HYBRIDIZATION OF MODIFIED ANT COLONY OPTIMIZATION AND INTELLIGENT WATER DROPS ALGORITHM FOR JOB SCHEDULING IN COMPUTATIONAL GRID
Abstract
vioft2nntf2t|tblJournal|Abstract_paper|0xf4ffe65a130000004b59010001000300
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
Yearly Full Views
JanuaryFebruaryMarchAprilMayJuneJulyAugustSeptemberOctoberNovemberDecember
000000000000
Published By :
ICTACT
Published In :
ICTACT Journal on Soft Computing
( Volume: 4 , Issue: 1 , Pages: 651-655 )
Date of Publication :
October 2013
Page Views :
112
Full Text Views :

Creative Commons License
This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.