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Performance Factor based Local Scheduling for Heterogeneous Grid Environments

by G.sumathi, S.sathyanarayanan, R.santhosh Kumar
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 44 - Number 22
Year of Publication: 2012
Authors: G.sumathi, S.sathyanarayanan, R.santhosh Kumar
10.5120/6415-8914

G.sumathi, S.sathyanarayanan, R.santhosh Kumar . Performance Factor based Local Scheduling for Heterogeneous Grid Environments. International Journal of Computer Applications. 44, 22 ( April 2012), 45-49. DOI=10.5120/6415-8914

@article{ 10.5120/6415-8914,
author = { G.sumathi, S.sathyanarayanan, R.santhosh Kumar },
title = { Performance Factor based Local Scheduling for Heterogeneous Grid Environments },
journal = { International Journal of Computer Applications },
issue_date = { April 2012 },
volume = { 44 },
number = { 22 },
month = { April },
year = { 2012 },
issn = { 0975-8887 },
pages = { 45-49 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume44/number22/6415-8914/ },
doi = { 10.5120/6415-8914 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T20:36:16.512855+05:30
%A G.sumathi
%A S.sathyanarayanan
%A R.santhosh Kumar
%T Performance Factor based Local Scheduling for Heterogeneous Grid Environments
%J International Journal of Computer Applications
%@ 0975-8887
%V 44
%N 22
%P 45-49
%D 2012
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Grids [3] have emerged as paradigms for the next generation parallel and distributed computing. Computational Grid can be defined as large-scale high-performance distributed computing environments that provide access to high-end computational resources. Grid scheduling is the process of scheduling jobs over grid resources. Improving overall system performance with a lower turnaround time is an important objective of Local Grid scheduling. In this paper a Performance Factor Based Local Scheduling Algorithm is proposed. In this algorithm priority for each subtask in the Grid is assigned based on two new parameters, Computational Complexity and Performance Factor. The algorithm classifies the subtasks into high, medium and low categories based on their priority. The value for performance factor is assigned based on the value of processing power of each node i. e. Number of operations per cycle per processor and the number of instructions processed per second. The subtasks are then mapped to respective processors based on the assigned priority for execution. A subtask, which requires a very high performance factor and that exhibits high computational complexity, is given a high priority. Prioritizing the subtasks in this way can improve the performance of grid resources that in turn improve the overall efficiency of the computational grid. The effectiveness of this algorithm is evaluated through simulation results.

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Index Terms

Computer Science
Information Sciences

Keywords

Global And Local Grid Resource Brokers (ggrb & Lgrb) grid Information Server (gis)

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