An Efficient On-Demand Virtual Machine Migration in Cloud Using Common Deployment Model
作者机构:Department of Information TechnologySt.Joseph’s Institute of TechnologyChennai600119India Department of Information TechnologyLoyola-ICAM College of Engineering and TechnologyChennai600034India Department of Electronics and Communication EngineeringM.Kumarasamy College of EngineeringKarur639113India Data Science and Analytics CenterKarpagam College of EngineeringCoimbatore641032India Department of Electronics and Communication EngineeringR.M.K College of Engineering and TechnologyChennai601206India
出 版 物:《Computer Systems Science & Engineering》 (计算机系统科学与工程(英文))
年 卷 期:2022年第42卷第7期
页 面:245-256页
核心收录:
学科分类:08[工学] 0812[工学-计算机科学与技术(可授工学、理学学位)]
主 题:Cloud computing virtualization hypervisor VMmigration virtual machine
摘 要:Cloud Computing provides various services to the customer in aflex-ible and reliable *** Machines(VM)are created from physical resources of the data center for handling huge number of requests as a *** tasks are executed in the VM at the data center which needs excess hosts for satis-fying the customer *** VM migration solves this problem by migrating the VM from one host to another host and makes the resources available at any *** process is carried out based on various algorithms which follow a pre-defined capacity of source VM leads to the capacity issue at the destination *** proposed VM migration technique performs the migration process based on the request of the requesting host *** technique can perform in three ways namely single VM migration,Multiple VM migration and Cluster VM *** Deployment Manager(CDM)is used to support through negotiation that happens across the source host and destination host for providing the high quality service to their *** VM migration requests are handled with an exposure of the source host *** proposed analysis also uses the retired instructions with execution by the hypervisor to achieve high *** objective of the proposed technique is to perform a VM migration process based on the prior knowledge of the resource availability in the target VM.