{"title":"一种基于阈值模糊的云数据中心虚拟机整合算法","authors":"N. Baskaran, R. Eswari","doi":"10.4018/ijghpc.2021010102","DOIUrl":null,"url":null,"abstract":"Cloud computing has grown exponentially in the recent years. Data growth is increasing day by day, which increases the demand for cloud storage, which leads to setting up cloud data centers. But they consume enormous amounts of power, use the resources inefficiently, and also violate service-level agreements. In this paper, an adaptive fuzzy-based VM selection algorithm (AFT_FS) is proposed to address these problems. The proposed algorithm uses four thresholds to detect overloaded host and fuzzy-based approach to select VM for migration. The algorithm is experimentally tested for real-world data, and the performance is compared with existing algorithms for various metrics. The simulation results testify to the proposed AFT_FS method is the utmost energy efficient and minimizes the SLA rate compared to other algorithms.","PeriodicalId":43565,"journal":{"name":"International Journal of Grid and High Performance Computing","volume":"57 1","pages":"18-46"},"PeriodicalIF":0.6000,"publicationDate":"2021-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"An Efficient Threshold-Fuzzy-Based Algorithm for VM Consolidation in Cloud Datacenter\",\"authors\":\"N. Baskaran, R. Eswari\",\"doi\":\"10.4018/ijghpc.2021010102\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Cloud computing has grown exponentially in the recent years. Data growth is increasing day by day, which increases the demand for cloud storage, which leads to setting up cloud data centers. But they consume enormous amounts of power, use the resources inefficiently, and also violate service-level agreements. In this paper, an adaptive fuzzy-based VM selection algorithm (AFT_FS) is proposed to address these problems. The proposed algorithm uses four thresholds to detect overloaded host and fuzzy-based approach to select VM for migration. The algorithm is experimentally tested for real-world data, and the performance is compared with existing algorithms for various metrics. The simulation results testify to the proposed AFT_FS method is the utmost energy efficient and minimizes the SLA rate compared to other algorithms.\",\"PeriodicalId\":43565,\"journal\":{\"name\":\"International Journal of Grid and High Performance Computing\",\"volume\":\"57 1\",\"pages\":\"18-46\"},\"PeriodicalIF\":0.6000,\"publicationDate\":\"2021-01-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"International Journal of Grid and High Performance Computing\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.4018/ijghpc.2021010102\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q4\",\"JCRName\":\"COMPUTER SCIENCE, THEORY & METHODS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Journal of Grid and High Performance Computing","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.4018/ijghpc.2021010102","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"COMPUTER SCIENCE, THEORY & METHODS","Score":null,"Total":0}
An Efficient Threshold-Fuzzy-Based Algorithm for VM Consolidation in Cloud Datacenter
Cloud computing has grown exponentially in the recent years. Data growth is increasing day by day, which increases the demand for cloud storage, which leads to setting up cloud data centers. But they consume enormous amounts of power, use the resources inefficiently, and also violate service-level agreements. In this paper, an adaptive fuzzy-based VM selection algorithm (AFT_FS) is proposed to address these problems. The proposed algorithm uses four thresholds to detect overloaded host and fuzzy-based approach to select VM for migration. The algorithm is experimentally tested for real-world data, and the performance is compared with existing algorithms for various metrics. The simulation results testify to the proposed AFT_FS method is the utmost energy efficient and minimizes the SLA rate compared to other algorithms.