Discrete PSO-based workload optimization in virtual machine placement

被引：0
作者：
Jianen Yan
Hongli Zhang
Haiyan Xu
Zhaoxin Zhang
机构：
[1] Harbin Institute of Technology,School of Computer Science and Technology
来源：
Personal and Ubiquitous Computing | 2018年 / 22卷
关键词：
Virtual machine placement; Discrete particle swarm optimization (DPSO); Workload optimization; OpenStack;
D O I：
暂无
中图分类号：
学科分类号：
摘要：
Virtual machine placement has great potential to significantly improve the efficiency of resource utilization in a cloud center. Focusing on CPU and memory resource, this paper presents SOWO—a discrete particle swarm optimization-based workload optimization approach to minimize the number of active physical machines in virtual machine placement. The experiment results show the usability and superiority of SOWO. Compared with the OpenStack native scheduler, SOWO decreases the physical machine consumption by at least 50% and increases the memory utilization of physical machine by more than two times.
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页码：589 / 596
页数：7
相关论文
共 40 条
[11]  
Kephart JO(2002)The particle swarm-explosion, stability, and convergence in a multidimensional complex space IEEE Trans Evol Comput 6 58-73
[12]  
Hanson JE(1997)A discrete binary version of the particle swarm algorithm IEEE Proc Syst Man Cybern Comput Cybern Simul 5 4104-4108
[13]  
Kandasamy N(2009)Sandpiper: black-box and gray-box resource management for virtual machines Comput Netw 53 2923-2938
[14]  
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