vioft2nntf2t|tblJournal|Abstract_paper|0xf4ff8eba030000006a0f000001000600 Grid computing is a high performance computing used to solve larger scale computational demands. Task scheduling is a major issue in grid computing systems. Scheduling of tasks is the NP hard problem. The heuristic approach provides optimal solution for NP hard problems .The ant colony algorithm provides optimal solution. The existing ant colony algorithm takes more time to schedule the tasks. In this paper ant colony algorithm improved by enhancing pheromone updating rule such that it schedules the tasks efficiently and better resource utilization. The simulation results prove that proposed method reduces the execution time of tasks compared to existing ant colony algorithm.
P. Mathiyalagan1, U.R. Dhepthie2, S.N. Sivanandam3
P.S.G. College of Technology, Tamil Nadu, India1, P.S.G. College of Technology, Tamil Nadu, India2, Akshaya College of Engineering, Tamil Nadu, India
Pheromone, Swarm Intelligence, Inertia, Grid Scheduling
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| Published By :
ICTACT
Published In :
ICTACT Journal on Soft Computing
( Volume: 1 , Issue: 2 , Pages: 85 - 87 )
Date of Publication :
October 2010
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