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Journal of Electrical and Computer Engineering
Volume 2015 (2015), Article ID 242086, 8 pages
http://dx.doi.org/10.1155/2015/242086
Research Article

A Bit String Content Aware Chunking Strategy for Reduced CPU Energy on Cloud Storage

1College of Computer Science, South-Central University for Nationalities, Wuhan, Hubei 430074, China
2School of Information Engineering, Wuhan Technology and Business University, Wuhan, Hubei 430065, China
3School of Foreign Languages, Huazhong University of Science and Technology, Wuhan, Hubei 430074, China

Received 11 May 2015; Accepted 30 July 2015

Academic Editor: Lu Liu

Copyright © 2015 Bin Zhou et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract

In order to achieve energy saving and reduce the total cost of ownership, green storage has become the first priority for data center. Detecting and deleting the redundant data are the key factors to the reduction of the energy consumption of CPU, while high performance stable chunking strategy provides the groundwork for detecting redundant data. The existing chunking algorithm greatly reduces the system performance when confronted with big data and it wastes a lot of energy. Factors affecting the chunking performance are analyzed and discussed in the paper and a new fingerprint signature calculation is implemented. Furthermore, a Bit String Content Aware Chunking Strategy (BCCS) is put forward. This strategy reduces the cost of signature computation in chunking process to improve the system performance and cuts down the energy consumption of the cloud storage data center. On the basis of relevant test scenarios and test data of this paper, the advantages of the chunking strategy are verified.