A Local Diagnosis Algorithm for Hypercube-like Networks under the BGM Diagnosis Model

TL;DR

This paper introduces a polynomial-time diagnosis algorithm for hypercube-like networks under the BGM model, improving fault detection efficiency in multiprocessor systems.

Contribution

It presents a new structure and an efficient algorithm for diagnosing nodes in hypercube-like networks under the BGM diagnosis model.

Findings

Correct diagnosis of nodes in three test rounds

Polynomial-time diagnosis algorithm

Applicable to hypercube-like network structures

Abstract

System diagnosis is process of identifying faulty nodes in a system. An efficient diagnosis is crucial for a multiprocessor system. The BGM diagnosis model is a modification of the PMC diagnosis model, which is a test-based diagnosis. In this paper, we present a specific structure and propose an algorithm for diagnosing a node in a system under the BGM model. We also give a polynomial-time algorithm that a node in a hypercube-like network can be diagnosed correctly in three test rounds under the BGM diagnosis model.