Abstract
The grid environment has the characteristics of distribution, dynamic and heterogeneous. How to schedule jobs is one of most important issues of computing grid. To address this problem, this paper presents a novel reputation-based ant algorithm in the computing grid scheduling. The reputation is a comprehensive measure and used to reflect the ability of compute node or network for a long-running stability. The reputation-based ant algorithm introduce reputation index both in tasks and resources to the local and global pheromone. Experimental results show that the reputation-based ant algorithm outperforms Round Robin, Min-Min, and reputation based Min-Min in makespan and system load balancing.
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References
He, X.S., Sun, X.H., Laszewski, G.V.: QoS Guided Min-min Heuristic for Grid Task Scheduling. Journal of Computer Science and Technology 18, 442–451 (2003)
Wu, Z.A., Luo, J.Z., Dong, F.: Measurement Model of Grid QoS and Multi-dimensional QoS Scheduling. In: Shen, W., Luo, J., Lin, Z., Barthès, J.-P.A., Hao, Q. (eds.) CSCWD. LNCS, vol. 4402, pp. 509–519. Springer, Heidelberg (2007)
Zhang, W.Z., Fang, B.X., et al.: A Trust-QoS Enhanced Grid Service Scheduling. Chinese Journal of Computers 7, 1157–1166 (2006)
Sonmez, O.O., Gursoy, A.: A Novel Economic-Based Scheduling Heuristic for Computational Grids. International Journal of High Performance Computing Applications 21(1), 21–29 (2007)
Kumar, S., Dutta, K., Mookerjee, V.: Maximizing Business Value by Optimal Assignment of Jobs to Resources in Grid Computing. European Journal of Operational Research 194, 856–872 (2009)
Vanderstera, D.C., Dimopoulosb, N.J., et al.: Resource Allocation on Computational Grids Using a Utility Model and the Knapsack Problem. Future Generation Computer Systems 25(1), 35–50 (2009)
Wu, Z.A., Luo, J.Z., Song, A.B.: QoS-Based Grid Resource Management. Journal of Software 17(11), 2264–2276 (2006)
Dorigo, M., Maniezzo, V., Colorni, A.: The Ant System: Optimization by a Colony of Cooperating Agents. IEEE Transactions on Systems, Man, and Cybernetics-Part B 26(1), 29–41 (1996)
Xu, Z., Hou, X., Sun, J.: Ant Algorithm-Based Task Scheduling in Grid Computing. In: Canadian Conference on Electrical and Computer Engineering, IEEE CCECE (2003)
Chang, R.S., Changa, J.S., Lina, P.S.: An Ant Algorithm for Balanced Job Scheduling in Grids. Future Generation Computer Systems 25, 20–27 (2009)
Sathish, K., Reddy, A.R.M.: Enhanced Ant Algorithm Based Load Balanced Task Scheduling in Grid Computing. International Journal of Computer Science and Network Security 8(10), 219–223 (2008)
Kousalya, K., Balasubramanie, P.: Ant Algorithm for Grid Scheduling Powered by Local Search. International Journal of Open Problems Computational Mathematics 1, 223–240 (2008)
Casanova, H., Legrand, A., Quinson, M.: SimGrid: A Generic Framework for Large-Scale Distributed Experiments. In: Tenth International Conference on Computer Modeling and Simulation (uksim 2008) 126–131 (2008)
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Liu, F., Dong, X. (2012). Powered Grid Scheduling by Ant Algorithm. In: Huang, DS., Jiang, C., Bevilacqua, V., Figueroa, J.C. (eds) Intelligent Computing Technology. ICIC 2012. Lecture Notes in Computer Science, vol 7389. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-31588-6_75
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DOI: https://doi.org/10.1007/978-3-642-31588-6_75
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-31587-9
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