Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/64263
Title: Virtual machine image content aware I/O optimization for mobile virtualization
Authors: Chen, R
Wang, Y
Hu, JT
Liu, D
Shao, ZL 
Guan, Y
Keywords: Metadata
Ash
Mobile communication
Virtualization
Operating systems
Nonvolatile memory
Virtual machining
Issue Date: 2015
Publisher: Institute of Electrical and Electronics Engineers
Source: Proceedings, 2015 IEEE 17th International Conference on High Performance Computing and Communications (HPCC) ; 2015 IEEE 7th International Symposium on Cyberspace Safety and Security (CSS); 2015 IEEE 12th International Conference on Embedded Software and Systems (ICESS) : 24-26 August 2015, New York, New York, p. 1031-1036 How to cite?
Abstract: Mobile virtualization introduces extra layers in software stacks, which leads to performance degradation. Especially, each I/O operation has to pass through several software layers to reach the NAND-flash-based storage systems. This paper targets at optimizing I/O for mobile virtualization, since I/O becomes one of major performance bottlenecks that seriously affects the performance of mobile devices. Among all the I/O operations, a large percentage is updating metadata. Frequent updating metadata not only degrades overall I/O performance but also severely reduces flash memory lifetime. In this paper, we propose a novel I/O optimization techniqueto identify the metadata of a guest file system which is storedin a VM (Virtual Machine) image file and frequently updated. Then, these metadata are stored in a small additional NVM(Non-Volatile Memory) which is faster and more endurableto greatly improve flash memory's performance and lifetime. To the best of our knowledge, this is the first work to identifythe file system metadata from regular data in a guest OS VMimage file under mobile virtualization. The proposed schemeis evaluated on a real hardware embedded platform. Theexperimental results show that the proposed techniques canimprove write performance to 45.21% in mobile devices withvirtualization.
URI: http://hdl.handle.net/10397/64263
ISBN: 978-1-4799-8937-9 (electronic)
978-1-4799-8936-2 (USB)
978-1-4799-8938-6 (Print on Demand(PoD))
DOI: 10.1109/HPCC-CSS-ICESS.2015.90
Appears in Collections:Conference Paper

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