Smart-blocking file storage method in cloud computing

Cloud storage is one of the underlying services in cloud computing. However, there are some critical issues in file storage which should be resolved urgently, such as the blocking file storage. In order to solve the shortages of hot file storage and parallel computing support issues in fixed-blocking storage, we propose a smart-blocking file storage method in this paper. By setting up 6 grouping factors, the method can determine whether the file should be blocked or not automatically depending on the size of the file and the client bandwidth. The proposed method can block the file into similar size sub-blocks as large as possible when the file is judged to be blocked. Normally the size of the last sub-block is smaller than other similar sub-blocks. But the gap maintains within the size of the next smaller grouping factor. The Metadata server can address the hot files when the file is blocked. In addition, the proposed method also defines the file uniformity and the system uniformity to quantitatively describe the uniformity of sub-blocks in the file and in the whole system. Analysis and simulation demonstrate the proposed method has better system uniformity in file storage, the node load balance caused by hot file, and a large number of file fragments reduction.

[1]  Xuemin Shen,et al.  Reputation-Based QoS Provisioning in Cloud Computing via Dirichlet Multinomial Model , 2010, 2010 IEEE International Conference on Communications.

[2]  Wang Fei,et al.  Optimized File-blocking Storage Scheme in Clustered VoD System , 2008 .

[3]  Tim Wright,et al.  Cloud Computing: Web-Based Applications That Change the Way You Work and Collaborate Online , 2009 .

[4]  Yun Tian,et al.  Improving MapReduce performance through data placement in heterogeneous Hadoop clusters , 2010, 2010 IEEE International Symposium on Parallel & Distributed Processing, Workshops and Phd Forum (IPDPSW).

[5]  Ya Wang,et al.  Cloud Storage as the Infrastructure of Cloud Computing , 2010, 2010 International Conference on Intelligent Computing and Cognitive Informatics.

[6]  Juebo Wu,et al.  Research and Application of Cloud Storage , 2010, 2010 2nd International Workshop on Intelligent Systems and Applications.

[7]  Prashant Pandey,et al.  Cloud computing , 2010, ICWET.

[8]  Zou De A Data Placement Strategy for Parallel Streaming Servers , 2006 .

[9]  Jianfeng Ma,et al.  Fast Parallel Computation of Tate Pairing , 2011, 2011 Third International Conference on Intelligent Networking and Collaborative Systems.

[10]  Andrew S. Tanenbaum,et al.  Distributed systems: Principles and Paradigms , 2001 .

[11]  Ying Zhan,et al.  Cloud Storage Management Technology , 2009, 2009 Second International Conference on Information and Computing Science.

[12]  Daiyuan Peng,et al.  An SMDP-Based Service Model for Interdomain Resource Allocation in Mobile Cloud Networks , 2012, IEEE Transactions on Vehicular Technology.