Detecting faulty nodes with data errors for wireless sensor networks

Shuo Guo, Heng Zhang, Ziguo Zhong, Jiming Chen, Qing Cao, Tian He

Research output: Contribution to journalArticlepeer-review

25 Scopus citations

Abstract

Wireless Sensor Networks (WSN) promise researchers a powerful instrument for observing sizable phenomena with fine granularity over long periods. Since the accuracy of data is important to the whole system's performance, detecting nodes with faulty readings is an essential issue in network management. As a complementary solution to detecting nodes with functional faults, this article, proposes FIND, a novel method to detect nodes with data faults that neither assumes a particular sensing model nor requires costly event injections. After the nodes in a network detect a natural event, FIND ranks the nodes based on their sensing readings as well as their physical distances from the event. FIND works for systems where the measured signal attenuates with distance. A node is considered faulty if there is a significant mismatch between the sensor data rank and the distance rank. Theoretically, we show that average ranking difference is a provable indicator of possible data faults. FIND is extensively evaluated in simulations and two test bed experiments with up to 25 MicaZ nodes. Evaluation shows that FIND has a less than 5% miss detection rate and false alarm rate in most noisy environments.

Original languageEnglish (US)
Article number40
JournalACM Transactions on Sensor Networks
Volume10
Issue number3
DOIs
StatePublished - Apr 2014

Keywords

  • Algorithms
  • Data fault detection
  • Design
  • Management
  • Wireless sensor networks

Fingerprint Dive into the research topics of 'Detecting faulty nodes with data errors for wireless sensor networks'. Together they form a unique fingerprint.

Cite this