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ELVMC: A Predictive Energy-Aware Algorithm for Virtual Machine Consolidation in Cloud Computing

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Algorithms and Architectures for Parallel Processing (ICA3PP 2020)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 12453))

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Abstract

Virtual machine consolidation (VMC) is a technology that aggregates virtual machines distributed on multiple physical machines into a small number of physical machines to improve resource utilization and energy efficiency of data center. However, excessive virtual machine aggregation and migration can also have a significant negative impact on performance. In this paper, an algorithm named ELVMC with multiple resource prediction is proposed for optimal virtual machine consolidation. It applies a modified Best-Fit Decreasing (BFD) algorithm for resource optimization at both overloaded hosts and underloaded hosts with consideration of load balancing. Different from current research, ELVMC aims to obtain an optimal virtual machine (VM) placement during each consolidation process by simultaneously optimizing multiple system performance metrics in terms of energy consumption, VM migrations and QoS guarantees while keeping the load balanced. Simulation results show that ELVMC is superior to the state of the arts, including the traditional BFD and SABFD-HS algorithms as well as recent research VMCUP-M and MUC-MBFD.

Supported by the National Natural Science Foundation of China under Grant No. 61662054, 61262082, Inner Mongolia Colleges and Universities of Young Technology Talent Support Program under Grant No. NJYT-19-A02, the Major Project of Inner Mongolia Natural Science Foundation: Research on Key Technologies of Cloud Support for Big Data Intelligent Analysis under Grant No. 2019ZD15, Natural Science Foundation of Inner Mongolia under Grand No. 2015MS0608, Inner Mongolia Science and Technology Innovation Team of Cloud Computing and Software Engineering, and Inner Mongolia Application Technology Research and Development Funding Project “Mutual Creation Service Platform Research and Development Based on Service Optimizing and Operation Integrating”.

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Authors and Affiliations

  1. College of Computer Science, Inner Mongolia University, Hohhot, China

    Da-ming Zhao & Jian-tao Zhou

  2. Department of Electrical and Computer Engineering, Stevens Institute of Technology, Hoboken, NJ, USA

    Shucheng Yu

Authors
  1. Da-ming Zhao
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  2. Jian-tao Zhou
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  3. Shucheng Yu
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Corresponding author

Correspondence to Jian-tao Zhou .

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Editors and Affiliations

  1. Columbia University, New York, NY, USA

    Meikang Qiu

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Zhao, Dm., Zhou, Jt., Yu, S. (2020). ELVMC: A Predictive Energy-Aware Algorithm for Virtual Machine Consolidation in Cloud Computing. In: Qiu, M. (eds) Algorithms and Architectures for Parallel Processing. ICA3PP 2020. Lecture Notes in Computer Science(), vol 12453. Springer, Cham. https://doi.org/10.1007/978-3-030-60239-0_5

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