Efficient Data Gathering in Wireless Sensor Networks Based on Matrix Completion and Compressive Sensing

International Journal of Online Engineering

Lei Chen¹  Jian Zhao²  Jiping Xiong² 

[1] School of Electronics and Information, TongJi University, Shanghai, ChinaSchool of Electronics and Information, TongJi University, Shanghai, ChinaSchool of Electronics and Information, TongJi University, Shanghai, China;College of Mathematics, Physics and Information Engineering, Zhejiang Normal University, Jinhua, ChinaCollege of Mathematics, Physics and Information Engineering, Zhejiang Normal University, Jinhua, ChinaCollege of Mathematics, Physics and Information Engineering, Zhejiang Normal University, Jinhua, China

关键词: Data Gathering;    Wireless senor Networks;    Matrix completion;    Compressive Sensing;   

DOI  :  

学科分类：社会科学、人文和艺术（综合）

来源: International Association of Online Engineering

【 摘 要 】

Gathering data in an energy efficient manner in wireless sensor networks is an important design challenge. In wireless sensor networks, the readings of sensors always exhibit intra-temporal and inter-spatial correlations. Therefore, in this paper, we use low rank matrix completion theory to explore the inter-spatial correlation and use compressive sensing theory to take advantage of intratemporal correlation. Our method, dubbed MCCS, can significantly reduce the amount of data that each sensor must send through network and to the sink, thus prolong the lifetime of the whole networks. Experiments using real datasets demonstrate the feasibility and efficacy of our MCCS method

【 授权许可】

Unknown