Spectral Heuristics Applied to Vertex Reliability

TL;DR

This paper introduces spectral heuristics to enhance vertex reliability in networks by strategically adding edges, demonstrating superior performance through extensive computational experiments across various graph models.

Contribution

The paper proposes two novel spectral heuristics for improving vertex reliability via a single edge insertion, evaluated against existing methods.

Findings

One spectral heuristic outperformed others in reliability improvement.

The heuristics were tested on 22,000 graphs from multiple models.

Statistical analysis confirmed the superior performance of one heuristic.

Abstract

The operability of a network concerns its ability to remain operational, despite possible failures in its links or equipment. One may model the network through a graph to evaluate and increase this operability. Its vertices and edges correspond to the users equipment and their connections, respectively. In this article, the problem addressed is identifying the topological change in the graph that leads to a greater increase in the operability of the associated network, considering the case in which failure occurs in the network equipment only. More specifically, we propose two spectral heuristics to improve the vertex reliability in graphs through a single edge insertion. The performance these heuristics and others that are usually found in the literature are evaluated by computational experiments with 22000 graphs of orders 10 up to 20, generated using the Models Erdos-Renyi, Barabasi-Albert, and Watts-Strogatz. From the experiments, it can be observed through analysis and application of statistical test, that one of the spectral heuristics presented a superior performance in relation to the others.