Han Xinming, Wang Jianxiao, Wu Jiaxi, Song Jie
Department of Industrial Engineering and Management, College of Engineering, Peking University, Beijing 100871, China.
National Engineering Laboratory for Big Data Analysis and Applications, Peking University, Beijing 100871, China.
iScience. 2025 Jan 27;28(3):111897. doi: 10.1016/j.isci.2025.111897. eCollection 2025 Mar 21.
This study addresses the challenge of virtual machine (VM) placement in cloud computing to improve resource utilization and energy efficiency. We propose a mixed integer linear programming (MILP) model incorporating -robustness theory to handle uncertainties in VM usage, optimizing both performance and energy consumption. A heuristic algorithm is developed for large-scale VM allocation. Experiments with Huawei Cloud data demonstrate significant improvements in resource utilization and energy efficiency.
本研究旨在应对云计算中虚拟机（VM）放置的挑战，以提高资源利用率和能源效率。我们提出了一种结合了-稳健性理论的混合整数线性规划（MILP）模型，以处理虚拟机使用中的不确定性，同时优化性能和能耗。针对大规模虚拟机分配开发了一种启发式算法。利用华为云数据进行的实验表明，在资源利用率和能源效率方面有显著提高。
