{"title":"动态环境下的多目标虚拟机布局","authors":"Diego Ihara, Fabio Lopez Pires, B. Barán","doi":"10.1109/UCC.2015.22","DOIUrl":null,"url":null,"abstract":"This paper presents for the first time a formulation of the Virtual Machine Placement as a Many-Objective problem (MaVMP), considering the simultaneous optimization of the following five objective functions for dynamic environments: (1) power consumption, (2) inter-VM network traffic, (3) economical revenue, (4) number of VM migrations and (5) network traffic overhead for VM migrations. To solve the formulated MaVMP problem, a novel Memetic Algorithm is proposed. As a potentially large number of feasible solutions at any time is one of the challenges of MaVMP, five selection strategies are evaluated in order to automatically select one solution at each time. The proposed algorithm with the considered selection strategies were evaluated in two different scenarios.","PeriodicalId":381279,"journal":{"name":"2015 IEEE/ACM 8th International Conference on Utility and Cloud Computing (UCC)","volume":"12 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2015-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"28","resultStr":"{\"title\":\"Many-objective virtual machine placement for dynamic environments\",\"authors\":\"Diego Ihara, Fabio Lopez Pires, B. Barán\",\"doi\":\"10.1109/UCC.2015.22\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper presents for the first time a formulation of the Virtual Machine Placement as a Many-Objective problem (MaVMP), considering the simultaneous optimization of the following five objective functions for dynamic environments: (1) power consumption, (2) inter-VM network traffic, (3) economical revenue, (4) number of VM migrations and (5) network traffic overhead for VM migrations. To solve the formulated MaVMP problem, a novel Memetic Algorithm is proposed. As a potentially large number of feasible solutions at any time is one of the challenges of MaVMP, five selection strategies are evaluated in order to automatically select one solution at each time. The proposed algorithm with the considered selection strategies were evaluated in two different scenarios.\",\"PeriodicalId\":381279,\"journal\":{\"name\":\"2015 IEEE/ACM 8th International Conference on Utility and Cloud Computing (UCC)\",\"volume\":\"12 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2015-12-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"28\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2015 IEEE/ACM 8th International Conference on Utility and Cloud Computing (UCC)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/UCC.2015.22\",\"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 IEEE/ACM 8th International Conference on Utility and Cloud Computing (UCC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/UCC.2015.22","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Many-objective virtual machine placement for dynamic environments
This paper presents for the first time a formulation of the Virtual Machine Placement as a Many-Objective problem (MaVMP), considering the simultaneous optimization of the following five objective functions for dynamic environments: (1) power consumption, (2) inter-VM network traffic, (3) economical revenue, (4) number of VM migrations and (5) network traffic overhead for VM migrations. To solve the formulated MaVMP problem, a novel Memetic Algorithm is proposed. As a potentially large number of feasible solutions at any time is one of the challenges of MaVMP, five selection strategies are evaluated in order to automatically select one solution at each time. The proposed algorithm with the considered selection strategies were evaluated in two different scenarios.