A non-disruptive multi-objective charging strategy for WRSN through multi-UAV deployment optimization using a meta-heuristic algorithm

Subject Areas : Computer Engineering and IT

Payman Habibi ¹ , Goran Hassanifard ² , Abdulbaghi Ghaderzadeh ³ , Arez Nosratpour ⁴

1 - Department of Electrical Engineering, Islamic Azad University, Sanandaj Branch, Sanandaj, Iran
2 - هیات علمی
3 - Department of computer engineering, Islamic Azad university sanandaj branch
4 - Department of Electrical Engineering, Islamic Azad University, Sanandaj Branch, Sanandaj, Iran

Received: 2023-10-15 Accepted : 2023-12-09 Published : 2023-12-19

Keywords: Multi-target charging strategy, Wireless Rechargeable Sensor Networks (WRSN), CUAV, K-means, Harris Hawks Optimization (HHO).,

Abstract :

Here, a planning approach for CUAVs movement path and charging schedule of sensor nodes under uncertainty in data transfer rate and energy consumption in nodes with the help of Harris Hawks Optimization (HHO) and gradient-based optimization (GBO) algorithms have been presented. By considering the inequalities and uncertainty in the battery limit and energy consumption of the nodes, we will achieve new scheduling strategies for WRSNs to increase the charging throughput and increase the network lifetime. Initially, with the help of information about the position and remaining energy of the nodes, clustering of the nodes into the number of drones has been done by the K-means method. According to the definition of the multi-purpose function of CUAV and with the help of the proposed algorithms, the routing and charging schedule of each of the drones is planned. In the defined objective function, all uncertainties and inequalities of the network are included for the delay and consumption of energy and battery of the nodes. The simulation was done under MATLAB software. The results showed that the proposed method based on HHO has achieved better solutions in terms of increasing the network lifetime and reducing the delay and optimizing energy consumption.

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