Fault Diagnosis for Distributed Systems using Accuracy Technique

TL;DR

This paper introduces a decentralized fault detection method for distributed systems that uses accuracy thresholds and voting among nodes to identify faults without relying on a central leader.

Contribution

It proposes an innovative accuracy-based voting technique for fault diagnosis that is decentralized and applicable to static ad-hoc networks.

Findings

Higher thresholds reduce false positives in fault detection

The method is decentralized, eliminating single points of failure

Applicable to static ad-hoc networks

Abstract

Distributed Systems involve two or more computer systems which may be situated at geographically distinct locations and are connected by a communication network. Due to failures in the communication link, faults arise which may make the entire system dysfunctional. To enable seamless operation of the distributed system, these faults need to be detected and located accurately. This paper examines various techniques of handling faults in distributed systems and proposes and innovative technique which uses percent accuracy for detecting faulty nodes in the system. Every node in the system acts as an initiator and votes for certifying faulty nodes in the system. This certification is done on the basis of percent accuracy value of each faulty node which should exceed a predefined threshold value to qualify node as faulty. As the threshold increases, the number of faulty nodes detected in the system reduces. This is a decentralized approach with no dependency on a single node to act as a leader for diagnosis. This technique is also applicable to ad-hoc networks, which are static in nature.