POTMEC: A Novel Power Optimization Technique for Mobile Edge Computing Networks

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Xuất bản năm:Computation vol. 13, no. 7 (2025), p. 161-175
Tác giả chính: Ananth, Kumar Tamilarasan
Tác giả khác: Rajmohan Rajendirane, Ajagbe Sunday Adeola, Akinlade Oluwatobi, Adigun Matthew Olusegun
Được phát hành:
MDPI AG
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Bài tóm tắt:The rapid growth of ultra-dense mobile edge computing (UDEC) in 5G IoT networks has intensified energy inefficiencies and latency bottlenecks exacerbated by dynamic channel conditions and imperfect CSI in real-world deployments. This paper introduces POTMEC, a power optimization framework that combines a channel-aware adaptive power allocator using real-time SNR measurements, a MATLAB-trained RL model for joint offloading decisions and a decaying step-size algorithm guaranteeing convergence. Computational offloading is a productive technique to overcome mobile battery life issues by processing a few parts of the mobile application on the cloud. It investigated how multi-access edge computing can reduce latency and energy usage. The experiments demonstrate that the proposed model reduces transmission energy consumption by 27.5% compared to baseline methods while maintaining the latency below 15 ms in ultra-dense scenarios. The simulation results confirm a 92% accuracy in near-optimal offloading decisions under dynamic channel conditions. This work advances sustainable edge computing by enabling energy-efficient IoT deployments in 5G ultra-dense networks without compromising QoS.
số ISSN:2079-3197
DOI:10.3390/computation13070161
Nguồn:Advanced Technologies & Aerospace Database