ODT: Optimal deadline-based trajectory for mobile sinks in WSN: A decision tree and dynamic programming approach

Recent studies have shown that utilizing a mobile sink (MS) to harvest and carry data from a wireless sensor network (WSN) can enhance network operations and increase the network lifetime. Since a significant portion of sensor nodes’ energy is consumed for data transmission to MS, the specific trajectory has a profound influence on the lifetime of WSN. In this paper, we study the problem of controlling sink mobility in deadline-based and event-driven applications to achieve maximum network lifetime. In these applications, when a sensor node captures an event, it should determine a visiting time and a deadline with respect to the amount of captured data and the type of event. MS then has to determine its trajectory to harvest data from active sensor nodes in single hop transmission so that the network lifetime is increased. We show that this problem is NP-hard when there are no predefined structures like a virtual grid or rendezvous points in the network. We propose an algorithm based on a decision tree and dynamic programming to approximately determine an optimal deadline-based trajectory (ODT). ODT is obtained by considering the geographical positions of active sensor nodes and the properties of captured events. The effectiveness of our approach is validated via the extensive number of simulation runs and comparison with other algorithms.