Evolutionary Beamforming Optimization for Radio Frequency Charging in Wireless Rechargeable Sensor Networks

Yao, Ke.; Jiang, Jehn-Ruey; Tsai, Chung Hsien; Wu, Zong Syun

doi:10.3390/s17081918

Cited by 4 publications

(1 citation statement)

References 22 publications

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“…Efficient wireless energy transmission technology in wireless rechargeable sensor networks (WRSNs) has developed rapidly for many years (Clerckx et al, 2019;Mudulia, L., Mishrab, D. P., & Jana, K., 2018;Liu, X., Guo, Y., Li, W., Hua, M., & Ding, E., 2018;Yao, K. H., Jiang, J. R., Tsai, C. H., & Wu, Z. S., 2017), which addresses the problems of charging, lifetime extension, and energy renewal between different devices. Recently, current research on WRSNs has focused mainly on the design and scheduling of wireless charging vehicles (WCVs) (Xu, C. J., Cheng, R. H., & Wu, T. K., 2018;Zhong et al, 2017;.…”

Section: Introductionmentioning

confidence: 99%

An Opportunistic Charger Recollection Algorithm for Wireless Rechargeable Sensor Networks

Chen

2023

International Journal of Grid and High Performance Computing

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Wireless rechargeable sensor networks (WRSNs) have received a lot of attention due to the development of wireless charging technology. Recently, a new solution of wireless charging vehicle (WCV) for WRSNs with separable charger array equipped with multiple chargers was suggested. By this method, each charger can be unloaded to serve one sensor, while the WCV can work in a very efficient way because it needs not to stay on site and can continue to perform its assigned task. But this solution created a new problem that is how to recollect these chargers for reusing when their charging services are finished. In previous research, however, the recollecting strategy has seldom been considered. In this work, an effectively opportunistic charger recollection algorithm (OCRA) are proposed. Simulation results indicate that OCRA has outperformed previous algorithms in many aspects.

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Section: Introductionmentioning

confidence: 99%

An Opportunistic Charger Recollection Algorithm for Wireless Rechargeable Sensor Networks

Chen

2023

International Journal of Grid and High Performance Computing

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Prolonging lifetime for wireless rechargeable sensor networks through sleeping and charging scheduling

Wang

Lin

et al. 2020

Int J Communication

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Summary Prolonging network lifetime is a fundamental requirement in wireless sensor network (WSN). Existing charging scheduling algorithms suffer from high node redundancy and energy consumption issues. In this paper, we study WSN charging problem from the perspectives of energy conservation combined with energy replenishment scheduling. Firstly, we detect the redundant nodes whose energy is wasted in the network functionality and develop a K‐covering redundant nodes sleeping scheduling algorithm (KRSS) for reducing energy. Secondly, we employed multiple wireless charging vehicles (WCVs) for energy replenishment and optimize the charging scheduling algorithm to prevent any exhaustion of nodes, and we proposed a distance and energy–oriented charging scheduling algorithm (DECS) with multiple WCVs. Simulation experiments are conducted to show the advantages of the proposed KRSS+DECS, confirming that our scheme is capable of removing redundant nodes, lowering node failures, and prolonging network lifetime.

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Beamforming Optimization in Internet of Things Applications Using Robust Swarm Algorithm in Conjunction with Connectable and Collaborative Sensors

Hasan

Al‐Rizzo

2020

Sensors

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The integration of the Internet of Things (IoT) with Wireless Sensor Networks (WSNs) typically involves multihop relaying combined with sophisticated signal processing to serve as an information provider for several applications such as smart grids, industrial, and search-and-rescue operations. These applications entail deploying many sensors in environments that are often random which motivated the study of beamforming using random geometric topologies. This paper introduces a new algorithm for the synthesis of several geometries of Collaborative Beamforming (CB) of virtual sensor antenna arrays with maximum mainlobe and minimum sidelobe levels (SLL) as well as null control using Canonical Swarm Optimization (CPSO) algorithm. The optimal beampattern is achieved by optimizing the current excitation weights for uniform and non-uniform interelement spacings based on the network connectivity of the virtual antenna arrays using a node selection scheme. As compared to conventional beamforming, convex optimization, Genetic Algorithm (GA), and Particle Swarm Optimization (PSO), the proposed CPSO achieves significant reduction in SLL, control of nulls, and increased gain in mainlobe directed towards the desired base station when the node selection technique is implemented with CB.

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Evolutionary Beamforming Optimization for Radio Frequency Charging in Wireless Rechargeable Sensor Networks

Cited by 4 publications

References 22 publications

An Opportunistic Charger Recollection Algorithm for Wireless Rechargeable Sensor Networks

An Opportunistic Charger Recollection Algorithm for Wireless Rechargeable Sensor Networks

Prolonging lifetime for wireless rechargeable sensor networks through sleeping and charging scheduling

Beamforming Optimization in Internet of Things Applications Using Robust Swarm Algorithm in Conjunction with Connectable and Collaborative Sensors

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