CRCM: A New Combined Data Gathering and Energy Charging Model for WRSN

• Main Authors: Yuhou Wang, Ying Dong, Shiyuan Li, Hao Wu, Mengyao Cui
• Format: Article
• Language: English
• Published: MDPI AG 2018-08-01
• Series: Symmetry
• Subjects: wireless rechargeable sensor network; energy replenishment; data gathering; dynamic mobile chargers
• Online Access: http://www.mdpi.com/2073-8994/10/8/319

With the development of wireless sensor networks (WSNs), the problem about how to increase the lifecycle of the WSNs is always a hot discussion point, and some researchers have devoted to the ‘energy saving’ to decrease the energy consumption of the sensor nodes by different algorithms. However, the fundamental technique is ‘energy acquiring’ for the battery which can solve the limited capacity problem. In this paper, we study the data gathering and energy charging by a mobile charger (MC) at the same time that most energy consumption can be saved by short communication distance. We have named this as the recharging model-combined recharging and collecting data model on-demand (CRCM). Firstly, the hexagon-based (HB) algorithm is proposed to sort all sensor nodes in the region to make data collecting and energy charging work at the same time. Then we consider both residual energy and geographic position (REGP) of the sensor node to calculate the priority of each cluster. Thirdly, the dynamic mobile charger (DMC) algorithm is proposed to calculate the number of MCs to make sure no sensor node will die in each charging queue. Finally, the simulations show that our REGP algorithm is better than Earliest Deadline First (EDF) and Nearest-Job-Next with Preemption (NJNP), and the DMC plays well when the number of sensor nodes increase.