Event Detection Using Unmanned Aerial Vehicles: Ordered versus Self-organized Search

Event coverage problem in wireless sensor networks has drawn the interest of several researchers. While most of the previous work has been on static or ground mobile sensor networks, airborne sensor networks have also found its way into several civil and military applications such as environmental monitoring or battlefield assistance. In this work, we study the mobility pattern of an Unmanned Aerial Vehicle (UAV) network and explore the benefits of ordered and self-organized random mobility in terms of event detection performance, when the event is stationary and event duration is finite. Specifically, we compare the performance of a UAV network flying in parallel formation to a simple, distributed, locally-interactive coverage-based mobility model as well as legacy mobility models such as random walk and random direction. We study the event detection probability of the UAV network with both perfect and imperfect sensing capabilities. Our results show that when the timing constraints are highly stringent or when the UAV sensors have a high miss probability, flying in formation cannot achieve a high detection probability and a self-organized distributed mobility model is more effective.