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Modeling and Analysis of Fault Detection and Fault Tolerance in Wireless Sensor Networks

Published:21 January 2015Publication History
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Abstract

Technological advancements in communications and embedded systems have led to the proliferation of Wireless Sensor Networks (WSNs) in a wide variety of application domains. These application domains include but are not limited to mission-critical (e.g., security, defense, space, satellite) or safety-related (e.g., health care, active volcano monitoring) systems. One commonality across all WSN application domains is the need to meet application requirements (e.g., lifetime, reliability). Many application domains require that sensor nodes be deployed in harsh environments, such as on the ocean floor or in an active volcano, making these nodes more prone to failures. Sensor node failures can be catastrophic for critical or safety-related systems. This article models and analyzes fault detection and fault tolerance in WSNs. To determine the effectiveness and accuracy of fault detection algorithms, we simulate these algorithms using ns-2. We investigate the synergy between fault detection and fault tolerance and use the fault detection algorithms’ accuracies in our modeling of Fault-Tolerant (FT) WSNs. We develop Markov models for characterizing WSN reliability and Mean Time to Failure (MTTF) to facilitate WSN application-specific design. Results obtained from our FT modeling reveal that an FT WSN composed of duplex sensor nodes can result in as high as a 100% MTTF increase and approximately a 350% improvement in reliability over a Non-Fault-Tolerant (NFT) WSN. The article also highlights future research directions for the design and deployment of reliable and trustworthy WSNs.

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                • Published in

                  cover image ACM Transactions on Embedded Computing Systems
                  ACM Transactions on Embedded Computing Systems  Volume 14, Issue 1
                  January 2015
                  443 pages
                  ISSN:1539-9087
                  EISSN:1558-3465
                  DOI:10.1145/2724585
                  Issue’s Table of Contents

                  Copyright © 2015 ACM

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                  Publication History

                  • Published: 21 January 2015
                  • Accepted: 1 September 2014
                  • Revised: 1 July 2014
                  • Received: 1 December 2013
                  Published in tecs Volume 14, Issue 1

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