Abstract
Load balancing has been known as one of the most challenging problems in computer sciences especially in the field of distributed systems and grid environments; hence, many different algorithms have been developed to solve this problem. Considering the revolution occurred in the modern processing units, using mutli-core processors can be an appropriate solution. one of the most important challenges in multi-core-based grids is scheduling. Specific computational intelligence methods are capable of dealing with complex problems for which there is no efficient classic method-based solution. One of these approaches is multi-objective genetic algorithm which can solve the problems in which multiple objectives are to be optimized at the same time. CoreIIScheduler, the proposed approach uses NSGA-II method which is successful in solving most of the multi-objective problems. Experimental results over lots of different grid environments show that the average utilization ratio is over 90% whilst for FCFS algorithm, it is only about 70%. Furthermore, CoreIIScheduler has an improvement ratio of 60% and 80% in wait time and makespan, respectively which is relative to FCFS.
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References
Zomaya, A.Y., Teh, Y.-H.: Observations on using genetic algorithms for dynamic load-balancing. IEEE Transactions on Parallel and Distributed Systems 12, 899–912 (2001)
Kwok, Y.K., Ahmad, I.: Dynamic Critical-Path Scheduling: An Effective Technique for Allocating Task Graphs to Multiprocessors. IEEE Trans. Parallel and Distributed Systems 7, 506–521 (1996)
Deb, K.: A fast and elitist multiobjective genetic algorithm: NSGA-II. IEEE Transactions on Evolutionary Computation 6, 182–197 (2002)
Cao, J., Spooner, D.P., Jarvis, S.A., Nudd, G.R.: Grid load balancing using intelligent agents. Future Generation Computer Systems 21, 135–149 (2005)
Li, Y., Yang, Y., Ma, M., Zhou, L.: A hybrid load balancing strategy of sequential tasks for grid computing environments. Future Generation Computer Systems 25, 819–828 (2009)
Singh, B., Bawa, S.: HybridSGSA: Sexual GA and Simulated Annealing based Hybrid Algorithm for Grid Scheduling. Global Journal of Computer Science and Technology 10, 78–81 (2010)
Abdulal, W., AlJadaan, O., Jabas, A., Ramchandraram, S.: Rank-based Genetic Algorithm with Limited Iteration for Grid Scheduling. In: First International Conference on Computational Intelligence, Communication Systems and Networks, India (2009)
Zhu, Y., Guo, X.: Grid Dependent Tasks Scheduling Based on Hybrid Adaptive Genetic Algorithm. In: Global Congress on Intelligent Systems (2009)
Grosan, C., Abraham, A., Helvik, B.: Multi-objective Evolutionary Algorithms for Scheduling Jobs on Computational Grids. In: International Conference on Applied Computing, Salamanca, Spain, pp. 459–463 (2007)
Talukder, A.K.M.K.A., Kirley, M., Buyya, R.: Multiobjective differential evolution for scheduling workflow applications on global Grids. Concurrency and Computation: Practice & Experience - Special Issue: Advanced Strategies in Grid Environments 21 (2009)
Ye, G., Rao, R., Li, M.: A Multiobjective Resources Scheduling Approach Based on Genetic Algorithms in Grid Environment. In: Fifth International Conference on Grid and Cooperative Computing Workshops (GCCW 2006), Hunan, China, pp. 504–509 (2006)
Gog, A., Dumitrescu, D., Hirsbrunner, B.: New Selection Operators based on Genetic Relatedness for Evolutionary Algorithms in Congress on Evolutionary Computation (2007)
Deb, K. (2009), Kanpur Genetic Algorithms Laboratory, http://www.iitk.ac.in/kangal/
Al-Sharaeh, S., Wells, B.E.: A Comparison of Heuristics for List Schedules using The Box-method and P-method for Random Digraph Generation. In: Proceedings of the 28th Southeastern Symposium on System Theory, pp. 467–471 (1996)
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Najm Abad, J.M., Shekofteh, S.K., Tabatabaee, H., Mehrnejad, M. (2013). CoreIIScheduler: Scheduling Tasks in a Multi-core-Based Grid Using NSGA-II Technique. In: Abraham, A., Thampi, S. (eds) Intelligent Informatics. Advances in Intelligent Systems and Computing, vol 182. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-32063-7_54
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DOI: https://doi.org/10.1007/978-3-642-32063-7_54
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