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An energy-efficient cloud system with novel dynamic resource allocation methods

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Abstract

In the last decade, cloud computing has brought enormous changes to people’s lives. Cloud computing gives a client-driven computational model. In this case, the pay-per-use model enables a flexible method of deploying and sharing distributed services and resources. Furthermore, computational resources are progressively reassembled and insulated to give various types of services. Current solutions on how to efficiently utilize energy consumption are inadequate. Thus, we propose two methods to tackle the problem, which are the dynamic resource allocation method and the energy saving method, respectively. In this work, we firstly deployed an infrastructure platform based on OpenStack to actualize the proposed approach with live migration of virtual machines (VMs). Secondly, we allocated the dynamic resources and proposed the energy saving algorithm. Thirdly, we monitor the power distribution unit status to record the energy consumption of the system. Finally, in the experiments, we found that the proposed algorithms cannot just accomplish the proficient use of VMs’ resources but also thrift the energy usage of physical machines. Our experimental results demonstrate about 39.89% of energy is saved from 20 VCPUs of 20 GB memory.

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Acknowledgements

This work was supported in part by the Ministry of Science and Technology, Taiwan, under Grant MOST 104-2221-E-029-010-MY3 and MOST 106-3114-E-029-003.

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Authors and Affiliations

  1. Department of Computer Science, Tunghai University, No. 1727, Section 4, Taiwan Boulevard, Xitun District, Taichung, Taiwan

    Chao-Tung Yang

  2. College of Future, Bachelor Program in Interdisciplinary Studies, National Yunlin University of Science and Technology, 123 University Road, Section 3, Douliou, 64002, Yunlin, Taiwan

    Shuo-Tsung Chen

  3. Department of Computer Science, Tunghai University, No. 1727, Section 4, Taiwan Boulevard, Xitun District, Taichung, 40704, Taiwan

    Jung-Chun Liu

  4. College of Computing and Informatics, Providence University, 200, Section 7, Taiwan Boulevard, Shalu District, Taichung, Taiwan

    Yu-Wei Chan

  5. Department of Computer Science, Tunghai University, No. 1727, Section 4, Taiwan Boulevard, Xitun District, Taichung, Taiwan

    Chien-Chih Chen

  6. Department of Computer Science and Engineering, Deemed University under Ministry of Human Resource Development, Government of India, Longowal, Sangrur District, Punjab, 148106, India

    Vinod Kumar Verma

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  1. Chao-Tung Yang
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  2. Shuo-Tsung Chen
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  3. Jung-Chun Liu
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  4. Yu-Wei Chan
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  5. Chien-Chih Chen
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  6. Vinod Kumar Verma
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Correspondence to Yu-Wei Chan.

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Yang, CT., Chen, ST., Liu, JC. et al. An energy-efficient cloud system with novel dynamic resource allocation methods. J Supercomput 75, 4408–4429 (2019). https://doi.org/10.1007/s11227-019-02794-w

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