Load balancing with Job Migration Algorithm for improving performance on grid computing: Experimental Results


Grid is the collection of geographically distributed computing resources. For efficient management of these resources, the manager must maximize its utilization, which can be achieved by efficient load balancing with Job Migration techniques.Job Migration from overloaded resources to underloaded is an attempt to load balancing across all processors, thus reduce average response time. The decision of migration is based on the information exchange between resources.In this paper, the authors propose a novel Job Migration Algorithm for Dynamic Load Balancing (JMADLB), in which parameters such as CPU load and queue length have been considered and have been used for the selection of overloaded resources (or underloaded ones) in Grid. Here, the overloaded resources do not accept any new job; but, the new jobs are migrated to underloaded resources, even though this mechanism migrate extra jobs to obtain load balancing. The performances of the proposed algorithms were tested in Alea 2 simulator by using different parameters like response time, resources utilization and waiting time in the global queue. In addition, they were compared with other scheduling algorithms such as First Come First Served (FCFS) and Earliest Deadline First (EDF).
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Buyya, R.and Murshed, M .(2002). Gridsim: a toolkit for the modeling and simulation of distributed resource management and scheduling for grid computing, The Journal of Concurrency and Computation: Practice and Experience (CCPE),Vol. 14, pp.13-15. - https://doi.org/10.1002/cpe.710

B. Yagoubi ,Y. Slimani.(2007, March). Load Balancing Strategy for Grid Computing. Journal of Information Technology and Applications ,Vol. 1 No.4, pp. 285-296.

B. Yagoubi, and M. Meddeber.( 2010). Distributed Load Balancing Model for Grid Computing, Revue ARIMA,Vol. 12,pp. 43-60.

Dalibor Klusá?ek and Hana Rudová.(2010). Alea 2 job scheduling simulator. In Proceedings of the 3rd International Conference on Simulation Tools and Techniques (SIMUTools 2010), Torremolinos, Malaga, Spain. - https://doi.org/10.4108/ICST.SIMUTOOLS2010.8722

Khanli, L.M., Razzaghzadeh, S. and Zargari, S.V., A new step toward load balancing based on competency rank and transitional phases in Grid networks,Journal of Grid Computing, 2008.

N. K. Rathore, I. Chana. (2016, March).Job Migration Policies for Grid Environment. Wireless Personal Communica-tion, Springer Publication-New-York (USA), volume: 89 (1), pp.241-269, IF -0.979. - https://doi.org/10.1007/s11277-016-3264-2

M. Mezmaz, N. Melab, and E.G. Talbi, An efficient load balancing strategy for Gridbased branch and bound algorithm, Parallel Computing, 2007. - https://doi.org/10.1016/j.parco.2007.02.004

M. Nandagopal, and R. V. Uthariaraj.( Feb. 2010 )"Hierarchical Status Information Exchange Scheduling Balancing For Computational Grid Environments," International Journal of Computer Science and Network Security, Vol. 10,No. 2, pp. 177-185.

R. U. Payli, K. Erciyes, and O. Dagdeviren.( 5, Sep. 2011). "cluster-based load balancing strategys for grids", International Journal of Computer Networks & Communications, Vol. 3, No, pp. 253-269. - https://doi.org/10.5121/ijcnc.2011.3518

R. J. Samuel, K.S. Hridya, and A. V. Vasudevan, Augmenting Hierarchical Load Balancing with Intelligence in Grid Environment,, International Journal of Grid and Distributed Computing, 2012.

S. Kumar, and N. Singhal. (Jul,2012).A Priority based Dynamic Load Balancing Approach in a Grid based Distributed Computing Network, International Journal of Computer Applications, Vol. 49, No.5, pp. 819-828. - https://doi.org/10.5120/7622-0677

S Khan,B Nazir, IA Khan, SShamshirband, AT Chronopoulos.( 20,feb.2017).Journal of Network and Computer Applications 88, 99-111

A. Touzene, S. Al-Yahai, H. AlMuqbali, A. Bouabdallah, and Y. Challa.(2011). "Performance Evaluation of Load Balancing in Hierarchical Architecture for Grid Computing Service Middleware," International Journal of Computer Science, Vol. 8, No.2, pp. 213-223.

Website: Dalibor Klusá?ek and Hana Rudová .Retrieved from http://www.fi.muni.cz/~xklusac/workload.
Wided, A., Okba, K., & Fatima, B. (2020). Load balancing with Job Migration Algorithm for improving performance on grid computing: Experimental Results. ADCAIJ: Advances in Distributed Computing and Artificial Intelligence Journal, 8(4), 5–18. https://doi.org/10.14201/ADCAIJ201984518


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Author Biographies

Ali Wided

Biskra University
computer science departement

Kazar Okba

University of Biskra
Computer Sciences Department 

Bouakkaz Fatima

Esi University
Computer Sciences Department