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9th International Conference on Communications and Networking in China

Research Article

A data placement strategy based on clustering and consistent hashing algorithm in Cloud Computing

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BibTeX Plain Text
  • @INPROCEEDINGS{10.4108/icst.chinacom.2014.256328,
        author={Qiang Li and Kun Wang and Suwei Wei and Xuefeng Han and Lili Xu and Min Gao},
        title={A data placement strategy based on clustering and consistent hashing algorithm in Cloud Computing},
        proceedings={9th International Conference on Communications and Networking in China},
        publisher={IEEE},
        proceedings_a={CHINACOM},
        year={2015},
        month={1},
        keywords={data placement clustering consistent hashing sparse matrix cloud computing},
        doi={10.4108/icst.chinacom.2014.256328}
    }
    
  • Qiang Li
    Kun Wang
    Suwei Wei
    Xuefeng Han
    Lili Xu
    Min Gao
    Year: 2015
    A data placement strategy based on clustering and consistent hashing algorithm in Cloud Computing
    CHINACOM
    IEEE
    DOI: 10.4108/icst.chinacom.2014.256328
Qiang Li1, Kun Wang1,*, Suwei Wei1, Xuefeng Han1, Lili Xu1, Min Gao2
  • 1: Nanjing University of Posts and Telecommunications
  • 2: UCLA
*Contact email: kwang@njupt.edu.cn

Abstract

To reduce time delay of processing data and improve the efficiency of cloud computing, a clustering algorithm based on the principle of minimum distance is proposed to place user-based and item-based data, update cluster centre and the threshold dynamically. Besides, consistent hashing is combined to solve the fault tolerance and scalability issues. In addition, Case-Based Reasoning (CBR) algorithm and item-based Coordination Filtering (CF) algorithms are used for filling sparse matrix to achieve better effect on the user-based clustering. Simulation results show that compared with data placement strategy based on K-means algorithm, this data placement strategy significantly improves clustering accuracy, greatly reduces delay of processing data and increases database scalability and redundancy, thereby improving the efficiency of cloud computing.

Keywords
data placement clustering consistent hashing sparse matrix cloud computing
Published
2015-01-21
Publisher
IEEE
Appears in
IEEEXplore
http://dx.doi.org/10.4108/icst.chinacom.2014.256328
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