A Probabilistic Comparison-based Fault Diagnosis for Hybrid Faults in Mobile Networks

Date
2020
Authors
Jarrah, H
Chong, P
Rapson, C
Sarkar, NI
Gutierrez, J
Supervisor
Item type
Journal Article
Degree name
Journal Title
Journal ISSN
Volume Title
Publisher
Elsevier
Abstract

Fault diagnosis has always been vital to providing a high level of dependability in systems. The comparison approach is one of the most prevalent diagnosis techniques that offers a simple and yet practical way to identify faulty nodes in a system. Even though several comparison-based diagnostic models have already been introduced, the majority of them only diagnose permanent faults in static networks. Nowadays, intermittent faults and dynamic systems are more challenging to diagnose and become more common. This paper, first, proposes a novel comparison-based diagnostic model that deals with hybrid fault model in mobile networks. Both the diagnosable systems and faults under the proposed model have been characterised. Second, this paper proposes an efficient fault diagnosis protocol for hybrid faults in mobile networks. The proposed protocol employs a network coding technique to exchange the diagnosis messages so that it can provide a correct diagnosis with a higher probability of completeness. The correctness and complexity proofs of the proposed protocol are presented, and they show the viability of the proposed diagnostic model and protocol for hybrid faults in mobile networks. Besides, we study and analyse the performance of the proposed protocol under various fault and system parameters using OMNeT++ simulation. The simulation results show that our protocol can diagnose hybrid faults in mobile networks with high accuracy and less overhead.

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Source
Computer Communications, Volume 156, 15 April 2020, Pages 131-144
Rights statement
Copyright © 2020 Elsevier Ltd. All rights reserved. This is the author’s version of a work that was accepted for publication in (see Citation). Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. The definitive version was published in (see Citation). The original publication is available at (see Publisher's Version).