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Reseach Article

Implementing Job Scheduling to Optimize Computational Tasks in Grid Computing using PSO

Published on July 2015 by Surendra Kumar Patel, Anil Kumar Sharma, Anurag Seetha
National Conference on Knowledge, Innovation in Technology and Engineering (NCKITE 2015)
Foundation of Computer Science USA
NCKITE2015 - Number 3
July 2015
Authors: Surendra Kumar Patel, Anil Kumar Sharma, Anurag Seetha
09889a1a-dc61-489c-ba01-9fa8e564ca56

Surendra Kumar Patel, Anil Kumar Sharma, Anurag Seetha . Implementing Job Scheduling to Optimize Computational Tasks in Grid Computing using PSO. National Conference on Knowledge, Innovation in Technology and Engineering (NCKITE 2015). NCKITE2015, 3 (July 2015), 20-24.

@article{
author = { Surendra Kumar Patel, Anil Kumar Sharma, Anurag Seetha },
title = { Implementing Job Scheduling to Optimize Computational Tasks in Grid Computing using PSO },
journal = { National Conference on Knowledge, Innovation in Technology and Engineering (NCKITE 2015) },
issue_date = { July 2015 },
volume = { NCKITE2015 },
number = { 3 },
month = { July },
year = { 2015 },
issn = 0975-8887,
pages = { 20-24 },
numpages = 5,
url = { /proceedings/nckite2015/number3/21494-2665/ },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Proceeding Article
%1 National Conference on Knowledge, Innovation in Technology and Engineering (NCKITE 2015)
%A Surendra Kumar Patel
%A Anil Kumar Sharma
%A Anurag Seetha
%T Implementing Job Scheduling to Optimize Computational Tasks in Grid Computing using PSO
%J National Conference on Knowledge, Innovation in Technology and Engineering (NCKITE 2015)
%@ 0975-8887
%V NCKITE2015
%N 3
%P 20-24
%D 2015
%I International Journal of Computer Applications
Abstract

Grid computing is a recent advancement technology that enables resource sharing and dynamic allocation of computational resources, thus getting higher access to distributed data, promoting operational elasticity and collaboration. So, efficient resource management is one of the fundamental requirements in grid computing. Resource management is required in an environment where resources are quite limited and need to be utilised properly. Due to the complex and dynamic properties of grid environments, existing traditional model-based methods may result in poor scheduling performance. To overcome of such problem, we need to develop improved algorithm that reduces the computation time. This paper proposed PSO algorithm specifically focused on improving computational grid performance in terms of equal load balance for all jobs and total computation time, which enhance grid throughput, utilization, response time and more economic profits.

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Index Terms

Computer Science
Information Sciences

Keywords

Grid Computing Resource Sharing Job Scheduling Pso Algorithm