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

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Dades bibliogràfiques
Publicat a:	Computation vol. 13, no. 7 (2025), p. 161-175
Autor principal:	Ananth, Kumar Tamilarasan
Altres autors:	Rajmohan Rajendirane, Ajagbe Sunday Adeola, Akinlade Oluwatobi, Adigun Matthew Olusegun
Publicat:	MDPI AG
Matèries:	Augmented reality Integer programming Investigations Edge computing Applications programs Bandwidths Optimization techniques Quality of service architectures Cloud computing Software services Optimization Network latency Mobile computing Computation offloading Power management Algorithms Real time Energy consumption Internet of Things Decisions
Accés en línia:	Citation/Abstract Full Text + Graphics Full Text - PDF
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Descripció
Resum:	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.
ISSN:	2079-3197
DOI:	10.3390/computation13070161
Font:	Advanced Technologies & Aerospace Database