The $g$-good neighbour diagnosability of hierarchical cubic networks

TL;DR

This paper investigates the fault diagnosability of hierarchical cubic networks, introducing the concept of $g$-good-neighbor diagnosability and deriving its exact value under two diagnostic models.

Contribution

It establishes the $g$-good-neighbor diagnosability of hierarchical cubic networks under PMC and MM* models, providing exact formulas for these measures.

Findings

$g$-good-neighbor diagnosability is $2^{g}(n+2-g)-1$ under PMC model.

$g$-good-neighbor diagnosability is $2^{g}(n+2-g)-1$ under MM* model.

Results enhance understanding of fault tolerance in hierarchical network topologies.

Abstract

Let $G=(V, E)$ be a connected graph, a subset $S\subseteq V(G)$ is called an $R^{g}$-vertex-cut of $G$ if $G-F$ is disconnected and any vertex in $G-F$ has at least $g$ neighbours in $G-F$. The $R^{g}$-vertex-connectivity is the size of the minimum $R^{g}$-vertex-cut and denoted by $\kappa^{g}(G)$. Many large-scale multiprocessor or multi-computer systems take interconnection networks as underlying topologies. Fault diagnosis is especially important to identify fault tolerability of such systems. The $g$-good-neighbor diagnosability such that every fault-free node has at least $g$ fault-free neighbors is a novel measure of diagnosability. In this paper, we show that the $g$-good-neighbor diagnosability of the hierarchical cubic networks $HCN_{n}$ under the PMC model for $1\leq g\leq n-1$ and the $MM^{*}$ model for $1\leq g\leq n-1$ is $2^{g}(n+2-g)-1$, respectively.