EDTP: Energy-Density-based Trajectory Planning for Wireless Sensor Networks With Mobile Collectors
Hong-mei Wang, Heejung Byun, Zhaodong Liu · Journal of Institute of Control Robotics and Systems · 2024
Mobile collectors (MCs) have been utilized to enhance the performance of wireless sensor networks (WSNs) in recent years. However, there are major limitations, particularly in latency-bound applications. The traveling paths taken by MCs have a significant impact on the time required for data collection. To regulate the paths of MCs, we propose a hybrid approach that MCs only visit cluster heads (CHs), and nodes that are not CHs forward data to the nearest CHs through a single-hopping. The energy difference and density of global sensor nodes are introduced to select CHs. To shorten the trajectory of MCs, the K-Dimension Tree Grouping algorithm (KDTG) is proposed to group CHs with the highest geographical similarity. The simulation results verify that the proposed algorithm has a broad range of applicability and robust stability, making it an asset for WSNs of varying scales and application scenarios.