorithms, based on the same strategy, are presented in the paper, incorporating the ability to cope with unknown network parameters. Several illustrative numerical examples are given. Finally, we implement the adaptive algorithms on an actual network of processor nodes using MPI implementation and demonstrate the feasibility of the adaptive approach.

Item Type: Journal Article
Publication: IEEE Transactions on Parallel and Distributed Systems
Publisher: IEEE
Additional Information: ©1990 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.
Keywords: Scheduling and task partitioning;Divisible loads; Distributed applications;workstations;Multiprocessor systems
Department/Centre: Division of Mechanical Sciences > Aerospace Engineering(Formerly Aeronautical Engineering)
Date Deposited: 25 Aug 2008
Last Modified: 19 Sep 2010 04:21
URI: http://eprints.iisc.ac.in/id/eprint/4004

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