A1 Journal article (refereed)
Adaptive Mobile Recharge Scheduling With Rapid Data Sharing in Wireless Rechargeable Networks (2024)


Huang, W., Zhao, Z., Wang, Z., Min, G., Chang, Z., Fu, L., & Duan, H. (2024). Adaptive Mobile Recharge Scheduling With Rapid Data Sharing in Wireless Rechargeable Networks. IEEE Transactions on Mobile Computing, 23(4), 3092-3105. https://doi.org/10.1109/TMC.2023.3273213


JYU authors or editors


Publication details

All authors or editorsHuang, Wenjie; Zhao, Zhiwei; Wang, Zi; Min, Geyong; Chang, Zheng; Fu, Luwei; Duan, Hancong

Journal or seriesIEEE Transactions on Mobile Computing

ISSN2161-9875

eISSN1536-1233

Publication year2024

Publication date05/05/2023

Volume23

Issue number4

Pages range3092-3105

PublisherIEEE

Publication countryUnited States

Publication languageEnglish

DOIhttps://doi.org/10.1109/TMC.2023.3273213

Publication open accessNot open

Publication channel open access


Abstract

The recent breakthrough in Wireless Power Transfer (WPT) provides a promising way to prolong network lifetime by employing a charging vehicle to replenish energy. Data transmissions from nodes typically happen in response to physical sensory events, leading to time-varying energy consumption. To improve charging efficiency, the existing schemes collect energy information by employing a data-gathering vehicle or data collection protocol. However, in duty cycle networks, these schemes either incur extra vehicles or high data collection delay. To solve this problem, we propose an mobile adaptive charging scheme with rapid data sharing (rShare), which establishes multi-layer collection trees and collects overall energy data to the vehicle. A spatial predicted active sending (SPAS) algorithm is proposed for distant nodes to actively estimate the future position and transmit their data to cover potential positions of the charging vehicle, which significantly reduces data collection delay. We also propose an estimated time of arrival (ETA)-aware scheme based on the TSP Nearest Neighbor algorithm that updates the charging path based on the collected data. Extensive simulation results demonstrate that our scheme outperforms the state-of-the-arts in terms of dead node avoidance with less communication overhead.


Keywordswireless networksmobile communication networkspower transmission


Contributing organizations


Ministry reportingYes

Reporting Year2024

Preliminary JUFO rating3


Last updated on 2024-03-07 at 20:06