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Comparison and analysis of eight scheduling heuristics for the optimization of energy consumption and makespan in large-scale distributed systems

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Abstract

In this paper, we study the problem of scheduling tasks on a distributed system, with the aim to simultaneously minimize energy consumption and makespan subject to the deadline constraints and the tasks’ memory requirements. A total of eight heuristics are introduced to solve the task scheduling problem. The set of heuristics include six greedy algorithms and two naturally inspired genetic algorithms. The heuristics are extensively simulated and compared using an simulation test-bed that utilizes a wide range of task heterogeneity and a variety of problem sizes. When evaluating the heuristics, we analyze the energy consumption, makespan, and execution time of each heuristic. The main benefit of this study is to allow readers to select an appropriate heuristic for a given scenario.

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Authors and Affiliations

  1. NDSU-CIIT Green Computing and Communications Laboratory, North Dakota State University, Fargo, ND, 58108-6050, USA

    Peder Lindberg, James Leingang, Daniel Lysaker, Samee Ullah Khan & Juan Li

Authors
  1. Peder Lindberg
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  2. James Leingang
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  3. Daniel Lysaker
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  4. Samee Ullah Khan
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  5. Juan Li
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Correspondence to Samee Ullah Khan.

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Lindberg, P., Leingang, J., Lysaker, D. et al. Comparison and analysis of eight scheduling heuristics for the optimization of energy consumption and makespan in large-scale distributed systems. J Supercomput 59, 323–360 (2012). https://doi.org/10.1007/s11227-010-0439-6

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  • DOI: https://doi.org/10.1007/s11227-010-0439-6

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