ISAC-Facilitated Optimal On-demand Mobile Charging Scheme for IoT-based WRSNs

IoT-based wireless sensor networks (WSNs) face significant energy constraints, which can be alleviated by wireless power transfer (WPT) technology. Integrating WPT with WSNs creates wireless rechargeable sensor networks (WRSNs), where optimizing charging efficiency and scheduling is critical. This paper introduces an ISAC-facilitated optimal on-demand mobile charging scheme for IoT-based WRSNs (IOMSN) with three key components. First, it presents an ISAC-assisted prioritized charging queue, incorporating four attributes with probability distributions: residual energy, traffic load, MCV travel time, and direction angle. Second, it provides ISAC-driven estimations of MCV distance, speed, and location to enhance prioritization, thereby optimizing the charging route and potentially reducing travel costs. Third, a time-allocated partial charging model improves charging efficiency. Numerical results show that the proposed protocol outperforms cutting-edge protocols in energy usage efficiency, travel distance, charging delay, and service time.

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Publication Details

Published
2024-12-04
DOI
https://doi.org/10.1145/3636534.3698228
Citations
3
Primary Topic
Energy Harvesting in Wireless Networks
Type
article
Field-Weighted Citation Impact
0.63
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article

ISAC-Facilitated Optimal On-demand Mobile Charging Scheme for IoT-based WRSNs

Muhammad Umar Farooq Qaisar, Chang Liu, Fisseha Teju Wedaj, Guangjie Han et al.
3 citations
Energy Harvesting in Wireless Networks
0.63
article

ISAC-Facilitated Optimal On-demand Mobile Charging Scheme for IoT-based WRSNs

Muhammad Umar Farooq Qaisar, Chang Liu, Fisseha Teju Wedaj, Guangjie Han, Fan Liu, Zhuo Sun
article en
3 citations

Abstract

IoT-based wireless sensor networks (WSNs) face significant energy constraints, which can be alleviated by wireless power transfer (WPT) technology. Integrating WPT with WSNs creates wireless rechargeable sensor networks (WRSNs), where optimizing charging efficiency and scheduling is critical. This paper introduces an ISAC-facilitated optimal on-demand mobile charging scheme for IoT-based WRSNs (IOMSN) with three key components. First, it presents an ISAC-assisted prioritized charging queue, incorporating four attributes with probability distributions: residual energy, traffic load, MCV travel time, and direction angle. Second, it provides ISAC-driven estimations of MCV distance, speed, and location to enhance prioritization, thereby optimizing the charging route and potentially reducing travel costs. Third, a time-allocated partial charging model improves charging efficiency. Numerical results show that the proposed protocol outperforms cutting-edge protocols in energy usage efficiency, travel distance, charging delay, and service time.

Guangdong University of Technology (CN), Hohai University (CN), Northwestern Polytechnical University (CN), Southern University of Science and Technology (CN), Adama Science and Technology University (ET)
Openalex Percentile: Top 30%
Energy Harvesting in Wireless Networks
0.63
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ISAC-Facilitated Optimal On-demand Mobile Charging Scheme for IoT-based WRSNs — Muhammad Umar Farooq Qaisar, Chang Liu, et al. · (2024) | TGRS Research Map | TGRS