An energy-density-based trajectory planning method for wireless sensor networks with mobile collectors

Mobile collectors (MCs), such as unmanned aerial vehicles (UAVs), play a crucial role in conserving energy and enhancing the longevity of wireless sensor networks (WSNs) compared to static sinks. The implementation of efficient routing algorithms and scheduling mechanisms tailored for MCs is of utmost importance. In response to this challenge, we propose an innovative data collection method called energy- density-based trajectory planning (EDTP) specifically designed for WSNs equipped with MCs. First, we introduce a global energy-difference density optimization scheme (GEDD) to select cluster heads (CHs) responsible for transmitting data to MCs. The selection of CHs aims to balance the energy consumption of nodes, thereby extending the system's lifespan. Second, we propose the K-dimension tree grouping algorithm (KDTG) with high computational efficiency to group CHs based on their geographical similarity. Comparisons with three existing approaches demonstrate that our proposed EDTP method can significantly increase system lifetime and reduce latency.