HYBRIDIZATION OF MODIFIED ANT COLONY OPTIMIZATION AND INTELLIGENT WATER DROPS ALGORITHM FOR JOB SCHEDULING IN COMPUTATIONAL GRID

ICTACT Journal on Soft Computing ( Volume: 4 , Issue: 1 )

Abstract

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As grid is a heterogeneous environment, finding an optimal schedule for the job is always a complex task. In this paper, a hybridization technique using intelligent water drops and Ant colony optimization which are nature-inspired swarm intelligence approaches are used to find the best resource for the job. Intelligent water drops involves in finding out all matching resources for the job requirements and the routing information (optimal path) to reach those resources. Ant Colony optimization chooses the best resource among all matching resources for the job. The objective of this approach is to converge to the optimal schedule faster, minimize the make span of the job, improve load balancing of resources and efficient utilization of available resources.

Authors

P. Mathiyalagan1, S. N. Sivanandam2, K. S. Saranya3
Sri Ramakrishna Engineering College, India 1, Karpagam College of Engineering, India 2, PSG College of Technology, India 3

Keywords

Grid Computing, Grid Scheduling, Ant Colony Optimization, Intelligent Water Drops, Pheromone

Published By
ICTACT
Published In
ICTACT Journal on Soft Computing
( Volume: 4 , Issue: 1 )
Date of Publication
October 2013
Pages
651-655

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