Drawing up the most reasonable charging schedule is one of the most important challenges to be solved in wireless rechargeable sensor networks (WRSNs).
However, in existing on-demand charging schemes using multicriteria, it leaves space for efficient combination of multicriteria in the proactive charging process as well as in determination of charging location and charging time.
To solve this problem, Ri Man Gun, an institute head at the Faculty of Communications, has proposed a novel charging scheduling scheme called eIFVT (exploiting an Integrated FAHP-VWA-TOPSIS).
The eIFVT first calculates the exact weights of multicriteria characterizing the sensor nodes including charging request nodes using FAHP-VWA. These weights are then used to select the most suitable next-to-be-charged nodes and future potential-to-be-bottlenecked nodes with TOPSIS and to determine the partial charging time of the on-demand charging scheme adaptively.
The extensive simulation results show that the eIFVT greatly improves the charging and network performance for various metrics compared with existing schemes.
For more information, please refer to his paper “eIFVT: Exploiting an Integrated FAHP-VWA-TOPSIS in Whole-Process of On-Demand Charging Scheduling for WRSNs” in “IEEE SYSTEMS JOURNAL” (SCI).
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