Abstract
Deploying lightweight tasks on grid resources would let the communication overhead dominate the overall application processing time. Our aim is to increase the resulting computation-communication ratio by adjusting the task granularity at the grid scheduler. We propose an on-line scheduling algorithm which performs task grouping to support an unlimited number of user tasks, arriving at the scheduler at runtime. The algorithm decides the task granularity based on the dynamic nature of a grid environment: task processing requirements; resource-network utilisation constraints; and users QoS requirements. Simulation results reveal that our algorithm reduces the overall application processing time and communication overhead significantly while satisfying the runtime constraints set by the users and the resources.
This research is partially supported by e-ScienceFund, Ministry of Science, Technology and Innovation, Malaysia, and Endeavour Awards, Austraining International.
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References
Berman, F., Fox, G.C., Hey, A.J.G. (eds.): Grid Computing - Making the Global Infrastructure a Reality. Wiley and Sons, Chichester (2003)
Baker, M., Buyya, R., Laforenza, D.: Grids and grid technologies for wide-area distributed computing. Softw. Pract. Exper. 32, 1437–1466 (2002)
Jacob, B., Brown, M., Fukui, K., Trivedi, N.: Introduction to Grid Computing. IBM Publication (2005)
Buyya, R., Date, S., Mizuno-Matsumoto, Y., Venugopal, S., Abramson, D.: Neuroscience instrumentation and distributed analysis of brain activity data: a case for escience on global grids: Research articles. Concurrency and Computation: Practice and Experience (CCPE) 17, 1783–1798 (2005)
Muthuvelu, N., Liu, J., Soe, N.L., Venugopal, S., Sulistio, A., Buyya, R.: A dynamic job grouping-based scheduling for deploying applications with fine-grained tasks on global grids. In: Proceedings of the 2005 Australasian workshop on Grid computing and e-research, pp. 41–48. Australian Computer Society, Inc. (2005)
Feng, J., Wasson, G., Humphrey, M.: Resource usage policy expression and enforcement in grid computing. In: Proceedings of the 8th IEEE/ACM International Conference on Grid Computing, Washington, DC, USA, pp. 66–73. IEEE Computer Society, Los Alamitos (2007)
Arnon, R.G.O.: Fallacies of distributed computing explained (2007), http://www.webperformancematters.com/
Ranaldo, N., Zimeo, E.: A framework for qos-based resource brokering in grid computing. In: Proceedings of the 5th IEEE European Conference on Web Services, the 2nd Workshop on Emerging Web Services Technology, Halle, Germany, vol. 313, pp. 159–170. Birkhauser, Basel (2007)
James, H., Hawick, K., Coddington, P.: Scheduling independent tasks on metacomputing systems. In: Proceedings of Parallel and Distributed Computing Systems, Fort Lauderdale, US, pp. 156–162 (1999)
Sodan, A.C., Kanavallil, A., Esbaugh, B.: Group-based optimizaton for parallel job scheduling with scojo-pect-o. In: Proceedings of the 2008 22nd International Symposium on High Performance Computing Systems and Applications, Washington, DC, USA, pp. 102–109. IEEE Computer Society, Los Alamitos (2008)
Maghraoui, K.E., Desell, T.J., Szymanski, B.K., Varela, C.A.: The internet operating system: Middleware for adaptive distributed computing. International Journal of High Performance Computing Applications 20, 467–480 (2006)
Ng, W.K., Ang, T., Ling, T., Liew, C.: Scheduling framework for bandwidth-aware job grouping-based scheduling in grid computing. Malaysian Journal of Computer Science 19, 117–126 (2006)
Stokes, J.H.: Behind the benchmarks: Spec, gflops, mips et al (2000), http://arstechnica.com/cpu/2q99/benchmarking-2.html
Muthuvelu, N., Chai, I., Chikkannan, E.: An adaptive and parameterized job grouping algorithm for scheduling grid jobs. In: Proceedings of the 10th International Conference on Advanced Communication Technology, vol. 2, pp. 975–980 (2008)
Lowekamp, B., Tierney, B., Cottrell, L., Jones, R.H., Kielmann, T., Swany, M.: A Hierarchy of Network Performance Characteristics for Grid Applications and Services (2003)
Buyya, R., Murshed, M.M.: Gridsim: A toolkit for the modeling and simulation of distributed resource management and scheduling for grid computing. Concurrency and Computation: Practice and Experience (CCPE)Â 14 (2002)
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Muthuvelu, N., Chai, I., Chikkannan, E., Buyya, R. (2010). On-Line Task Granularity Adaptation for Dynamic Grid Applications. In: Hsu, CH., Yang, L.T., Park, J.H., Yeo, SS. (eds) Algorithms and Architectures for Parallel Processing. ICA3PP 2010. Lecture Notes in Computer Science, vol 6081. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-13119-6_24
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DOI: https://doi.org/10.1007/978-3-642-13119-6_24
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