Multi-access edge computing (MEC) is a promising technology that provides low-latency processing capabilities. To optimize the network performance in a MEC system, an efficient routing path between a user and a MEC host is essential. The network performance is characterized by multiple attributes, including packet-loss probability, latency, and jitter. A user service may require a particular combination of such attributes, complicating the shortest-path computation. This paper introduces Q-Routing for Multi-Objective shortest-path computation (QR-MO), which simultaneously optimizes multiple attributes. We compare the QR-MO's solutions with the optimal solutions provided by the Multi-objective Dijkstra Algorithm (MDA). The result shows the favorable potential of QR-MO. After 100 episodes, QR-MO achieves 100% accuracy in networks with low to moderate average node degrees, regardless of the size, and over 85% accuracy in networks with high average node degrees.
@article{arxiv.2503.18122,
title = {QR-MO: Q-Routing for Multi-Objective Shortest-Path Computation in 5G-MEC Systems},
author = {Annisa Sarah and Rosario G. Garroppo and Gianfranco Nencioni},
journal= {arXiv preprint arXiv:2503.18122},
year = {2025}
}
Comments
Submitted to Workshop on Space-Air-Ground-Sea Integrated Sensing, Computing, and Communications For 6G IoT; The 2025 IEEE 101st Vehicular Technology Conference: VTC2025-Spring