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An approximation algorithm for virtual machine placement in cloud data centers

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Abstract

This study addresses the energy efficiency challenge in cloud data centers by examining the Virtual Machine Placement (VMP) problem. VMP involves mapping virtual machines (VMs) to physical machines (PMs) under capacity constraints. The paper focuses on the bin packing with linear usage cost (BPLUC) variant of bin packing, which includes fixed and variable costs in the calculation of the cost of a used bin. We prove that every approximation algorithm for the bin and vector bin packing can be used for BPLUC and VBPLUC, respectively. We propose a more power-efficient approach to VMP by applying a vector bin packing algorithm to minimize power consumption in data centers. We test the proposed algorithm on various synthetic and real workloads, and the experimental results demonstrate that it is more power-efficient than existing algorithms for VMP. The findings suggest that the proposed algorithm has significant implications for energy-efficient strategies in cloud data centers. Generally, this study makes contributes to the development of energy-efficient approaches to VMP that can help reduce power consumption and improve the sustainability of cloud data centers.

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Authors and Affiliations

  1. Department of Computer Engineering, Ferdowsi University of Mashhad, Mashhad, Iran

    Zahra Mahmoodabadi & Mostafa Nouri-Baygi

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  1. Zahra Mahmoodabadi
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  2. Mostafa Nouri-Baygi
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Correspondence to Mostafa Nouri-Baygi.

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Mahmoodabadi, Z., Nouri-Baygi, M. An approximation algorithm for virtual machine placement in cloud data centers. J Supercomput 80, 915–941 (2024). https://doi.org/10.1007/s11227-023-05505-8

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