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Recover Corrupted Data in Sensor Networks: A Matrix Completion Solution

文献类型：期刊论文

作者Xie, Kun4,5; Ning, Xueping5; Wang, Xin4; Xie, Dongliang1,4; Cao, Jiannong3; Xie, Gaogang2; Wen, Jigang2
刊名IEEE TRANSACTIONS ON MOBILE COMPUTING
出版日期2017-05-01
卷号16期号:5页码:1434-1448
关键词Corrupted data recovery matrix completion wireless sensor networks
ISSN号1536-1233
DOI10.1109/TMC.2016.2595569
英文摘要Affected by hardware and wireless conditions in WSNs, raw sensory data usually have notable data loss and corruption. Existing studies mainly consider the interpolation of random missing data in the absence of the data corruption. There is also no strategy to handle the successive missing data. To address these problems, this paper proposes a novel approach based on matrix completion (MC) to recover the successive missing and corrupted data. By analyzing a large set of weather data collected from 196 sensors in Zhu Zhou, China, we verify that weather data have the features of low-rank, temporal stability, and spatial correlation. Moreover, from simulations on the real weather data, we also discover that successive data corruption not only seriously affects the accuracy of missing and corrupted data recovery but even pollutes the normal data when applying the matrix completion in a traditional way. Motivated by these observations, we propose a novel Principal Component Analysis (PCA)-based scheme to efficiently identify the existence of data corruption. We further propose a two-phase MC-based data recovery scheme, named MC-Two-Phase, which applies the matrix completion technique to fully exploit the inherent features of environmental data to recover the data matrix due to either data missing or corruption. Finally, the extensive simulations with real-world sensory data demonstrate that the proposed MC-Two-Phase approach can achieve very high recovery accuracy in the presence of successively missing and corrupted data.
资助项目National High Technology Research and Development Program of China (863 Program)[2015AA01A705] ; Prospective Research Project on Future Networks (Jiangsu Future Networks Innovation Institute)[BY2013095-4-06] ; National Natural Science Foundation of China[61572184] ; National Natural Science Foundation of China[61300219] ; National Natural Science Foundation of China[61472283] ; National Natural Science Foundation of China[61271185] ; National Natural Science Foundation of China[61472131] ; US National Science Foundation[CNS 1526843]
WOS研究方向Computer Science ; Telecommunications
语种英语
WOS记录号WOS:000399322600019
出版者IEEE COMPUTER SOC
源URL[http://119.78.100.204/handle/2XEOYT63/7261]  
专题中国科学院计算技术研究所期刊论文_英文
通讯作者Xie, Kun
作者单位1.Beijing Univ Posts & Telecommun, State Key Lab Networking & Switching Technol, Beijing 100876, Peoples R China
2.Chinese Acad Sci, Inst Comp Technol, Beijing 100080, Peoples R China
3.Hong Kong Polytech Univ, Dept Comp, Hong Kong, Hong Kong, Peoples R China
4.SUNY Stony Brook, Dept Elect & Comp Engn, Stony Brook, NY 11794 USA
5.Hunan Univ, Coll Comp Sci & Elect Engn, Changsha 410082, Hunan, Peoples R China
推荐引用方式
GB/T 7714		 Xie, Kun,Ning, Xueping,Wang, Xin,et al. Recover Corrupted Data in Sensor Networks: A Matrix Completion Solution[J]. IEEE TRANSACTIONS ON MOBILE COMPUTING,2017,16(5):1434-1448.
APA Xie, Kun.,Ning, Xueping.,Wang, Xin.,Xie, Dongliang.,Cao, Jiannong.,...&Wen, Jigang.(2017).Recover Corrupted Data in Sensor Networks: A Matrix Completion Solution.IEEE TRANSACTIONS ON MOBILE COMPUTING,16(5),1434-1448.
MLA Xie, Kun,et al."Recover Corrupted Data in Sensor Networks: A Matrix Completion Solution".IEEE TRANSACTIONS ON MOBILE COMPUTING 16.5(2017):1434-1448.

入库方式： OAI收割

来源：计算技术研究所

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