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Online energy-efficient deployment based on equivalent continuous DFS for large-scale web cluster

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Abstract

How to dynamically deploy web cluster so as to reduce energy consumption and mean-while satisfy performance requirements is an urgent problem to be resolved. In this paper, we propose an online energy-efficient deployment strategy to minimize cluster’s energy consumption on the premise of guaranteeing server’s CPU utilization equal to a given target value. It adopts CPU equivalent continuous Dynamic Frequency Scaling to reduce server power. First, we propose an approach of CPU utilization guarantee. Then, we describe cluster’s energy-efficient deployment problem as a constrained Mixed Integer Programming problem. Compared with similar works, our variable definition manner can reduce variable number significantly. Finally, we propose an improved differential evolution algorithm to solve the problem. Because of few variable number and high solving efficiency, even if applied to large-scale clusters, our strategy can still dynamically deploy the cluster online. Evaluation results verify the feasibility and effectiveness of the proposed deployment strategy.

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Acknowledgements

The authors acknowledge the Special Funds for Discipline and Specialty Construction of Guangdong Higher Education Institutions (2016KTSCX040), the Science and Technology Planning Project of Guangdong Province (No. 2016B090920095, 2016B010124012), and the Science and Technology Program of Shantou (No. 2014-98).

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Authors and Affiliations

  1. Department of Computer Science and Technology, Shantou University, Shantou, Guangdong, China

    Zhi Xiong, Ting Guo, Zhongliang Xue, Weihong Cai, Lingru Cai & Nanfu Luo

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  1. Zhi Xiong
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  2. Ting Guo
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  3. Zhongliang Xue
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  4. Weihong Cai
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  5. Lingru Cai
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  6. Nanfu Luo
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Correspondence to Zhi Xiong.

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Xiong, Z., Guo, T., Xue, Z. et al. Online energy-efficient deployment based on equivalent continuous DFS for large-scale web cluster. Cluster Comput 22 (Suppl 1), 583–596 (2019). https://doi.org/10.1007/s10586-017-1429-8

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  • DOI: https://doi.org/10.1007/s10586-017-1429-8

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