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Wireless Rechargeable Sensor Networks 2020-2022

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A special issue of Energies (ISSN 1996-1073). This special issue belongs to the section "A1: Smart Grids and Microgrids".

Deadline for manuscript submissions: closed (15 December 2022) | Viewed by 6781

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Prof. Dr. Chang Wu Yu

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Department of Computer Science and Information Engineering, Chung Hua University, Hsinchu City 300, Taiwan
Interests: theoretical and fundamental problems in wireless sensor networks; algorithms in wireless sensor networks; graph algorithms
Special Issues, Collections and Topics in MDPI journals

Dr. Naveen Chilamkurti

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Department of Computer Science and Information Technology, La Trobe University, Melbourne, VIC 3086, Australia
Interests: network security; CPS; sensor network; IoT; AI-based information processing
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Wireless sensor networks have recently attracted a great deal of attention due to their various applications in many fields. Due to their limited power consumption, these sensor nodes may experience power shortages and thus lead to many problems, including network disconnection. Most previous methods focused on providing energy-saving strategies to elevate the lifetime of sensor networks. Another aggressive but different approach is to wirelessly re-charge the sensor nodes to increase the lifetime of the sensor networks.

This Special Issue, entitled “Wireless Rechargeable Sensor Networks”, invites articles that address state-of-the-art technologies and new developments for wireless rechargeable sensor networks (WRSNs).

Articles which deal with the latest hot topics in WRSNs are particularly encouraged, such as charger deployment, charger scheduling, wireless energy transfer, mobile charger design, energy-harvesting techniques, and energy provisioning. In addition, articles which discuss protocols, algorithms, and optimization in WRSN are of particular interest.

Prof. Dr. Chang Wu Yu
Dr. Naveen Chilamkurti
Guest Editors

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Keywords

charging scheduling
wireless energy transfer techniques
energy-harvesting technique
charger and charging pad deployment
protocol design
mobile charger design
energy provisioning
wireless sensor networks
flying sensor networks

Published Papers (3 papers)

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27 pages, 5372 KiB

Open AccessArticle

Collaborative Charging Scheduling of Hybrid Vehicles in Wireless Rechargeable Sensor Networks

by Jing-Jing Chen and Chang-Wu Yu

Energies 2022, 15(6), 2256; https://doi.org/10.3390/en15062256 - 19 Mar 2022

Cited by 3 | Viewed by 1369

Abstract

Wireless rechargeable sensor networks (WRSN) are utilized in environmental monitoring, traffic video surveillance, medical services, etc. In most existing schemes, WRSNs provide sustainable energy for sensor nodes by employing one or more wireless charging vehicles (WCVs). However, two essential drawbacks, regional limitations and traveling speed limitations, constrain these schemes when applied in hostile and large-scale environments. On the other hand, benefiting from the intrinsic flexibility, high flight speed, low cost, and small size of drones, some works have used drones to charge sensor nodes. However, suffering from limited battery capacities, it is also hard to only use drones in large-scale WRSNs. To overcome the drawbacks of WCVs and drones, we proposed a novelty wireless charging system that deploys WCV, WCV-carried drones, and wireless charging pads (pads) in a large-scale wireless sensor network. Based on this new wireless charging system, we first formulated a pad deployment problem for minimizing the total number of pads subject to each sensor in the pad region that only can be charged by drones. In this work, three near-optimal algorithms, i.e., greedy, K-mean, and static, for the pad deployment problem are proposed. Then, to form a sustainable WRSN, we elucidated the collaborative charging scheduling problem with the deadlines of sensors. To guarantee the maximum number of sensors to be charged before the deadlines, we also presented an approximation algorithm to find the collaborative charging scheduling of WCV and WCV-carried drones with the help of pads based on the three deployment pad schemes. Through extensive simulations, we demonstrate the effectiveness of the proposed deployment pad schemes. and that the number of pads obtained by the greedy and K-mean scheme was generally lower than that of the static scheme with respect to network density, WCV region, and flight range. Then, we also examined the proposed collaborative charging scheduling scheme by extensive simulations. The results were compared and showed the effectiveness of the proposed schemes in terms of lifetime, the percentage of nodes being charged in time, the average move time of drones, the percentage of nodes being charged late by the drones, and the charge efficiency of all vehicles under different traffic loads. Related statistical analyses showed that the percentage of nodes being charged in time and the percentage of nodes being charged late based on the greedy and K-mean schemes were slightly better than those of the static scheme, but the charge efficiency of drones of the static scheme was significantly superior to that of the K-mean scheme under a busy network. Full article

