Network Coding-Based Fault Diagnosis Protocol for Dynamic Networks

• Hazim Jarrah,
• Peter Han Joo Chong,
• Nurul I. Sarkar,
• Jairo Gutierrez,

Vol. 14, No. 4, April 30, 2020
10.3837/tiis.2020.04.005, Download Paper (Free):

• Dependability
• Fault diagnosis
• Comparison Model
• Dynamic Networks
• LNC

Abstract

Dependable functioning of dynamic networks is essential for delivering ubiquitous services. Faults are the root causes of network outages. The comparison diagnosis model, which automates fault’s identification, is one of the leading approaches to attain network dependability. Most of the existing research has focused on stationary networks. Nonetheless, the time-free comparison model imposes no time constraints on the system under considerations, and it suits most of the diagnosis requirements of dynamic networks. This paper presents a novel protocol that diagnoses faulty nodes in diagnosable dynamic networks. The proposed protocol comprises two stages, a testing stage, which uses the time-free comparison model to diagnose faulty neighbour nodes, and a disseminating stage, which leverages a Random Linear Network Coding (RLNC) technique to disseminate the partial view of nodes. We analysed and evaluated the performance of the proposed protocol under various scenarios, considering two metrics: communication overhead and diagnosis time. The simulation results revealed that the proposed protocol diagnoses different types of faults in dynamic networks. Compared with most related protocols, our proposed protocol has very low communication overhead and diagnosis time. These results demonstrated that the proposed protocol is energy-efficient, scalable, and robust.

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