STCDG: An efficient data gathering algorithm based on matrix completion for wireless sensor networks

Jie Cheng, Qiang Ye, Hongbo Jiang, Dan Wang, Chonggang Wang

Research output: Journal article publicationJournal articleAcademic researchpeer-review

115 Citations (Scopus)


Data gathering in sensor networks is required to be efficient, adaptable and robust. Recently, compressive sensing (CS) based data gathering shows promise in meeting these requirements. Existing CS-based data gathering solutions require that a transform that best sparsifies the sensor readings should be used in order to reduce the amount of data traffic in the network as much as possible. As a result, it is very likely that different transforms have to be determined for varied sensor networks, which seriously affects the adaptability of CS-based schemes. In addition, the existing schemes result in significant errors when the sampling rate of sensor data is low (equivalent to the case of high packet loss rate) because CS inherently requires that the number of measurements should exceed a certain threshold. This paper presents STCDG, an efficient data gathering scheme based on matrix completion. STCDG takes advantage of the low-rank feature instead of sparsity, thereby avoiding the problem of having to be customized for specific sensor networks. Besides, we exploit the presence of the short-term stability feature in sensor data, which further narrows down the set of feasible readings and reduces the recovery errors significantly. Furthermore, STCDG avoids the optimization problem involving empty columns by first removing the empty columns and only recovering the non-empty columns, then filling the empty columns using an optimization technique based on temporal stability. Our experimental results indicate that STCDG outperforms the state-of-the-art data gathering algorithms in terms of recovery error, power consumption, lifespan, and network capacity.
Original languageEnglish
Article number6399487
Pages (from-to)850-861
Number of pages12
JournalIEEE Transactions on Wireless Communications
Issue number2
Publication statusPublished - 7 Jan 2013


  • compressive sensing
  • data gathering
  • matrix completion
  • Wireless sensor networks

ASJC Scopus subject areas

  • Computer Science Applications
  • Electrical and Electronic Engineering
  • Applied Mathematics

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