Description
This research proposes an agent-based optimization framework for addressing the cellular coverage gap problem in multi-access edge computing (MEC) systems. This optimization model aims to minimize the coverage gap area and reduce energy costs associated with mobile edge (ME) movements. To evaluate the model, effective metrics such as the filled area, travel distance, DSR, and FAR are introduced. Using geographic and cellular tower data collected from Dublin, the simulation environment demonstrates the high stability and reliability of the proposed model for real-world applications. An innovative aspect of this research is the use of a simulation environment that closely replicates real urban conditions. The results highlight that the optimization frequency significantly influences the overall performance of the system. High-frequency strategies incur higher energy costs, while frequencies between 100- and 150-time units strike a balance between efficiency and cost. Overall, the algorithm enhances the quality of service (QoS) of MEC networks by balancing coverage and energy costs.| Period | 1 Jan 2024 → 24 Dec 2024 |
|---|---|
| Degree of Recognition | International |