Journal of Beijing Normal University, Volume. 61, Issue 3, 317(2025)

Resource-aware and energy-efficient virtual machine deployment in cloud datacenters

LIU Xuan1,2, WANG Chenyan1, LIU Zheng1,2, HU Bingmeng2, WEI Jieyao2, and CHENG Bo3、*
Author Affiliations
  • 1Key Laboraory of Ethnic Language Intelligent Analysis and Security Governance, Ministry of Education, Beijing, Minzu University of China, Beijing, China
  • 2School of Information Engineering, Minzu University of China, Beijing, China
  • 3School of Computer Science (National Pilot Software Engineering School), Beijing University of Posts and Telecommunications, Beijing, China
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    Aiming at the collaborative problem of resource load balancer and energy consumption optimization in cloud data center virtualization deployment, an efficient method is proposed to achieve some balance between these two objectives. Specifically, a load balancing model that integrates the multi-dimensional resource utilization balance is constructed, along with an energy consumption model that reflects energy loss under different system operating states. A bi-objective optimization function with resource constraints is then formulated. An improved hybrid sparrow search algorithm (HSSA) is then designed to minimize this optimization function. Cloud simulations show that, in a heterogeneous cloud environment with 200 nodes, the proposed method improves performance by 45.28% compared to the ant colony system (ACS), by 58.06% and 8.38% respectively compared to the first fit decreasing (FFD) algorithm and genetic algorithm (GA).

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    LIU Xuan, WANG Chenyan, LIU Zheng, HU Bingmeng, WEI Jieyao, CHENG Bo. Resource-aware and energy-efficient virtual machine deployment in cloud datacenters[J]. Journal of Beijing Normal University, 2025, 61(3): 317

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    Paper Information

    Received: Apr. 9, 2025

    Accepted: Aug. 21, 2025

    Published Online: Aug. 21, 2025

    The Author Email: CHENG Bo (chengbo@bupt.edu.cn)

    DOI:10.12202/j.0476-0301.2025058

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