Mobility increases the capacity of ad hoc wireless networks
IEEE/ACM Transactions on Networking (TON)
Towards realistic mobility models for mobile ad hoc networks
Proceedings of the 9th annual international conference on Mobile computing and networking
Integrated coverage and connectivity configuration in wireless sensor networks
Proceedings of the 1st international conference on Embedded networked sensor systems
A framework and analysis for cooperative search using UAV swarms
Proceedings of the 2004 ACM symposium on Applied computing
Worst and Best-Case Coverage in Sensor Networks
IEEE Transactions on Mobile Computing
Mobility improves coverage of sensor networks
Proceedings of the 6th ACM international symposium on Mobile ad hoc networking and computing
A community based mobility model for ad hoc network research
REALMAN '06 Proceedings of the 2nd international workshop on Multi-hop ad hoc networks: from theory to reality
Collaborative microdrones: applications and research challenges
Autonomics '08 Proceedings of the 2nd International Conference on Autonomic Computing and Communication Systems
Balancing search and target response in cooperative unmanned aerial vehicle (UAV) teams
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
IEEE Communications Magazine
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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.