Prepartition: Load Balancing Approach for Virtual Machine Reservations in a Cloud Data Center  

作　　者：田文洪 徐敏贤 周光耀 吴逵 须成忠 Rajkumar Buyya Wen-Hong Tian;Min-Xian Xu;Guang-Yao Zhou;Kui Wu;Cheng-Zhong Xu;Rajkumar Buyya(School of Information and Software Engineering,University of Electronic Science and Technology of China Chengdu 610054,China;Yangtze Delta Region Institute(Huzhou),University of Electronic Science and Technology of China,Huzhou 313001,China;Institute of Advanced Computing and Digital Engineering,Shenzhen Institute of Advanced Technology,Chinese Academy of Sciences,Shenzhen 518055,China;Department of Computer Science,University of Victoria,Victoria,BC,V8W 3P6,Canada;State Key Laboratory of Internet of Things for Smart City,University of Macao,Macao 999078,China;School of Computing and Information Systems,University of Melbourne,Melbourne 3010,Australia)

机构地区：[1]School of Information and Software Engineering,University of Electronic Science and Technology of China Chengdu 610054,China [2]Yangtze Delta Region Institute(Huzhou),University of Electronic Science and Technology of China,Huzhou 313001,China [3]Institute of Advanced Computing and Digital Engineering,Shenzhen Institute of Advanced Technology,Chinese Academy of Sciences,Shenzhen 518055,China [4]Department of Computer Science,University of Victoria,Victoria,BC,V8W 3P6,Canada [5]State Key Laboratory of Internet of Things for Smart City,University of Macao,Macao 999078,China [6]School of Computing and Information Systems,University of Melbourne,Melbourne 3010,Australia

出　　处：《Journal of Computer Science & Technology》2023年第4期773-792,共20页计算机科学技术学报（英文版）

基　　金：supported by Shenzhen Industrial Application Projects of undertaking the National Key Research and Development Program of China under Grant No.CJGJZD20210408091600002;the National Natural Science Foundation of China under Grant No.62102408;Shenzhen Science and Technology Program under Grant No.RCBS20210609104609044.

摘　　要：Load balancing is vital for the efficient and long-term operation of cloud data centers.With virtualization,post(reactive)migration of virtual machines(VMs)after allocation is the traditional way for load balancing and consolidation.However,it is not easy for reactive migration to obtain predefined load balance objectives and it may interrupt services and bring instability.Therefore,we provide a new approach,called Prepartition,for load balancing.It partitions a VM request into a few sub-requests sequentially with start time,end time and capacity demands,and treats each sub-request as a regular VM request.In this way,it can proactively set a bound for each VM request on each physical machine and makes the scheduler get ready before VM migration to obtain the predefined load balancing goal,which supports the resource allocation in a fine-grained manner.Simulations with real-world trace and synthetic data show that our proposed approach with offline version(PrepartitionOff)scheduling has 10%–20%better performance than the existing load balancing baselines under several metrics,including average utilization,imbalance degree,makespan and Capacity_makespan.We also extend Prepartition to online load balancing.Evaluation results show that our proposed approach also outperforms state-of-the-art online algorithms.

关 键 词：cloud computing physical machine(PM) virtual machine(VM) RESERVATION load balancing Prepartition 

分 类 号：TP302[自动化与计算机技术—计算机系统结构]