Maximizing Computational Profit in Grid Resource Allocation Using Dynamic Algorithm

kuppani sathish; K.Sathish

Maximizing Computational Profit in Grid Resource Allocation Using Dynamic Algorithm

Sathish Kuppani * §

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K.Sathish §

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§ Srivenkateswara University,Tirupati

Maximizing Computational Profit in Grid Resource Allocation Using Dynamic Algorithm

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Abstract

Grid computing, one of the most trendy phrase used in IT, is emerging vastly distributed computational paradigm. A computational grid provides a collaborative environment of the hefty number of resources capable to do high computing performance to reach the common goal. Grid computing can be called as super virtual computer, it ensemble large scale geographically distributed hetero-geneous resources. Resource allocation is a key element in the grid computing and grid resource may leave at anytime from grid environment. Despite a number of benefits in grid computing, still resource allocation is a challenging task in the grid. This work investigates to maximize the profits by analyzing how the tasks are allocated to grid resources effectively according to quality of service parameter and gratifying user requisition. A fusion of SS-GA algorithm has introduced to answer the above raised question about the resource allocation problem based on grid user requisition. The swift uses genetic algorithms heuristic functions and makes an effective resource allocation process in grid environment. The result of proposed fusion of SS-GA algorithm ameliorates the grid resource allocation.

References

18 Cites in Article

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Funding

No external funding was declared for this work.

Conflict of Interest

The authors declare no conflict of interest.

Ethical Approval

No ethics committee approval was required for this article type.

Data Availability

Not applicable for this article.

How to Cite This Article

kuppani sathish, K.Sathish. 2013. "Maximizing Computational Profit in Grid Resource Allocation Using Dynamic Algorithm". Global Journal of Computer Science and Technology - B: Cloud & Distributed GJCST-B Volume 13 (GJCST Volume 13 Issue B2).

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GJCST Volume 13 Issue B2

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Journal Specifications

Crossref Journal DOI 10.17406/gjcst

Print ISSN 0975-4350

e-ISSN 0975-4172

Keywords

fusion of SS-GA genetic algorithm (GA)grid computing heterogeneous resources QoS parameter resource allocation swift scheduler (SS)

Classification

GJCST-B Classification C.1.4

Submission ReceivedApril 5, 2013
Peer Review Double Blind
Handling Editor
Accepted April 30, 2013
Published June 22, 2013

Version of record

v1.2

Issue date

June 22, 2013

Language

English

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Article Matrices

Total Score: 107

Country: India

Subject: Global Journal of Computer Science and Technology - B: Cloud & Distributed

Authors: K.Sathish, Dr.A. Rama Mohan Reddy (PhD/Dr. count: 1)

View Count (all-time): 552

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Publish Date: 2013 05, Wed

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Total Views: 2.4K

Total Downloads: 119

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