GNN-MSOrchest: Graph Neural Networks Based Approach for Micro-Services Orchestration - A Simulation Based Design Use Case

Nader Belhadj, Mohamed Amine Mezghich, Jaouher Fattahi, Lassaad Latrach

2025

Abstract

In recent years, the micro-services architecture has emerged as a dominant paradigm in software engineering, praised for its modularity, scalability, and ease of maintenance. Nevertheless, orchestrating micro-services efficiently presents significant challenges, particularly in optimizing communication, load balancing, and fault tolerance. Graph Neural Networks (GNN), with their ability to model and process data structured as graphs, are particularly well-suited for representing the complex inter dependencies between micro-services. Despite their promising applications in micro-services architecture, GNNs are not sufficiently used for micro-services orchestration, which involves the automated management, coordination, and scaling of services. This paper proposes a novel GNNs based approach for micro-services orchestration. A simulation based design use case is studied and analysed.

Paper Citation

in Harvard Style

Belhadj N., Mezghich M., Fattahi J. and Latrach L. (2025). GNN-MSOrchest: Graph Neural Networks Based Approach for Micro-Services Orchestration - A Simulation Based Design Use Case. In Proceedings of the 17th International Conference on Agents and Artificial Intelligence - Volume 3: ICAART; ISBN 978-989-758-737-5, SciTePress, pages 933-939. DOI: 10.5220/0013238200003890

in Bibtex Style

@conference{icaart25,
author={Nader Belhadj and Mohamed Mezghich and Jaouher Fattahi and Lassaad Latrach},
title={GNN-MSOrchest: Graph Neural Networks Based Approach for Micro-Services Orchestration - A Simulation Based Design Use Case},
booktitle={Proceedings of the 17th International Conference on Agents and Artificial Intelligence - Volume 3: ICAART},
year={2025},
pages={933-939},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0013238200003890},
isbn={978-989-758-737-5},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 17th International Conference on Agents and Artificial Intelligence - Volume 3: ICAART
TI - GNN-MSOrchest: Graph Neural Networks Based Approach for Micro-Services Orchestration - A Simulation Based Design Use Case
SN - 978-989-758-737-5
AU - Belhadj N.
AU - Mezghich M.
AU - Fattahi J.
AU - Latrach L.
PY - 2025
SP - 933
EP - 939
DO - 10.5220/0013238200003890
PB - SciTePress