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Job Scheduling in Grids with QoS Satisfaction using Ant Colony Optimization (ACO)

P. Devaki, Dr.M.L. Valarmathi

Abstract


Grid computing, a next leap in communication technology, a new trend in distributed computing systems, enables utilization of idle resources existing worldwide, to solve data intensive and computational intensive problems. These heterogeneous resources are shared from multiple administrative domains. The problem is divided into independent jobs and the jobs are executed by the resources available in grid. Scheduling these tasks to various resources in a grid is a very important problem and it is NP Complete. Hence we need a good job scheduling strategy to utilize the grids effectively such that overall completion time (makespan) is minimized. In literature, many heuristic scheduling approaches are available that give near optimal solution. In this paper we propose a weighted QoS (Quality of Service) factor enabled ant colony algorithm for scheduling independent jobs on heterogeneous grid resources. The main contribution of our work is to minimize the makespan (overall completion time) with QoS satisfaction and the results are compared with max-min and min-min algorithm

Keywords


Ant Colony, Grid Computing, Job Scheduling, Makespan, QoS

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References


Ruay-Shiung Chang, Jih Sheng Chang, Po-Sheng Lin, “An algorithm for balanced job scheduling in grids”, Future Generation Computer Systems 25(2009) 20-27.

Kobra Etminani, M. Naghibzadeh, “A Min-Min Max-Min Selective Algorithm for Grid Task Scheduling” , Internet 2007,ICI 2007,3rd IEEE/IFIP International Conference in Central Asia on, Sept. 2007.

T. Braun, H. Siegel, N. Beck, L. Boloni, M. Maheswaran, A. Reuther, J. Robertson, M. Theys, B. Yao, D. Hensgen, and R. Freund, “A comparison study of static mapping heuristics for a class of meta tasks on heterogeneous computing systems”, 8th IEEE Heterogeneous Computing Workshop (HCW’99), pages 15-29, April 1999.

J.G. Webster, “Heterogeneous Distributed Computing, ” Encyclopaedia of Electrical and Electronics Engineering, Vol. 8, pp. 679-690, 1999.

D. Feitelson, L. Rudolph, U. Schwiegelshohm, K. Sevcik and P. Wong, “Theory and Practice in Parallel Job Scheduling”, JSSPP, pp. 1-34, 1997.

Jamshid Bagherzadeh, Mojtaba Madadyar Adeh, “An Improved Ant Algorithm for Grid Scheduling Problem” , International CSI Computer Conference CSICC'09 pp. 323 – 328, 2009.

Bing Tang, Yingying Yin, Quan Liu and Zude Zhou, “Research on the Application of Ant Colony Algorithm in Grid Resource Scheduling”, Journal on Wireless Communications, Networking and Mobile Computing, 2008, Page(s):1 - 4.

Li Li, Wang Keqi, Zhou Chunnan, “An Improved Ant Colony Algorithm Combined with Particle Swarm Optimization Algorithm for Multi-objective Flexible Job Shop scheduling Problem” , International Conference on Machine Vision and Human-machine Interface 2010.

Ms. P. Devaki, Dr. M. L. Valarmathi, P.C. Harikarthik, “Weighted QoS Ant Colony Optimization Algorithm”, International Conference on Emerging Trends in Computing 2011.


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