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Applications to Computer Science: Optimal Scheduling for Global Computing

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Computing Statistics under Interval and Fuzzy Uncertainty

Part of the book series: Studies in Computational Intelligence ((SCI,volume 393))

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Abstract

In many practical situations, in particular in many bioinformatics problems, the amount of computations is so huge that the only way to perform these computations in reasonable time is to distribute them between multiple processors. The more processors we engage, the faster the resulting computations; thus, in addition to processor exclusively dedicated to this job, systems often use idle time on other processors. The use of these otherwise engaged processors adds additional uncertainty to computations.

How should we schedule the computational tasks so as to achieve the best utilization of the computational resources? Because of the presence of uncertainty, this scheduling problem is very difficult not only to solve but even to formalize (i.e., to describe in precise terms). In this chapter, we provide the first steps towards formalizing and solving this scheduling problem.

The main result of this chapter first appeared in [12].

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© 2012 Springer-Verlag Berlin Heidelberg

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Nguyen, H.T., Kreinovich, V., Wu, B., Xiang, G. (2012). Applications to Computer Science: Optimal Scheduling for Global Computing. In: Computing Statistics under Interval and Fuzzy Uncertainty. Studies in Computational Intelligence, vol 393. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-24905-1_33

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  • DOI: https://doi.org/10.1007/978-3-642-24905-1_33

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-24904-4

  • Online ISBN: 978-3-642-24905-1

  • eBook Packages: EngineeringEngineering (R0)

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