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Dynamic Objective and Advance Scheduling in Federated Grids

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On the Move to Meaningful Internet Systems: OTM 2008 (OTM 2008)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 5331))

Abstract

In this paper we present a dynamic mapping strategy for scheduling independent tasks in Federated Grids. This strategy is performed in two steps: first we calculate a new objective, and then we apply advance scheduling to meet the new objective. The results obtained by simulation show that the combination of these two steps reduces the makespan and increases the throughput. Thus, the mapping strategy proposed meets two of the most common objective functions of tasks scheduling problems: makespan and performance of the resources. The presented algorithm is easy to implement, unlike Genetic Algorithms is fast enough to be used in a realistic scheduling, and is efficient. In addition, the information the strategy needs can be provided by any Grid Information Service, and its does not require the deployment of complex prediction services or service level agreement: it can work in any Grid.

This research was supported by Consejería de Educación de la Comunidad de Madrid, Fondo Europeo de Desarrollo Regional (FEDER) and Fondo Social Europeo (FSE), through BIOGRIDNET Research Program S-0505/TIC/000101, and by Ministerio de Educación y Ciencia and through the research grant TIN2006-02806. Research work also supported by the Madrid Regional Research Council under project TIC-000285-0505.

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Leal, K., Huedo, E., Llorente, I.M. (2008). Dynamic Objective and Advance Scheduling in Federated Grids. In: Meersman, R., Tari, Z. (eds) On the Move to Meaningful Internet Systems: OTM 2008. OTM 2008. Lecture Notes in Computer Science, vol 5331. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-88871-0_50

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  • DOI: https://doi.org/10.1007/978-3-540-88871-0_50

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-88870-3

  • Online ISBN: 978-3-540-88871-0

  • eBook Packages: Computer ScienceComputer Science (R0)

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