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arXiv · 2503.18122

QR-MO: Q-Routing for Multi-Objective Shortest-Path Computation in 5G-MEC Systems

Annisa Sarah·Rosario G. Garroppo·Gianfranco Nencioni
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Abstract

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.

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Annisa Sarah, Rosario G. Garroppo, Gianfranco Nencioni. 2025-03-23. QR-MO: Q-Routing for Multi-Objective Shortest-Path Computation in 5G-MEC Systems. https://arxiv.org/abs/2503.18122

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