Abstract
The ability to migrate running applications among different grid resources is generally accepted as the solution to adapt to dynamic resource load, availability and cost. In this paper we focus on opportunistic migration when a new resource becomes available in the Grid. In this situation the performance of the new host, the remaining execution time of the application, and also the proximity of the new resource to the needed data, become critical factors to decide if job migration is feasible and worthwhile. We discuss the extension of the GridWay framework to consider all the previous factors in the resource selection and migration stages in order to improve response times of individual applications. The benefits of the new resource selector will be demonstrated for the execution of a computational fluid dynamics (CFD) code.
This research was supported by Ministerio de Ciencia y Tecnología through the research grant TIC 2002-00334 and Instituto Nacional de Técnica Aeroespacial (INTA).
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Liu, C., Yang, L., Foster, I., Angulo, D.: Design and Evaluation of a Resource Selection Framework for Grid Applications. In: Proceedings of the 11th IEEE Symposium on High-Performance Distributed Computing (2002)
Kennedy, K., et al.: Toward a Framework for Preparing and Execution Adaptive Grid Applications. In: Proceedings of NSF Next Generation Systems Program Workshop, International Parallel and Distributed Processing Symposium (2002)
Allcock, W., Chervenak, A., Foster, I., Pearlman, L., Welch, V., Wilde, M.: Globus Toolkit Support for Distributed Data-Intensive Science. In: Proceedings of Computing in High Energy Physics, CHEP 2001 (2001)
Evers, X., de Jongh, J.F.C.M., Boontje, R., Epema, D.H.J., van Dantzig, R.: Condor Flocking: Load Sharing Between Pools of Workstations. Technical Report DUT-TWI-93-104, Delft, The Netherlands (1993)
Vadhiyar, S., Dongarra, J.: A Performance Oriented Migration Framework for the Grid. In: Proceedings of the 3rd IEEE/ACM Int’l Symposium on Cluster Computing and the Grid, CCGrid (2003)
Wolski, R., Shao, G., Berman, F.: Predicting the Cost of Redistribution in Schedulling. In: Proceedings of the 8th SIAM Conference on Parallel Processing for Scientific Applications (1997)
Allen, G., et al.: The Cactus Worm: Experiments with Dynamic Resource Discovery and Allocation in a Grid Environment. International Journal of High- Performance Computing Applications 15 (2001)
Huedo, E., Montero, R.S., Llorente, I.M.: An Experimental Framework for Executing Applications in Dynamic Grid Environments. Technical Report 2002-43, ICASE NASA Langley, submitted to Intl. J. Software Practice & Experience (2002)
Wolski, R., Spring, N., Hayes, J.: The Network Weather Service: A Distributed Resource Performance Forecasting Service for Metacomputing. Journal of Future Generation Computing Systems 15, 757–768 (1999)
Vazhkudai, S., Schopf, J., Foster, I.: Predicting the Performance of Wide-Area Data Transfers. In: Proceedings of 16th Int’l Parallel and Distributed Processing Symposium, IPDPS 2002 (2002)
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Montero, R.S., Huedo, E., Llorente, I.M. (2003). Grid Resource Selection for Opportunistic Job Migration. In: Kosch, H., Böszörményi, L., Hellwagner, H. (eds) Euro-Par 2003 Parallel Processing. Euro-Par 2003. Lecture Notes in Computer Science, vol 2790. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-45209-6_55
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DOI: https://doi.org/10.1007/978-3-540-45209-6_55
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