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Failure detection in wireless sensor networks: A sequence-based dynamic approach

Published:31 January 2014Publication History
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Abstract

Wireless Sensor Network (WSN) technology has recently moved out of controlled laboratory settings to real-world deployments. Many of these deployments experience high rates of failure. Common types of failure include node failure, link failure, and node reboot. Due to the resource constraints of sensor nodes, existing techniques for fault detection in enterprise networks are not applicable. Previously proposed WSN fault detection algorithms either rely on periodic transmission of node status data or inferring node status based on passive information collection. The former approach significantly reduces network lifetime, while the latter achieves poor accuracy in dynamic or large networks. Herein, we propose Sequence-Based Fault Detection (SBFD), a novel framework for network fault detection in WSNs. The framework exploits in-network packet tagging using the Fletcher checksum and server-side network path analysis to efficiently deduce the path of all packets sent to the sink. The sink monitors the extracted packet paths to detect persistent path changes which are indicative of network failures. When a failure is suspected, the sink uses control messages to check the status of the affected nodes. SBFD was implemented in TinyOS on TelosB motes and its performance was assessed in a testbed network and in TOSSIM simulation. The method was found to achieve a fault detection accuracy of 90.7% to 95.0% for networks of 25 to 400 nodes at the cost of 0.164% to 0.239% additional control packets and a 0.5% reduction in node lifetime due to in-network packet tagging. Finally, a comparative study was conducted with existing solutions.

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    • Published in

      cover image ACM Transactions on Sensor Networks
      ACM Transactions on Sensor Networks  Volume 10, Issue 2
      January 2014
      609 pages
      ISSN:1550-4859
      EISSN:1550-4867
      DOI:10.1145/2575808
      Issue’s Table of Contents

      Copyright © 2014 ACM

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      Publication History

      • Published: 31 January 2014
      • Accepted: 1 April 2013
      • Revised: 1 March 2013
      • Received: 1 May 2012
      Published in tosn Volume 10, Issue 2

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