MULTIPROCESSOR SCHEDULING BY MEAN FIELD THEORY

Document Type

Conference Proceeding

Publication Date

1-1-1992

Abstract

In this paper, we develop an optimization scheme based on Mean Field Theory (MFT) to solve the Task Scheduling Problem. The algorithm combines characteristics of the Simulated Annealing (SA) algorithm and the Hopfield neural network. The temperature behavior of MFT for the task scheduling problem is shown to possess a critical temperature (Tc) below which an optimal solution may be achieved. The algorithm has been applied to various task graphs, and promising results have been obtained.

Identifier

85132251143 (Scopus)

ISBN

[0780305590]

Publication Title

Proceedings of the International Joint Conference on Neural Networks

External Full Text Location

https://doi.org/10.1109/IJCNN.1992.227256

First Page

582

Last Page

587

Volume

4

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