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Verlag: Creative Media Partners, LLC, 2025
ISBN 10: 1025158113 ISBN 13: 9781025158112
Sprache: Englisch
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ISBN 10: 1025154274 ISBN 13: 9781025154275
Sprache: Englisch
Anbieter: AHA-BUCH GmbH, Einbeck, Deutschland
Buch. Zustand: Neu. Neuware - This thesis provides design and analysis of techniques for global load balancing on ensemble architectures running soft-real-time object-oriented applications with statistically periodic loads. It focuses on estimating the instantaneous average load over all the processing elements. The major contribution is the use of explicit stochastic process models for both the loading and the averaging itself. These models are exploited via statistical time-series analysis and Bayesian inference to provide improved average load estimates, and thus to facilitate global load balancing. This thesis explains the distributed algorithms used and provides some optimality results. It also describes the algorithms' implementation and gives performance results from simulation. These results show that our techniques allow more accurate estimation of the global system load ing, resulting in fewer object migration than local methods. Our method is shown to provide superior performance, relative not only to static load-balancing schemes but also to many adaptive methods.
Verlag: Creative Media Partners, LLC, 2025
ISBN 10: 1025158113 ISBN 13: 9781025158112
Sprache: Englisch
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In den WarenkorbZustand: New. KlappentextrnrnThis thesis provides design and analysis of techniques for global load balancing on ensemble architectures running soft-real-time object-oriented applications with statistically periodic loads. It focuses on estimating the instant.
Verlag: Creative Media Partners, LLC Mär 2013, 2013
ISBN 10: 1288916299 ISBN 13: 9781288916290
Sprache: Englisch
Anbieter: AHA-BUCH GmbH, Einbeck, Deutschland
Taschenbuch. Zustand: Neu. Neuware - This thesis provides design and analysis of techniques for global load balancing on ensemble architectures running soft-real-time object-oriented applications with statistically periodic loads. It focuses on estimating the instantaneous average load over all the processing elements. The major contribution is the use of explicit stochastic process models for both the loading and the averaging itself. These models are exploited via statistical time-series analysis and Bayesian inference to provide improved average load estimates, and thus to facilitate global load balancing. This thesis explains the distributed algorithms used and provides some optimality results. It also describes the algorithms' implementation and gives performance results from simulation. These results show that our techniques allow more accurate estimation of the global system load ing, resulting in fewer object migration than local methods. Our method is shown to provide superior performance, relative not only to static load-balancing schemes but also to many adaptive methods.
Verlag: Creative Media Partners, LLC, 2025
ISBN 10: 1025154274 ISBN 13: 9781025154275
Sprache: Englisch
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Verlag: Creative Media Partners, LLC, 2025
ISBN 10: 1025154274 ISBN 13: 9781025154275
Sprache: Englisch
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In den WarenkorbZustand: New. Print on Demand pp. 150.
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In den WarenkorbPaperback / softback. Zustand: New. This item is printed on demand. New copy - Usually dispatched within 5-9 working days 311.
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Zustand: New. PRINT ON DEMAND pp. 150.