UAV-Assisted MEC: A Hybrid PSO-GA for Joint Task Offloading Optimization
9th International Conference on Advanced Electronic Technology, Computers and Software Engineering, AETCSE 2026, Xian, Çin, 20 - 22 Mart 2026, ss.883-889, (Tam Metin Bildiri)
- Yayın Türü: Bildiri / Tam Metin Bildiri
- Doi Numarası: 10.1109/aetcse69203.2026.11504432
- Basıldığı Şehir: Xian
- Basıldığı Ülke: Çin
- Sayfa Sayıları: ss.883-889
- Anahtar Kelimeler: energy efficiency, joint optimization, task offloading, UAV-assisted MEC
- İstanbul Gelişim Üniversitesi Adresli: Evet
Özet
Enhancing the energy efficiency of ground users and UAVs or MECs sharing tasks in offloading mode. The main challenge to creating a UAV-assisted MEC task offloading mechanism is maintaining service quality and minimizing latency, as well as reducing energy consumption. The task offloading problem in UAV-assisted MEC systems is formulated as a mixed-integer nonlinear programming problem. We propose a joint optimization mechanism to process the tasks originated from end users, which is solved by the hybrid PSO-GA algorithm. The proposed mechanism aims to minimize energy consumption and reconstruct the service quality based on a task offloading mechanism that can accept some tolerance levels of latency in both task uplink and downlink. We utilized three network scenarios, each featuring varying numbers of UAVs, ground users, and MEC. The results show that the proposed hybrid PSO-GA outperforms, compared to benchmark studies, in terms of performance improvement mechanisms, increasing 4.7% and minimizing 7.14% of the energy efficiency of an entire network