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| Title | Enhanced Wireless Communication Optimization With Neural Networks, Proximal Policy Optimization And Edge Computing For Latency And Energy Efficiency |
|---|---|
| ID_Doc | 23702 |
| Authors | Kousika N.; Thangamalar J.B.; Pritha N.; Jackson B.; Aiswarya M. |
| Year | 2024 |
| Published | International Journal of Electrical and Electronics Research, 12, 2 |
| DOI | http://dx.doi.org/10.37391/IJEER.120250 |
| Abstract | This research proposes a novel approach for efficient resource allocation in wireless communication systems. It combines dynamic neural networks, Proximal Policy Optimization (PPO), and Edge Computing Orchestrator (ECO) for latency-aware and energy-efficient resource allocation. The proposed system integrates multiple components, including a dynamic neural network, PPO, ECO, and a Mobile Edge Computing (MEC) server. The experimental methodology involves utilizing the NS-3 simulation platform to assess latency and energy efficiency in resource allocation within a wireless communication network, incorporating an ECO, MEC server, and dynamic task scheduling algorithms. It demonstrates a holistic and adaptable approach to resource allocation in dynamic environments, showcasing a notable reduction in latency for devices and tasks. Latency values range from 5 to 20 milliseconds, with corresponding resource utilization percentages varying between 80% and 95%. Additionally, energy-efficient resource allocation demonstrates a commendable reduction in energy consumption, with measured values ranging from 10 to 30 watts, coupled with efficient resource usage percentages ranging from 70% to 85%. These outcomes validate the efficacy of achieving both latency-aware and energy-efficient resource allocation for enhanced wireless communication systems. The proposed system has broad applications in healthcare, smart cities, IoT, real-time analytics, autonomous vehicles, and augmented reality, offering a valuable solution to optimize energy consumption, reduce latency, and enhance system efficiency in these industries. © 2024 by N. Kousika, J. Babitha Thangamalar, N. Pritha, Beulah Jackson, and M. Aiswarya. |
| Author Keywords | Dynamic Neural Networks; Edge Computing Orchestrator; Mobile Edge Computing server; Proximal Policy Optimization; Wireless Communication System |
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