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Number 3

A Novel Resource Scheduling Algorithm for Computational Grid

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  • Gunjan Aggarwal and Meenakshi Kamboj and Charanjit Singh and Preeti Sharma 2012. A Novel Resource Scheduling Algorithm for Computational Grid. International Journal of Applied Information Systems. 4, 3 (September 2012), 34-37. DOI=http://dx.doi.org/10.5120/ijais450668
  • @article{10.5120/ijais2017451568,
    author = {Gunjan Aggarwal and Meenakshi Kamboj and Charanjit Singh and Preeti Sharma},
    title = {A Novel Resource Scheduling Algorithm for Computational Grid},
    journal = {International Journal of Applied Information Systems},
    issue_date = {September 2012},
    volume = {4},
    number = {},
    month = {September},
    year = {2012},
    issn = {},
    pages = {34-37},
    numpages = {},
    url = {/archives/volume4/number3/284-0668},
    doi = { 10.5120/ijais12-450668},
    publisher = { xA9 2010 by IJAIS Journal},
    address = {}
    }
    
  • %1 450668
    %A Gunjan Aggarwal
    %A Meenakshi Kamboj
    %A Charanjit Singh
    %A Preeti Sharma
    %T A Novel Resource Scheduling Algorithm for Computational Grid
    %J International Journal of Applied Information Systems
    %@ 
    %V 4
    %N 
    %P 34-37
    %D 2012
    %I  xA9 2010 by IJAIS Journal
    

Abstract

Grid is an emerging technology for enabling resource sharing and coordinated problem solving in dynamic multi- institutional heterogeneous virtual organizations. However, the management of resources and computational tasks is a critical and complex undertaking as these resources and tasks are geographically distributed. A suitable and efficient scheduling algorithm is needed to schedule user tasks to heterogeneous resources distributed in the grid. We propose a genetic algorithm to solve the scheduling problems in computational grid. The proposed algorithm uses the optimal searching technique of genetic approach and takes different computing capabilities of nodes into consideration. The simulation result shows that proposed algorithm yields better performance when compared with other traditional heuristic approaches.

References

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Keywords

Grid Computing, Genetic Algorithm, Resource Scheduling

Index Terms

Computer Science
Information Sciences