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MOEA/D for Energy-Aware Scheduling on Heterogeneous Computing Systems

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Bio-Inspired Computing -- Theories and Applications (BIC-TA 2015)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 562))

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Abstract

Heterogeneous Computing Systems (HCSs) often consist of a set of heterogeneous processors, and finding a scheduling for a workflow becomes a problem worth considering. The Dynamic Voltage Scaling (DVS) technique, which allows processors to operate at lower voltage to reduce the energy consumption, is widely used on HCSs. However, the technique also cause the loss of executing speed, and it makes the resource allocation a core component of the HCSs. In this paper, those two minimization objectives, the makespan and energy consumption, are considered together. As the heuristic methods have been widely applied in similar field, we adopt a multi-objective evolutionary algorithm based on decomposition (MOEA/D) to solve this scheduling problem. In our experiments, the algorithm shows higher performance in benchmark and the real-world applications than other state-of-art evolutionary algorithms do.

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Acknowledgment

This work was supported by the Natural Science Foundation of Heilongjiang Province (No. F201132).

Author information

Authors and Affiliations

  1. Software School, Xiamen University, Xiamen, 361005, China

    Gaoshan Deng

  2. Department of Computer Science, Xiamen University, Xiamen, 361005, China

    Ziming Li & Xiangxiang Zeng

  3. Information and Computer Engineering College, Northeast Forestry University, Harbin, 150001, Heilongjiang, China

    Yuming Zhao

Authors
  1. Gaoshan Deng
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  2. Ziming Li
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  3. Yuming Zhao
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  4. Xiangxiang Zeng
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Corresponding author

Correspondence to Ziming Li .

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Editors and Affiliations

  1. Xidian University, Xi'an, China

    Maoguo Gong

  2. Huazhong Univ. of Science and Technology, Wuhan, China

    Pan Linqiang

  3. University of Petroleum, Qingdao, China

    Song Tao

  4. University of Science and Technology of China, Hefei, China

    Ke Tang

  5. Anhui University, Hefei, China

    Xingyi Zhang

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Deng, G., Li, Z., Zhao, Y., Zeng, X. (2015). MOEA/D for Energy-Aware Scheduling on Heterogeneous Computing Systems. In: Gong, M., Linqiang, P., Tao, S., Tang, K., Zhang, X. (eds) Bio-Inspired Computing -- Theories and Applications. BIC-TA 2015. Communications in Computer and Information Science, vol 562. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-662-49014-3_9

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  • DOI: https://doi.org/10.1007/978-3-662-49014-3_9

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-662-49013-6

  • Online ISBN: 978-3-662-49014-3

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