Potential of Using the Ant Colony Optimization Algorithm for Optimal Network Path Selection

• Published in: Proceedings of the International Conference on Applied Innovations in IT Vol. 13; no. 1; pp. 17 - 25
• Main Authors: Oleksandra Yaroshevska, Veronika Kirova
• Format: Journal Article
• Language: English
• Published: Anhalt University of Applied Sciences 01.04.2025
• Subjects: ant colony optimization (aco) algorithm; dijkstra’s algorithm; lowest common ancestor (lca); network optimal path; pheromone; python; rtt
• ISSN: 2199-8876
• DOI: 10.25673/119211

The article considers the possibilities of using the Ant Colony Optimization algorithm to find the shortest path in the network based on the selected criteria. Its performance is compared to Dijkstra's algorithm and LCA algorithm, which is widely used in different network routing protocols. An overview of the ACO algorithm, including its two primary components, the "ant" and "pheromone," is provided, highlighting its efficiency for the optimal network path selection. Detailed schemes, parameters and formulas of the ACO algorithm implementation in terms of networking are shown. A comparative analysis of the performance and execution time of the ACO and two compared algorithms for the optimal network path based on Round Trip Time criteria in networks of varying scale, ranging from small to highly branched networks with thousands of nodes, is discussed. Finally, the results are analysed, and the potential for ACO to serve as a complementary algorithm to Dijkstra's and LCA in future network applications is explored.