DocumentCode :
1926058
Title :
ME2: Efficient Live Migration of Virtual Machine with Memory Exploration and Encoding
Author :
Ma, Yanqing ; Wang, Hongbo ; Dong, Jiankang ; Li, Yangyang ; Cheng, Shiduan
Author_Institution :
State Key Lab. of Networking & Switching Technol., Beijing Univ. of Posts & Telecommun., Beijing, China
fYear :
2012
fDate :
24-28 Sept. 2012
Firstpage :
610
Lastpage :
613
Abstract :
Live migration of virtual machine plays an important role in data center, which can successfully migrate virtual machine from one physical machine to another with only slight influence on upper workload. It can be used to facilitate hardware maintenance, load balancing, fault-tolerance and power-saving, especially in cloud computing data centers. Although the pre-copy is the prevailing approach, it cannot distinguish which memory page is used, resulting in transferring large amounts of useless memory pages. This paper presents a novel approach Memory Exploration and Encoding (ME2), which first identifies useful pages and then utilizes Run Length Encode algorithm to quickly encode memory, to efficiently decrease the total transferred data, total migration time and downtime. Experiments demonstrate that ME2 can significantly decrease 50.5% of total transferred data, 48.2% of total time and 47.6% of downtime on average compared with Xen´s pre-copy algorithm.
Keywords :
computer centres; encoding; fault tolerant computing; power aware computing; resource allocation; virtual machines; ME2; Memory Exploration and Encoding; Run Length Encode algorithm; Xen pre-copy algorithm; cloud computing data centers; fault-tolerance; hardware maintenance; live migration; load balancing; memory encoding; memory exploration; migrate virtual machine; power-saving; total migration time; total transferred data; Algorithm design and analysis; Bandwidth; Kernel; Linux; Memory management; Servers; Virtual machining; Data Center; Virtual Machine Migration; Virtualization; XEN;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Cluster Computing (CLUSTER), 2012 IEEE International Conference on
Conference_Location :
Beijing
Print_ISBN :
978-1-4673-2422-9
Type :
conf
DOI :
10.1109/CLUSTER.2012.52
Filename :
6337834
Link To Document :
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