Completion time minimization for UAV enabled data collection with communication link constrained

This paper studies unmanned aerial vehicles (UAV) enabled industrial Internet of Things while a UAV dispatched to collect data of low‐power ground sensor nodes (SNs) in multi‐obstacle environment. The authors aim to minimize the completion time while satisfying the communication link constraints of...

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Veröffentlicht in:IET communications 2022-06, Vol.16 (10), p.1025-1040
Hauptverfasser: Wu, Binbin, Guo, Daoxing, Zhang, Bangning, Zhang, Xiaokai, Wang, Hongbin, Wang, Haichao, Jiang, Hao
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Sprache:eng
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Zusammenfassung:This paper studies unmanned aerial vehicles (UAV) enabled industrial Internet of Things while a UAV dispatched to collect data of low‐power ground sensor nodes (SNs) in multi‐obstacle environment. The authors aim to minimize the completion time while satisfying the communication link constraints of each SN and obstacle avoidance, data collection requirements etc. To this end, the authors first formulate the completion time minimization problem by jointly optimizing the UAV trajectory and collection sequence of SNs. The problem is difficult to be optimally solved, as it is non‐convex. To tackle this problem, the authors first transform the original problem to a Traveling Salesman Problem‐like (TSP‐like) problem based on a hover point that can naturally satisfy the communication link constraints of data collection. The dynamic programming (DP) algorithm to figure out the order in which the UAV collects each SN, which gives the initial path of the UAV traversing each SN from the beginning point to the end point. Next, the authors consider the general scenarios of data collection tasks where the UAV also communicates while flying. The authors construct an equivalent problem with integer variable constraints for the original problem with indicative function constraints. The authors rewrite the non‐convex constraints of the equal problem by introducing slack variables and leveraging the SCA, and add the discrete region threat constraints for the traditional path discretization method. Finally, the simulation results verify the effectiveness of the proposed algorithm under different parameter configurations.
ISSN:1751-8628
1751-8636
DOI:10.1049/cmu2.12378