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Job Scheduling Using Coupling in Grid

DOI: 10.4236/jcc.2015.310001    1,747 Downloads   2,109 Views   Citations
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ABSTRACT

The grid computing main concern is to use the resources efficiently. For achieving this many grid resource scheduling algorithms are used for the efficient use of unused resources, especially CPU. The scheduling algorithms assign single complete job to a single resource. Instead, if these algorithms consider the degree of dependency among the modules of a job, they can be allocated parallel to the different resources. This reduces the completion time of the job and the resources can be utilized to its maximum extent. Towards this, the job scheduling using coupling algorithm is proposed. This algorithm puts forward the idea of considering the coupling degree while allocating the modules of a job parallel to different resources. In this algorithm, resource selection is done by using both its functional and non-functional properties. The algorithm works in 3 phases. It groups the interdependent modules of a job into different sets using coupling in the first phase. It checks the non-functional property i.e. availability of a resource using echo procedure in the second phase and in the third phase, the sets created in first phase, are allocated parallel to different available and matching resources. From the simulation results it is observed that job scheduling using coupling algorithm gives better performance in terms of reduced turnaround time as compared to First Come First Served, Largest Task First and Minimum Execution Time scheduling algorithms.

Cite this paper

Anitha, A. (2015) Job Scheduling Using Coupling in Grid. Journal of Computer and Communications, 3, 1-12. doi: 10.4236/jcc.2015.310001.

Conflicts of Interest

The authors declare no conflicts of interest.

References

[1] Kesselman, C., Foster, I. and Steven, T. (2001) The Anatomy of the Grid-Enabling Scalable Virtual Organizations. The International Journal of Super Computer Application, 15, 200-222.
http://dx.doi.org/10.1177/109434200101500302
[2] Andrew, R. and Krzysztof, P. (2004) Grid Computing: The Current State and Future Trends (in General). University of Canterbury, Christchurch, TR-CoSc 01/04.
[3] Paolucii, M., Kawamura, T., Payne, T. and Sycara, K. (2002) Semantic Matching of Web Service Capabilities. Proceedings of 1st International Semantic Web Conference (ISWC2002), Berlin.
[4] Zhang, Z.P., Wen, L.J. and Wang, Z.P. (2013) LoBa-Min-Min-SPA: Grid Resources Scheduling Algorithm Based on Load Balance Using SPA. The Open Automation and Control Systems Journal, 5, 87-95.
http://dx.doi.org/10.2174/1874444301305010087
[5] Anitha, A. (2015) Trust Management in Grid-Trust Assessment and Trust Degree Calculation of a Resource—A Novel Approach. Journal of Computers and Communications, Scientific Research Publications, 3, 34-41.
http://dx.doi.org/10.4236/jcc.2015.36005
[6] Ahmed, I., Kwok, Y.K., Wu, M.Y. and Li, K. (2004) Experimental Performance Evaluation of Job Scheduling and Processor Allocation Algorithms for Grid Computing on Metacomputers. Proceedings of the 18th International Symposium Parallel Distributed Processing, IEEE Xplore Press, 170-177.
[7] Daulamis, N.D., Daulamis, A.D., Varvarigos, E.A. and Varvarigou, T.A. (2007) Fair Scheduling Algorithms in Grid. IEEE Transactions on Parallel Distributed System, 18, 1630-1648.
http://dx.doi.org/10.1109/TPDS.2007.1053
[8] Yu, X.P. and Yu, X.G. (2009) A New Grid Computation-Based Min-Min Algorithm. 6th International Conference on Fuzzy Systems and Knowledge Discovery, Tianjin, 14-16 August 2009, 43-45.
http://dx.doi.org/10.1109/fskd.2009.81
[9] Ni, L.N., Zhang, J.Q., Yan, C.G. and Jiang, C.J. (2005) A Heuristic Algorithm for Task Scheduling Based on Mean Load. 1st International Conference on Semantics, Knowledge and Grid (SKG’05), Beijing, 27-29 November 2005.
http://dx.doi.org/10.1109/skg.2005.13
[10] Kamalam, G.K. and Muralibhaskaran, V. (2010) A New Heuristic Approach: Min-Mean Algorithm for Scheduling Metatasks on Heterogenous Computing Systems. International Journal of Computer Science and Network Security, 10.
[11] Menasce, D., Saha, D., Porto, S.C.D., Almeida, V.A.F. and Tripathi, S.K. (1995) Static and Dynamic Processor Scheduling Disciplines in Heterogenous Parallel Architectures. Journal of Parallel and Distributed Computing, 28, 1-18.
http://dx.doi.org/10.1006/jpdc.1995.1085
[12] Ramaparvathy, L. (2014) A New-Threshold Based Job Scheduling for Grid System. Journal of Computer Science, Science Publications, 10, 1069-1076.
http://dx.doi.org/10.3844/jcssp.2014.1069.1076
[13] Madhuri, B. and Pradhan, S.N. (2011) NGSched—An Efficient Scheduling Algorithm Handling Interactive Jobs in Grid Environment. International Journal of Grid and Distributed Computing, 4, 1.
[14] Ajith, A., Rajkumar, B. and Baikunth, N. (2000) Nature’s Heuristic for Scheduling Jobs on Computational Grids. Proceedings of 8th IEEE International Conference on Advanced Computing and Communications (ADCOM2000).
[15] Pinky, R., Ravinder, S., Payal, S. and Dilip, S. (2012) Group Based Job Scheduling Algorithm Using Priority Queue and Hybrid Algorithm in Grid Computing. International Journal of Grid Computing and Applications, 3, 55-64.
http://dx.doi.org/10.5121/ijgca.2012.3405
[16] Prajapathi, H.B. and Vipul, A.S. (2014) Scheduling in Grid Computing Environment. 4th International Conference on Advanced Computing & Communication Technologies (ACCT), Rohtak, 8-9 February 2014, 315-324.
http://dx.doi.org/10.1109/ACCT.2014.32
[17] Armstrong, R., Hensegen, D. and Kidd, T. (1998) The Relative Performance of Various Mapping Algorithms Is Independent of Sizable Variances in Run-Time Productions. 7th IEEE Heterogenous Computing Workshop (HCW’98), Orlando, 30 March 1998, 79-87.
http://dx.doi.org/10.1109/HCW.1998.666547
[18] Freund, R.F. and Siegel, H.J. (1993) Heterogenous Processing. IEEE Computer, 26, 13-17.
[19] Massimiliano, C. and Stefano, G. (2008) Resource Allocation in Grid Computing. WSEAS Transactions on Computer Research, 3.
[20] Jefferson, O.A., Mary, J.H. and Priyadarshan, K. (1996) A Software Metric System for Module Coupling. Journal of Systems & Software, 20, 295-308.
[21] Allen, E.B. and Khoshgoftaar, T.M. (2001) Measuring Coupling and Cohesion of Software Modules: An Information Theory Approach. Proceedings of 7th International Conference on Software Metric Symposium, London, 4-6 April 2001, 124-134.
http://dx.doi.org/10.1109/METRIC.2001.915521
[22] Ferreira, L., Berstis, V., Armstrong J., Kendzierski, M., Neukoetter, A., Takagi, M., Bing-Wo, R., Amir, A., Murakawa, R., Hernandez, O., Magowan, J. and Bieberstein, N. (2003) Introduction to Grid with Globus. 2nd Edition, IBM Redbook.

  
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