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A goal programming based energy efficient resource allocation in data centers

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Abstract

We study the multi-objective problem of mapping independent tasks onto a set of data center machines that simultaneously minimizes the energy consumption and response time (makespan) subject to the constraints of deadlines and architectural requirements. We propose an algorithm based on goal programming that effectively converges to the compromised Pareto optimal solution. Compared to other traditional multi-objective optimization techniques that require identification of the Pareto frontier, goal programming directly converges to the compromised solution. Such a property makes goal programming a very efficient multi-objective optimization technique. Moreover, simulation results show that the proposed technique achieves superior performance compared to the greedy and linear relaxation heuristics, and competitive performance relative to the optimal solution implemented in Linear Interactive and Discrete Optimizer (LINDO) for small-scale problems.

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Authors and Affiliations

  1. Department of Electrical and Computer Engineering, North Dakota State University, Fargo, ND, 58108, USA

    Samee Ullah Khan

  2. Department of Computer Science, COMSATS Institute of Information Technology, Islamabad, Pakistan

    Nasro Min-Allah

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  1. Samee Ullah Khan
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  2. Nasro Min-Allah
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Correspondence to Samee Ullah Khan.

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Khan, S.U., Min-Allah, N. A goal programming based energy efficient resource allocation in data centers. J Supercomput 61, 502–519 (2012). https://doi.org/10.1007/s11227-011-0611-7

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