(This article belongs to the Special Issue Wireless Rechargeable Sensor Networks 2020-2022)

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14 pages, 553 KiB

Open AccessArticle

Improving the Convergence Period of Adaptive Data Rate in a Long Range Wide Area Network for the Internet of Things Devices

by Khola Anwar, Taj Rahman, Asim Zeb, Yousaf Saeed, Muhammad Adnan Khan, Inayat Khan, Shafiq Ahmad, Abdelaty Edrees Abdelgawad and Mali Abdollahian

Energies 2021, 14(18), 5614; https://doi.org/10.3390/en14185614 - 07 Sep 2021

Cited by 14 | Viewed by 1735

Abstract

A Long-Range Wide Area Network (LoRaWAN) is one of the most efficient technologies and is widely adopted for the Internet of Things (IoT) applications. The IoT consists of massive End Devices (EDs) deployed over large geographical areas, forming a large environment. LoRaWAN uses an Adaptive Data Rate (ADR), targeting static EDs. However, the ADR is affected when the channel conditions between ED and Gateway (GW) are unstable due to shadowing, fading, and mobility. Such a condition causes massive packet loss, which increases the convergence time of the ADR. Therefore, we address the convergence time issue and propose a novel ADR at the network side to lower packet losses. The proposed ADR is evaluated through extensive simulation. The results show an enhanced convergence time compared to the state-of-the-art ADR method by reducing the packet losses and retransmission under dynamic mobile LoRaWAN network. Full article

(This article belongs to the Special Issue Wireless Rechargeable Sensor Networks 2020-2022)

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21 pages, 4200 KiB

Open AccessArticle

Enabling a Battery-Less Sensor Node Using Dedicated Radio Frequency Energy Harvesting for Complete Off-Grid Applications

by Timothy Miller, Stephen S. Oyewobi, Adnan M. Abu-Mahfouz and Gerhard P. Hancke

Energies 2020, 13(20), 5402; https://doi.org/10.3390/en13205402 - 16 Oct 2020

Cited by 5 | Viewed by 2376

Abstract

The large-scale deployment of sensor nodes in difficult-to-reach locations makes powering of sensor nodes via batteries impractical. Besides, battery-powered WSNs require the periodic replacement of batteries. Wireless, battery-less sensor nodes represent a less maintenance-intensive, more environmentally friendly and compact alternative to battery powered sensor nodes. Moreover, such nodes are powered through wireless energy harvesting. In this research, we propose a novel battery-less wireless sensor node which is powered by a dedicated 4 W EIRP 920 MHz radio frequency (RF) energy device. The system is designed to provide complete off-grid Internet of Things (IoT) applications. To this end we have designed a power base station which derives its power from solar PV panels to radiate the RF energy used to power the sensor node. We use a PIC32MX220F32 microcontroller to implement a CC-CV battery charging algorithm to control the step-down DC-DC converter which charges lithium-ion batteries that power the RF transmitter and amplifier, respectively. A 12 element Yagi antenna was designed and optimized using the FEKO electromagnetic software. We design a step-up converter to step the voltage output from a single stage fully cross-coupled RF-DC converter circuit up to 3.3 V. Finally, we use the power requirements of the sensor node to size the storage capacity of the capacitor of the energy harvesting circuit. The results obtained from the experiments performed showed that enough RF energy was harvested over a distance of 15 m to allow the sensor node complete one sense-transmit operation for a duration of 156 min. The Yagi antenna achieved a gain of 12.62 dBi and a return loss of −14.11 dB at 920 MHz, while the battery was correctly charged according to the CC-CV algorithm through the control of the DC-DC converter. Full article

(This article belongs to the Special Issue Wireless Rechargeable Sensor Networks 2020-2022)

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