Maynooth University

Maynooth University ePrints and eTheses Archive

Maynooth University Library

Adaptive Scheduling Across a Distributed Computation Platform

Page, Andrew and Keane, Thomas and Naughton, Thomas J. (2004) Adaptive Scheduling Across a Distributed Computation Platform. Proceedings Third International Symposium on Parallel and Distributed Computing.

[img] Download (207kB)


A programmable Java distributed system, which adapts to available resources, has been developed to minimise the overall processing time of computationally intensive problems. The system exploits the free resources of a heterogeneous set of computers linked together by a network, communicating using SUN Microsystems' Remote Method Invocation and Java sockets. It uses a multi-tiered distributed system model, which in principal allows for a system of unbounded size. The system consists of an n-ary tree of nodes where the internal nodes perform the scheduling and the leaves do the processing. The scheduler nodes communicate in a peer-to-peer manner and the processing nodes operate in a strictly client-server manner with their respective scheduler. The independent schedulers on each tier of the tree dynamically allocate resources between problems based on the constantly changing characteristics of the underlying network. The system has been evaluated over a network of 86 PCs with a bioinformatics application and the travelling salesman optimisation problem.

Item Type: Article
Additional Information: Pages 141- 148
Keywords: Distributed computing, Java, Parallel computing, webcomputing, adaptive scheduling
Subjects: Science & Engineering > Electronic Engineering
Science & Engineering > Computer Science
Item ID: 182
Depositing User: Andrew Page
Date Deposited: 27 Jan 2005
Journal or Publication Title: Proceedings Third International Symposium on Parallel and Distributed Computing
Publisher: IEEE Computer Society
Refereed: No

    Repository Staff Only(login required)

    View Item Item control page

    Document Downloads

    More statistics for this item...