{"title":"基于生物地理的多目标虚拟机布局优化","authors":"Q. Zheng, R. Li, Xiuqi Li, Jie Wu","doi":"10.1109/CCGrid.2015.25","DOIUrl":null,"url":null,"abstract":"In cloud computing, an important issue is virtual machine placement (VMP), selecting the most suitable set of physical hosts for a set of virtual machines. In this paper, we present a novel solution to the VMP problem called VMPMBBO. Our scheme treats the VMP problem as a complex system, and utilizes the biogeography-based optimization (BBO) technique to optimize the virtual machine placement that minimizes power consumption, resource waste, server unevenness, inter-VM traffic, storage traffic and migration time at the same time. Compared with three existing multi-objective VMP optimization algorithms, VMPMBBO has better convergence characteristics and is more computationally efficient. VMPMBBO is also robust. Extensive experiments are conducted using synthetic data from related literatures. The results confirm the effectiveness, efficiency, and robustness of the proposed approach. To the best of our knowledge, this work is the first approach that applies BBO and complex system optimization to virtual machine placement (VMP).","PeriodicalId":6664,"journal":{"name":"2015 15th IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing","volume":"9 1","pages":"687-696"},"PeriodicalIF":0.0000,"publicationDate":"2015-05-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"37","resultStr":"{\"title\":\"A Multi-objective Biogeography-Based Optimization for Virtual Machine Placement\",\"authors\":\"Q. Zheng, R. Li, Xiuqi Li, Jie Wu\",\"doi\":\"10.1109/CCGrid.2015.25\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In cloud computing, an important issue is virtual machine placement (VMP), selecting the most suitable set of physical hosts for a set of virtual machines. In this paper, we present a novel solution to the VMP problem called VMPMBBO. Our scheme treats the VMP problem as a complex system, and utilizes the biogeography-based optimization (BBO) technique to optimize the virtual machine placement that minimizes power consumption, resource waste, server unevenness, inter-VM traffic, storage traffic and migration time at the same time. Compared with three existing multi-objective VMP optimization algorithms, VMPMBBO has better convergence characteristics and is more computationally efficient. VMPMBBO is also robust. Extensive experiments are conducted using synthetic data from related literatures. The results confirm the effectiveness, efficiency, and robustness of the proposed approach. To the best of our knowledge, this work is the first approach that applies BBO and complex system optimization to virtual machine placement (VMP).\",\"PeriodicalId\":6664,\"journal\":{\"name\":\"2015 15th IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing\",\"volume\":\"9 1\",\"pages\":\"687-696\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2015-05-04\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"37\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2015 15th IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/CCGrid.2015.25\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2015 15th IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CCGrid.2015.25","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
A Multi-objective Biogeography-Based Optimization for Virtual Machine Placement
In cloud computing, an important issue is virtual machine placement (VMP), selecting the most suitable set of physical hosts for a set of virtual machines. In this paper, we present a novel solution to the VMP problem called VMPMBBO. Our scheme treats the VMP problem as a complex system, and utilizes the biogeography-based optimization (BBO) technique to optimize the virtual machine placement that minimizes power consumption, resource waste, server unevenness, inter-VM traffic, storage traffic and migration time at the same time. Compared with three existing multi-objective VMP optimization algorithms, VMPMBBO has better convergence characteristics and is more computationally efficient. VMPMBBO is also robust. Extensive experiments are conducted using synthetic data from related literatures. The results confirm the effectiveness, efficiency, and robustness of the proposed approach. To the best of our knowledge, this work is the first approach that applies BBO and complex system optimization to virtual machine placement (VMP).