Fault Localization in Cloud using Centrality Measures

TL;DR

This paper proposes a novel fault localization method in cloud environments using centrality measures on fault graphs, enhancing accuracy and efficiency in identifying faulty modules within distributed systems.

Contribution

It introduces a graph-based fault localization approach leveraging centrality measures tailored for fault graphs in cloud environments, improving fault detection accuracy.

Findings

Effective identification of faulty modules in cloud systems

Improved fault localization accuracy over traditional methods

Applicable to complex distributed environments

Abstract

Fault localization is an imperative method in fault tolerance in a distributed environment that designs a blueprint for continuing the ongoing process even when one or many modules are non-functional. Visualizing a distributed environment as a graph, whose nodes represent faults (fault graph), allows us to introduce probabilistic weights to both edges and nodes that cause the faults. With multiple modules like databases, run-time cloud, etc. making up a distributed environment and extensively, a cloud environment, we aim to address the problem of optimally and accurately performing fault localization in a distributed environment by modifying the Graph optimization approach to localization and centrality, specific to fault graphs.