Localized fault-tolerant event boundary detection in sensor networks

Min Ding*, Dechang Chen, Kai Xing, Xiuzhen Cheng

*Corresponding author for this work

Research output: Contribution to journalConference articlepeer-review

367 Scopus citations


This paper targets the identification of faulty sensors and detection of the reach of events in sensor networks with faulty sensors. Typical applications include the detection of the transportation front line of a contamination and the diagnosis of network health. We propose and analyze two novel algorithms for faulty sensor identification and fault-tolerant event boundary detection. These algorithms are purely localized and thus scale well to large sensor networks. Their computational overhead is low, since only simple numerical operations are involved. Simulation results indicate that these algorithms can clearly detect the event boundary and can identify faulty sensors with a high accuracy and a low false alarm rate when as many as 20% sensors become faulty. Our work is exploratory in that the proposed algorithms can accept any kind of scalar values as inputs, a dramatic improvement over existing works that take only 0/1 decision predicates. Therefore, our algorithms are generic. They can be applied as long as the "events" can be modelled by numerical numbers. Though designed for sensor networks, our algorithms can be applied to the outlier detection and regional data analysis in spatial data mining.

Original languageEnglish
Pages (from-to)902-913
Number of pages12
JournalProceedings - IEEE INFOCOM
StatePublished - 2005
Externally publishedYes
EventIEEE INFOCOM 2005 - Miami, FL, United States
Duration: 13 Mar 200517 Mar 2005


  • Event boundary detection
  • Fault tolerance
  • Faulty sensor identification
  • Sensor networks


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