Towards mobility as a network control primitive
Proceedings of the 5th ACM international symposium on Mobile ad hoc networking and computing
On the Use of Nodes with Controllable Mobility for Conserving Power in MANETs
ICDCSW '06 Proceedings of the 26th IEEE International ConferenceWorkshops on Distributed Computing Systems
Enhancing WLAN Capacity by Strategic Placement of Tetherless Relay Points
IEEE Transactions on Mobile Computing
Approximation Algorithms for Orienteering and Discounted-Reward TSP
SIAM Journal on Computing
Maintaining Optimal Communication Chains in Robotic Sensor Networks using Mobility Control
Mobile Networks and Applications
Experimental characterization of 802.11n link quality at high rates
Proceedings of the fifth ACM international workshop on Wireless network testbeds, experimental evaluation and characterization
From ground to aerial communication: dissecting WLAN 802.11n for the drones
Proceedings of the 8th ACM international workshop on Wireless network testbeds, experimental evaluation & characterization
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Search and rescue missions are entering a new era with the advent of small scale unmanned aerial vehicles (UAVs) with communication capabilities and embedded cameras. Yet, delivering high resolution images of the supervised surface to rescuers is time-critical. To help resolving this problem, we study how UAVs can take advantage of their controlled mobility to derive the optimum strategy for data transmission. Driven by real-world aerial experiments with both airplanes and quadrocopters equipped with 802.11n technology, we show that the UAV should not necessarily transmit as soon as a wireless link is established. Instead, it should wait until it reaches a suitable distance to the receiving UAV, only to transmit when the time to move to the new location and transmit is minimal. We then apply the principle of delayed gratification, where the UAV attempts to solve the tradeoff between postponing until it reaches this minimum and the impatience to deliver as much data as soon as possible, before any physical damage on-the-fly may occur. Our empirical-driven simulations demonstrate that the optimal distance of transmission greatly depends on the interplay of actual throughput, data size, UAV cruise speed, and failure rate, and that state-of-the-art UAVs can already benefit from our approach.