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Static Workload Distribution of Parallel Applications in Heterogeneous Distributed Computing Systems with Memory and Communication Capacity Constraints

by Marwa Shouman, Gamal Attiya, Ibrahim Z. Morsi
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 34 - Number 6
Year of Publication: 2011
Authors: Marwa Shouman, Gamal Attiya, Ibrahim Z. Morsi
10.5120/4095-5977

Marwa Shouman, Gamal Attiya, Ibrahim Z. Morsi . Static Workload Distribution of Parallel Applications in Heterogeneous Distributed Computing Systems with Memory and Communication Capacity Constraints. International Journal of Computer Applications. 34, 6 ( November 2011), 18-24. DOI=10.5120/4095-5977

@article{ 10.5120/4095-5977,
author = { Marwa Shouman, Gamal Attiya, Ibrahim Z. Morsi },
title = { Static Workload Distribution of Parallel Applications in Heterogeneous Distributed Computing Systems with Memory and Communication Capacity Constraints },
journal = { International Journal of Computer Applications },
issue_date = { November 2011 },
volume = { 34 },
number = { 6 },
month = { November },
year = { 2011 },
issn = { 0975-8887 },
pages = { 18-24 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume34/number6/4095-5977/ },
doi = { 10.5120/4095-5977 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T20:20:23.322757+05:30
%A Marwa Shouman
%A Gamal Attiya
%A Ibrahim Z. Morsi
%T Static Workload Distribution of Parallel Applications in Heterogeneous Distributed Computing Systems with Memory and Communication Capacity Constraints
%J International Journal of Computer Applications
%@ 0975-8887
%V 34
%N 6
%P 18-24
%D 2011
%I Foundation of Computer Science (FCS), NY, USA
Abstract

This paper addresses the problem of static load balancing in heterogeneous distributed computing systems taking into account both memory and communication capacity constraints. The load balancing problem is first modeled as an optimization problem. Then, a heuristic approach, called Adaptive Genetic Algorithm (AGA), is proposed to solve the problem. The performance of the proposed algorithm is evaluated by simulation studies on randomly generated instances and the results are compared with that obtained by applying both the Genetic Algorithm (GA) and the Simulated Annealing (SA). Also, the qualities of the results are compared with the optimal solutions that obtained by applying the Brach-and-Bound (BB) algorithm.

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Index Terms

Computer Science
Information Sciences

Keywords

Load Balancing Simulated Annealing Genetic Algorithm Heuristics Mapping

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