Aristide Ndayikengurukiye, Abderrahmane Ez-Zahout, F. Omary
{"title":"优化异构云数据中心系统中的虚拟机部署","authors":"Aristide Ndayikengurukiye, Abderrahmane Ez-Zahout, F. Omary","doi":"10.22247/ijcna/2024/224431","DOIUrl":null,"url":null,"abstract":"– In a cloud computing environment, good resource management remains a major challenge for its good operation. Implementing virtual machine placement (VMP) on physical machines helps to achieve various objectives, such as resource allocation, load balancing, energy consumption, and quality of service. VMP (virtual machine placement) in the cloud is critical, so it's important to audit its implementation. It must take into account the resources of the physical server, including CPU, RAM, and storage. In this paper, a metaheuristic algorithm based on the Grey Wolf Optimization (GWO) method is used to optimize the placement of virtual machines in a cloud environment, effectively minimizing the number of active virtual machines used to host virtual servers. Experimental results demonstrate the effectiveness of the proposed method, called Grey Wolf Optimization for Virtual Machine Placement (GWOVMP). The method reduces power consumption by 20.99 and resource wastage by 1.80 compared with existing algorithms.","PeriodicalId":36485,"journal":{"name":"International Journal of Computer Networks and Applications","volume":"50 9","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2024-02-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Optimizing Virtual Machines Placement in a Heterogeneous Cloud Data Center System\",\"authors\":\"Aristide Ndayikengurukiye, Abderrahmane Ez-Zahout, F. Omary\",\"doi\":\"10.22247/ijcna/2024/224431\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"– In a cloud computing environment, good resource management remains a major challenge for its good operation. Implementing virtual machine placement (VMP) on physical machines helps to achieve various objectives, such as resource allocation, load balancing, energy consumption, and quality of service. VMP (virtual machine placement) in the cloud is critical, so it's important to audit its implementation. It must take into account the resources of the physical server, including CPU, RAM, and storage. In this paper, a metaheuristic algorithm based on the Grey Wolf Optimization (GWO) method is used to optimize the placement of virtual machines in a cloud environment, effectively minimizing the number of active virtual machines used to host virtual servers. Experimental results demonstrate the effectiveness of the proposed method, called Grey Wolf Optimization for Virtual Machine Placement (GWOVMP). The method reduces power consumption by 20.99 and resource wastage by 1.80 compared with existing algorithms.\",\"PeriodicalId\":36485,\"journal\":{\"name\":\"International Journal of Computer Networks and Applications\",\"volume\":\"50 9\",\"pages\":\"\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2024-02-26\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"International Journal of Computer Networks and Applications\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.22247/ijcna/2024/224431\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q4\",\"JCRName\":\"Computer Science\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Journal of Computer Networks and Applications","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.22247/ijcna/2024/224431","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"Computer Science","Score":null,"Total":0}
Optimizing Virtual Machines Placement in a Heterogeneous Cloud Data Center System
– In a cloud computing environment, good resource management remains a major challenge for its good operation. Implementing virtual machine placement (VMP) on physical machines helps to achieve various objectives, such as resource allocation, load balancing, energy consumption, and quality of service. VMP (virtual machine placement) in the cloud is critical, so it's important to audit its implementation. It must take into account the resources of the physical server, including CPU, RAM, and storage. In this paper, a metaheuristic algorithm based on the Grey Wolf Optimization (GWO) method is used to optimize the placement of virtual machines in a cloud environment, effectively minimizing the number of active virtual machines used to host virtual servers. Experimental results demonstrate the effectiveness of the proposed method, called Grey Wolf Optimization for Virtual Machine Placement (GWOVMP). The method reduces power consumption by 20.99 and resource wastage by 1.80 compared with existing algorithms.