Grouping Reduces Energy Cost in Directionally Rechargeable Wireless Vehicular and Sensor Networks

• Published in: IEEE transactions on vehicular technology 2023-08, Vol.72 (8), p.1-12
• Main Authors: Liang, Yuzhu, Yin, Mujun, Zhang, Yilin, Wang, Wenhua, Jia, Weijia, Wang, Tian
• Format: Article
• Language: English
• Subjects: Collaboration; Costs; directional recharging; Energy consumption; Energy costs; Greedy algorithms; grouping recharging; Inductive charging; Linear programming; Optimization; Recharging; Sensors; Trajectory; Trajectory planning; wireless charging vehicle; Wireless communication; Wireless networks; Wireless power transmission; Wireless sensor networks
• ISSN: 0018-9545; 1939-9359
• DOI: 10.1109/TVT.2023.3259683

The use of Wireless Charging Vehicles (WCVs) to wirelessly recharge sensors is a promising but not yet fully developed technology. The existing WCV trajectory planning schemes either fail to consider the directional characteristics of wireless recharging or fail to jointly optimise the mobile feature and the one-to-many feature. The objective of this paper is to find the optimal recharging scheme to minimise the energy costs of WCVs (recharging cost and mobile cost) in rechargeable networks. While recharging, the recharging efficiency has a trade-off between the distance and recharging angle. For the recharging distance, if the WCV comes close to the sensors, the recharging efficiency is high, but the entire recharging trajectory of the WCV will be long and vice versa. For the recharging angle, if the recharging deflection angle is small, the recharging efficiency is high, but the calculation complexity will be high and vice versa. To solve this problem, we prove that the recharging group can reduce mobile costs. Based on this idea, we optimise the recharging trajectory of the WCV to reduce the mobile energy consumption. The optimal recharging group generation problem is discussed, and the problem is proven to be NP-hard. We propose a greedy recharging group generation algorithm with an approximate ratio of \text{ln} \, N, where N is the number of sensors. On this basis, we propose a linear programming equation to minimise the recharging delay of the recharging group to reduce the energy cost during recharging. Experiments show that the number of recharging groups generated by this scheme is 24.5% less than the circle coverage baseline method on average. The energy consumption is reduced by 49.8% on average compared with one-to-one recharging.