TY - GEN
T1 - Multiple Mobile Chargers-assisted Efficient Green Energy Wireless Charging for WRSNs
AU - Ding, Jun
AU - Liu, Xilong
AU - Ansari, Nirwan
N1 - Publisher Copyright: © 2022 IEEE.
PY - 2022
Y1 - 2022
N2 - With the development of Internet of Things (IoT), wireless rechargeable sensor networks (WRSNs) have been widely applied in modern society. There has a greater demand for green and efficient remote wireless charging to power the wireless sensor nodes (SNs) in WRSNs. However, few has tackled the wireless charging efficiency problem that can achieve the low dead SNs percentage (DSP) in far-field wireless charging. Existing far-field wireless charging schemes cannot meet the energy supply requirement of large-scale SNs. Therefore, this work proposes the multiple mobile chargers (MCs)-assisted efficient green energy wireless charging for WRSNs. Firstly, according to the existing Density-Based Spatial Clustering of Applications with Noise (DBSCAN) algorithm, the area not covered by the wireless charging base stations (BSs) is divided into multiple irregular-shape sub-regions. Then, we leverage multiple MCs to wirelessly charge the SNs located in these sub-regions. Finally, we propose the Minimal chArging grouPings (MAP) algorithm to minimize the number of the MCs' anchor points (APs) and efficiently charge the SNs. The simulation results validate that our proposed algorithm can effectively improve the wireless charging energy efficiency and reduce the DSP.
AB - With the development of Internet of Things (IoT), wireless rechargeable sensor networks (WRSNs) have been widely applied in modern society. There has a greater demand for green and efficient remote wireless charging to power the wireless sensor nodes (SNs) in WRSNs. However, few has tackled the wireless charging efficiency problem that can achieve the low dead SNs percentage (DSP) in far-field wireless charging. Existing far-field wireless charging schemes cannot meet the energy supply requirement of large-scale SNs. Therefore, this work proposes the multiple mobile chargers (MCs)-assisted efficient green energy wireless charging for WRSNs. Firstly, according to the existing Density-Based Spatial Clustering of Applications with Noise (DBSCAN) algorithm, the area not covered by the wireless charging base stations (BSs) is divided into multiple irregular-shape sub-regions. Then, we leverage multiple MCs to wirelessly charge the SNs located in these sub-regions. Finally, we propose the Minimal chArging grouPings (MAP) algorithm to minimize the number of the MCs' anchor points (APs) and efficiently charge the SNs. The simulation results validate that our proposed algorithm can effectively improve the wireless charging energy efficiency and reduce the DSP.
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U2 - 10.1109/APCC55198.2022.9943772
DO - 10.1109/APCC55198.2022.9943772
M3 - Conference contribution
T3 - APCC 2022 - 27th Asia-Pacific Conference on Communications: Creating Innovative Communication Technologies for Post-Pandemic Era
SP - 384
EP - 389
BT - APCC 2022 - 27th Asia-Pacific Conference on Communications
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 27th Asia-Pacific Conference on Communications, APCC 2022
Y2 - 19 October 2022 through 21 October 2022
ER -