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

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Pubblicato in:Computation vol. 13, no. 7 (2025), p. 161-175
Autore principale: Ananth, Kumar Tamilarasan
Altri autori: Rajmohan Rajendirane, Ajagbe Sunday Adeola, Akinlade Oluwatobi, Adigun Matthew Olusegun
Pubblicazione:
MDPI AG
Soggetti:
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
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Abstract: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
Fonte:Advanced Technologies & Aerospace Database