Probabilistic On-Demand Charging Scheduling for ISAC-Assisted WRSNs with Multiple Mobile Charging Vehicles

Qaisar, Muhammad Umar Farooq1; Yuan, Weijie1; Bellavista, Paolo2; Han, Guangjie3; Zakariyya, Rabiu Sale1; Ahmed, Adeel4

10.1109/GLOBECOM54140.2023.10437255

2023

IEEE Conference on Global Communications (IEEE GLOBECOM) - Intelligent Communications for Shared Prosperity

2334-0983

2576-6813

IEEE CONFERENCE ON GLOBAL COMMUNICATIONS, GLOBECOM

DEC 04-08, 2023

null,Kuala Lumpur,MALAYSIA

345 E 47TH ST, NEW YORK, NY 10017 USA

IEEE

The internet of things (IoT) based wireless sensor networks (WSNs) face an energy shortage challenge that could be overcome by the novel wireless power transfer (WPT) technology. The combination of WSNs and WPT is known as wireless rechargeable sensor networks (WRSNs), with the charging efficiency and charging scheduling being the primary concerns. Therefore, this paper proposes a probabilistic on-demand charging scheduling for integrated sensing and communication (ISAC)-assisted WRSNs with multiple mobile charging vehicles (MCVs) that addresses three parts. First, it considers the four attributes with their probability distributions to balance the charging load on each MCV. The distributions are residual energy of charging node, distance from MCV to charging node, degree of charging node, and charging node betweenness centrality. Second, it considers the efficient charging factor strategy to partially charge network nodes. Finally, it employs the ISAC concept to efficiently utilize the wireless resources to reduce the traveling cost of each MCV and to avoid the charging conflicts between them. The simulation results show that the proposed protocol outperforms cutting-edge protocols in terms of energy usage efficiency, charging delay, survival rate, and travel distance.

Wireless rechargeable sensor networks on-demand partial charging ISAC mobile charging vehicles

第一 ; 通讯

英语

CPCI-S

National Natural Science Foundation of China[62101232]

Engineering ; Telecommunications

Engineering, Electrical & Electronic ; Telecommunications

WOS:001178562006076

Web of Science

1.Southern Univ Sci & Technol, Dept Elect & Elect Engn, Shenzhen, Peoples R China
2.Univ Bologna, Dept Comp Sci & Engn, Bologna, Italy
3.Hohai Univ, Dept Internet Things Engn, Changzhou, Jiangsu, Peoples R China
4.Univ Sci & Technol China, Sch Comp Sci & Technol, Hefei, Peoples R China

Qaisar, Muhammad Umar Farooq,Yuan, Weijie,Bellavista, Paolo,et al. Probabilistic On-Demand Charging Scheduling for ISAC-Assisted WRSNs with Multiple Mobile Charging Vehicles[C]. 345 E 47TH ST, NEW YORK, NY 10017 USA:IEEE,2023.