In-network outlier detection in wireless sensor networks

Joel W. Branch, Chris Giannella, Boleslaw Szymanski, Ran Wolff, Hillol Kargupta

Research output: Contribution to journalArticlepeer-review

Abstract

To address the problem of unsupervised outlier detection in wireless sensor networks, we develop an approach that (1) is flexible with respect to the outlier definition, (2) computes the result in-network to reduce both bandwidth and energy consumption, (3) uses only single-hop communication, thus permitting very simple node failure detection and message reliability assurance mechanisms (e. g., carrier-sense), and (4) seamlessly accommodates dynamic updates to data. We examine performance by simulation, using real sensor data streams. Our results demonstrate that our approach is accurate and imposes reasonable communication and power consumption demands.

Original languageEnglish
Pages (from-to)23-54
Number of pages32
JournalKnowledge and Information Systems
Volume34
Issue number1
DOIs
StatePublished - Jan 2013

Keywords

  • In-network computation
  • Outlier detection
  • Wireless sensor networks

ASJC Scopus subject areas

  • Software
  • Information Systems
  • Human-Computer Interaction
  • Hardware and Architecture
  • Artificial Intelligence

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