Research Article
A data placement strategy based on clustering and consistent hashing algorithm in Cloud Computing
@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
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.