VMStore: Distributed storage system for multiple virtual machines

作     者：LIAO XiaoFei, LI He, JIN Hai , HOU HaiXiang, JIANG Yue & LIU HaiKun Services Computing Technology and System Lab, Cluster and Grid Computing Lab, School of Computer Science and Technology, Huazhong University of Science and Technology, Wuhan 430074, China 

作者机构：1. Services Computing Technology and System Lab Cluster and Grid Computing Lab School of Computer Science and Technology Huazhong University of Science and Technology Wuhan 430074 China 

出 版 物：《Science China(Information Sciences)》 (中国科学:信息科学(英文版))

年 卷 期：2011年第54卷第6期

页      面：1104-1118页

核心收录：

学科分类：08[工学] 081201[工学-计算机系统结构] 0812[工学-计算机科学与技术（可授工学、理学学位）] 

基　　金：supported by the National Basic Research Program of China(Grant No.2007CB310900) Program for New Century Excellent Talents in University(Grant No.NCET-08-0218) the National Natural Science Foundation of China(Grant No.60973133) FOK YING TUNG Education Foundation(Grant No.122007) the MoE-Intel Information Technology Special Research Foundation(Grant No.MOE-INTEL-10-05) 

主　　题：virtualization virtualized desktop distributed storage 

摘      要：Desktop virtualization is a very hot concept in both industry and academic communities. Since virtualized desktop system is based on multiple virtual machines (VM), it is necessary to design a distributed storage system to manage the VM images. In this paper, we design a distributed storage system, VMStore, by taking into account three important characteristics: high performance VM snapshot, booting optimization from multiple images and redundancy removal of images data. We adopt a direct index structure of blocks for VM snapshots to speed up VM booting performance significantly; provide a distribute storage structure with good bandwidth scalability by dynamically changing the number of storage nodes; and propose a data preprocessing strategy with intelligent object partitioning techniques, which would eliminate duplication more effectively. Performance analysis for VMStore focuses on two metrics: the speedup of VM booting and the overhead of de-duplication. Experimental results show the efficiency and effectiveness of VMStore.