A Combining Strategy of Energy Replenishment and Data Collection in Wireless Sensor Networks

In wireless rechargeable sensor networks, the mobile vehicle (MV) combining energy replenishment and data collection often collects all sensed data, which may lead to data overflow and larger delay. To avoid these defects, we propose a novel data collection policy, where the MV acts as an auxiliary mobile data collector to gather buffered data as much as possible and the base station receives and processes remaining sensed data. As the mobile vehicle acts the data collector and the mobile charger simultaneously, how to scheduling it to minimize energy consumption and improve data transmission performance without network lifetime degradation is a challenge. To address this, some algorithms are proposed under the new policy. First, according to the residual lifetime of nodes, a classic charging algorithm is utilized to dispatch the MV to charge nodes to maximize the network lifetime. After determining the trajectory of the MV, considering data type and buffer state, we divide data collection into two sub-problems: how to collect sensed data from neighbor clusters and roadside clusters respectively. To assign optimal data collection time and select best roadside clusters, some algorithms are proposed which can maximize the sum of normalized saved energy of neighbor clusters and roadside clusters. Finally, we evaluate the performance by simulations. The results show that our proposed algorithms can significantly improve the network performance, such as the delay, data overflow, energy consumption, network lifetime, and throughput.