Abstract
In a wireless sensor network, the sensing and data transmission for sensors will cause energy depletion, which will lead to the inability to complete the tasks. To solve this problem, wireless rechargeable sensor networks (WRSNs) have been developed to extend the lifetime of the entire network. In WRSNs, a mobile charging robot (MR) is responsible for wireless charging each sensor battery and collecting sensory data from the sensor simultaneously. Thereby, MR needs to traverse along a designed path for all sensors in the WRSNs. In this paper, dual-side charging strategies are proposed for MR traversal planning, which minimize the MR traversal path length, energy consumption, and completion time. Based on MR dual-side charging, neighboring sensors in both sides of a designated path can be wirelessly charged by MR and sensory data sent to MR simultaneously. The constructed path is based on the power diagram according to the remaining power of sensors and distances among sensors in a WRSN. While the power diagram is built, charging strategies with dual-side charging capability are determined accordingly. In addition, a clustering-based approach is proposed to improve minimizing MR moving total distance, saving charging energy and total completion time in a round. Moreover, integrated strategies that apply a clustering-based approach on the dual-side charging strategies are presented in WRSNs. The simulation results show that, no matter with or without clustering, the performances of proposed strategies outperform the baseline strategies in three respects, energy saving, total distance reduced, and completion time reduced for MR in WSRNs.
Highlights
With the technological progress of the Internet of things, the deployment of sensors has increased demand widely in many fields, such as used in smart city, industry, precision agriculture, and so on
Total energy consumption: including the energy consumptions measured in Joules for mobile charging robot (MR) moving, MR charging for all sensors, and MR receiving sensory data from all sensors at one round
The completion time: including the total moving time measured in seconds for MR moving and charging at one round
Summary
With the technological progress of the Internet of things, the deployment of sensors has increased demand widely in many fields, such as used in smart city, industry, precision agriculture, and so on. The development of sensors has the trend toward low-power consumption of wireless communications and computation. Researchers have proposed various powerful strategies to extend the operating time of sensors, such as wireless recharging strategies [1,2], reducing sensor consumption techniques, and harvesting energy from the environment, i.e., solar energy [3,4]. Power converting from the source of external energy, such as solar energy, into electrical energy is unreliable due to the inefficiency of the power conversion and uncertainty of the environment. By reducing the energy consumption for sensors, the network lifetime can be extended, but the sensors energy cannot be prevented from being depleted in a long time. To gain better performance, the wireless recharging strategies to supply the sensors power for the wireless rechargeable sensor network (WRSN) [5,6] are recommended
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