MPI-based Evaluation of Coordinator Election Algorithms

TL;DR

This paper presents an MPI-based experimental framework for evaluating and comparing distributed coordinator election algorithms on HPC infrastructure, emphasizing performance metrics and educational applications.

Contribution

It introduces an MPI implementation for experimental comparison of election algorithms and demonstrates its use in educational and practical HPC contexts.

Findings

Performance metrics characterized through statistical analysis

Educational use for teaching distributed algorithms

Use cases demonstrating algorithm applicability

Abstract

In this paper, we detail how two types of distributed coordinator election algorithms can be compared in terms of performance based on an evaluation on the High Performance Computing (HPC) infrastructure. An experimental approach based on an MPI (Message Passing Interface) implementation is presented, with the goal to characterize the relevant evaluation metrics based on statistical processing of the results. The presented approach can be used to learn master students of a course on distributed software the basics of algorithms for coordinator election, and how to conduct an experimental performance evaluation study. Finally, use cases where distributed coordinator election algorithms are useful are presented.