This paper proposes a content addres sable storage optimization method, VDeskCAS, for desktop virtualization storage based disaster backup storage system. The method implements a blocklevel storage optimization, by em...This paper proposes a content addres sable storage optimization method, VDeskCAS, for desktop virtualization storage based disaster backup storage system. The method implements a blocklevel storage optimization, by employing the algorithms of chunking image file into blocks, the blockffmger calculation and the block dedup li cation. A File system in Use Space （FUSE） based storage process for VDeskCAS is also introduced which optimizes current direct storage to suit our content addressable storage. An interface level modification makes our system easy to extend. Experiments on virtual desktop image files and normal files verify the effectiveness of our method and above 60% storage volume decrease is a chieved for Red Hat Enterprise Linux image files. Key words： disaster backup; desktop virtualization; storage optimization; content addressable storage展开更多
More and more embedded devices, such as mobile phones, tablet PCs and laptops, are used in every field, so huge files need to be stored or backed up into cloud storage. Optimizing the performance of cloud storage is v...More and more embedded devices, such as mobile phones, tablet PCs and laptops, are used in every field, so huge files need to be stored or backed up into cloud storage. Optimizing the performance of cloud storage is very important for Internet development. This paper presents the performance evaluation of the open source distributed storage system, a highly available, distributed, eventually consistent object/blob store from Open Stack cloud computing components. This paper mainly focuses on the mechanism of cloud storage as well as the optimization methods to process different sized files. This work provides two major contributions through comprehensive performance evaluations. First, it provides different configurations for Open Stack Swift system and an analysis of how every component affects the performance. Second, it presents the detailed optimization methods to improve the performance in processing different sized files. The experimental results show that our method improves the performance and the structure. We give the methods to optimize the object-based cloud storage system to deploy the readily available storage system.展开更多
基金the Hi-tech Research and Development Program of China，the National Natural Science Foundation of China，the Beijing Natural Science Foundation，the Fundamental Research Funds for the Central Universities，the Fund of the State Key Laboratory of Software Development Environment
文摘This paper proposes a content addres sable storage optimization method, VDeskCAS, for desktop virtualization storage based disaster backup storage system. The method implements a blocklevel storage optimization, by employing the algorithms of chunking image file into blocks, the blockffmger calculation and the block dedup li cation. A File system in Use Space （FUSE） based storage process for VDeskCAS is also introduced which optimizes current direct storage to suit our content addressable storage. An interface level modification makes our system easy to extend. Experiments on virtual desktop image files and normal files verify the effectiveness of our method and above 60% storage volume decrease is a chieved for Red Hat Enterprise Linux image files. Key words： disaster backup; desktop virtualization; storage optimization; content addressable storage
基金performed by key technology of networking media broadcast based on cloud computing in"China Twelfth Five-Year"Plan for Science&Technology Project(Grant No.:2013BAH65F01-2013BAH65F04)NSFC(Grant No.:61472144)+3 种基金National science and technology support plan(Grant No.:2013BAH65F03,2013BAH65F04)GDSTP(Grant No.:2013B010202004,2014A010103012)GDUPS(2011)Research Fund for the Doctoral Program of Higher Education of China(Grant No.:20120172110023)
文摘More and more embedded devices, such as mobile phones, tablet PCs and laptops, are used in every field, so huge files need to be stored or backed up into cloud storage. Optimizing the performance of cloud storage is very important for Internet development. This paper presents the performance evaluation of the open source distributed storage system, a highly available, distributed, eventually consistent object/blob store from Open Stack cloud computing components. This paper mainly focuses on the mechanism of cloud storage as well as the optimization methods to process different sized files. This work provides two major contributions through comprehensive performance evaluations. First, it provides different configurations for Open Stack Swift system and an analysis of how every component affects the performance. Second, it presents the detailed optimization methods to improve the performance in processing different sized files. The experimental results show that our method improves the performance and the structure. We give the methods to optimize the object-based cloud storage system to deploy the readily available storage system.
