Research on the Design of Power Supply Gateway and Wireless Power Transmission Based on Edge Computing

Research on the Design of Power Supply Gateway and Wireless Power Transmission Based on Edge Computing

Zemin Wang, Jianmiao Ping, Junwei Fu, Yuedeng He, Changchun Li
Copyright: © 2024 |Pages: 18
DOI: 10.4018/IJDST.340941
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Abstract

There is a rising need for sensors under an IoT network to identify and monitor the environment as more IoT devices and services are made accessible for use. This movement presents challenges such as the proliferation of data and the scarcity of energy. This research presents a strategy for enhancing the service provision capabilities of WSN-aided IoT applications by combining mobile edge computation with wireless signal and control transmission. In order to reduce overall system energy consumption while maintaining data transmission rate and power needs, a new optimization problem integrating power allocation, CPU frequency, offloading weight factor, and energy harvesting is devised. The non-convex nature of the problem necessitates the development of a novel ideal solution group iterative process optimization model that divides the original problem into multiple subproblems, with each subproblem being optimized in turn. According to the results of simulations with a numerical model, our proposed method consumes considerably less energy than just the two benchmark methodologies.
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Introduction

With the 5G-enabled Internet of Things (IoT) (Shafique et al., 2020), humans can connect their physical environments with their digital environments at a time when human civilization is transitioning from informatization to intelligence (Chettri & Bera, 2019). Big capacity, ultralow latency, high dependability, and broad connectivity are the four qualities of the 5G communication system that are most significant for the development of IoT (Shahzadi et al., 2019). Using IoT services is now possible not just in smart cities (Wang et al., 2018) but also agriculture (Xuefei et al., 2020), medical care (Wazid et al., 2020), transportation (Dua et al., 2020), industry (Lu et al., 2020), and other fields (Zhang et al., 2020). Because 5G and wireless sensor network (WSN)-assisted IoT make it a lot easier to link the physical world with the internet (Lu et al., 2020), this is the case. Although WSN-assisted IoT presents significant risks (Zhang et al., 2020), the vast amounts of data traffic generated by a massive number of IoT devices and sensor systems may place considerable strain on the network (Cui et al., 2021), resulting in increased service disruptions and significantly reduced quality of service (QoS) (Jiang et al., 2020).

Regardless of the fact that technologically advanced terminal systems are dealing with advanced technology (Hewa et al., 2020), meeting the expectations of a computing-intensive workforce, specifically when it comes to ensuring low resource utilization and latency, can be difficult. Throughout the 5G IoT, multi-access edge computing (MEC), aka mobile edge computing technology, has been widely recognized as a significant framework (Zhang et al., 2016). In addition to reducing their own processing impact and energy efficiency (Spinelli & Mancuso, 2020), terminal appliances can offload almost all of their computational operations to an edge cloud infrastructure for processing (Spinelli & Mancuso, 2020), thereby increasing the processing productivity and effectiveness of the computing device while also providing a higher level of service (Liu et al., 2020). When MEC enabled industrial areas of expertise to continue operating in 5G environments, Guo et al. (2017) examined how this was accomplished. Giannopoulos et al. (2021) cite a study by Yang et al. that looked into the essential characteristics of MEC throughout the context of 5G as well as IoT. They also identified and described numerous fundamental core technologies that would allow MEC to be included in 5G and IoT.

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