A Resource Management Algorithm for Virtual Machine Migration in Vehicular Cloud Computing

作     者：Sohan Kumar Pande Sanjaya Kumar Panda Satyabrata Das Kshira Sagar Sahoo Ashish Kr.Luhach N.Z.Jhanjhi Roobaea Alroobaea Sivakumar Sivanesan 

作者机构：Veer Surendra Sai University of Technology BurlaBurla768018India National Institute of Technology WarangalWarangal506004India VNR Vignana Jyothi Institute of Engineering and TechnologyHyderabad500090India The Papua New Guinea University of TechnologyLae-41PapuaNew Guinea School of Computer Science and EngineeringTaylor’s UniversitySubang Jaya47500Malaysia Department of Computer ScienceCollege of Computers and Information TechnologyTaif UniversityTaif21944Saudi Arabia 

出 版 物：《Computers, Materials & Continua》 (计算机、材料和连续体（英文）)

年 卷 期：2021年第67卷第5期

页      面：2647-2663页

核心收录：

学科分类：08[工学] 082303[工学-交通运输规划与管理] 082302[工学-交通信息工程及控制] 0823[工学-交通运输工程] 

基　　金：Supporting Project number(TURSP-2020/36) Taif University Taif Saudi Arab 

主　　题：Resource management virtual machine migration vehicular cloud computing resource utilization source vehicle destination vehicle 

摘      要：In recent years,vehicular cloud computing(VCC)has gained vast attention for providing a variety of services by creating virtual machines(VMs).These VMs use the resources that are present in modern smart *** studies reported that some of these VMs hosted on the vehicles are overloaded,whereas others are *** a circumstance,the energy consumption of overloaded vehicles is drastically *** the other hand,underloaded vehicles are also drawing considerable energy in the underutilized ***,minimizing the energy consumption of the VMs that are hosted by both overloaded and underloaded is a challenging issue in the VCC *** proper and efcient utilization of the vehicle’s resources can reduce energy consumption *** of the solutions is to improve the resource utilization of underloaded vehicles by migrating the over-utilized VMs of overloaded *** the other hand,a large number of VM migrations can lead to wastage of energy and time,which ultimately degrades the performance of the *** paper addresses the issues mentioned above by introducing a resource management algorithm,called resource utilization-aware VM migration(RU-VMM)algorithm,to distribute the loads among the overloaded and underloaded vehicles,such that energy consumption is ***-VMM monitors the trend of resource utilization to select the source and destination vehicles within a predetermined threshold for the process of VM *** ensures that any vehicles’resource utilization should not exceed the threshold before or after the ***-VMM also tries to avoid unnecessary VM migrations between the ***-VMM is extensively simulated and tested using nine *** results are carried out using three performance metrics,namely number of nal source vehicles(nfsv),percentage of successful VM migrations(psvmm)and percentage of dropped VM migrations(pdvmm),and compared with threshold-based algorithm(i.e.,threshold)and