Performance Comparisons of Self-stabilizing Algorithms for Maximal Independent Sets

TL;DR

This paper compares five self-stabilizing algorithms for finding maximal independent sets in sensor networks, analyzing their efficiency, convergence time, and the size of the sets they produce through simulations.

Contribution

It introduces and evaluates five different self-stabilizing algorithms for maximal independent sets, providing a comparative analysis of their performance.

Findings

Algorithms vary in convergence time and set size.

Simulation results highlight trade-offs between speed and quality.

Self-stabilizing algorithms are effective for distributed topology control.

Abstract

Sensor networks, such as ultra-wideband sensors for the smart warehouse, may need to run distributed algorithms for automatically determining a topological layout. In this paper, we present 5 different self-stabilizing algorithms (their central and distributed counterparts) for determining maximal independent sets. The performance of the algorithms, in terms of time complexity, simulation analysis, and size of maximal independent sets found are then compared.