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An adaptive heuristic for managing energy consumption and overloaded hosts in a cloud data center

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Abstract

In this paper, we address the problems of massive amount of energy consumption and service level agreements (SLAs) violation in cloud environment. Although most of the existing work proposed solutions regarding energy consumption and SLA violation for cloud data centers (CDCs), while ignoring some important factor: (1) analysing the robustness of upper CPU utilization threshold which maximize utilization of resources; (2) CPU utilization prediction based VM selection from overloaded host which reduce performance degradation time and SLA violation. In this context, we proposed adaptive heuristic algorithms, namely least medial square regression for overloaded host detection and minimum utilization prediction for VM selection from overloaded hosts. These heuristic algorithms reducing CDC energy consumption with minimal SLA. Unlike the existing algorithms, the proposed VM selection algorithm consider the types of application running and it CPU utilization at different time periods over the VMs. The proposed approaches are validated using the CloudSim simulator and through simulations for different days of a real workload trace of PlanetLab.

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Acknowledgements

The National Key Research and Development Plan under Grant No. 2017YFB0801801, the National Science Foundation of China (NSFC) under Grant Nos. 61672186, 61472108, support this work.

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Authors and Affiliations

  1. School of Computer Science and Technology, Harbin Institute of Technology, Harbin, 150001, China

    Rahul Yadav, Weizhe Zhang, Muhammad Shafiq & Nabin Kumar Karn

  2. Pengcheng Laboratory, Shenzhen, China

    Weizhe Zhang

  3. Department of Computer Science, State University of New York, New Paltz, NY, 12561, USA

    Keqin Li

  4. School of Computer Science and Technology, Harbin Institute of Technology Shenzhen Graduate School, Shenzhen, China

    Chuanyi Liu

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  1. Rahul Yadav
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Correspondence to Rahul Yadav or Weizhe Zhang.

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Yadav, R., Zhang, W., Li, K. et al. An adaptive heuristic for managing energy consumption and overloaded hosts in a cloud data center. Wireless Netw 26, 1905–1919 (2020). https://doi.org/10.1007/s11276-018-1874-1

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