Journal
IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY
Volume 69, Issue 5, Pages 5562-5569Publisher
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TVT.2020.2982172
Keywords
Internet of things (IoT); internet of drones (IoD); unmanned aerial vehicles (UAV); fog computing; task allocation; flying control; energy consumption; quality of service (QoS)
Categories
Funding
- National Science Foundation [CNS-1814748]
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Fog-aided Internet of Drones (IoD) networks employ fog nodes to provide computing resources for the delay-sensitive tasks offloaded from drones. In IoD networks, drones are launched to complete a journey in which several locations of interest are visited. At each location, a drone collects the ground information, generates computing tasks and offloads them to the fog nodes for processing. In our work, we consider both the task allocation (which distributes tasks to different fog nodes) and the flying control (which adjusts the drone's flying speed) to minimize the drone's journey completion time constrained by the drone's battery capacity and task completion deadlines. We formulate this joint optimization problem as a mixed integer non-linear programming (MINLP) problem. In consideration of the practical scenario that the future task information is difficult to obtain, we design an online algorithm to provide strategies for task allocation and flying control when the drone visits each location without knowing the future. The performances of our proposed online algorithm are demonstrated via extensive simulations.
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