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

Abstract

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.

Priority‐aware intelligent device access management for carbon footprint monitoring in sustainable cites and society

“…A similar proof can be found in Appendix A. □ C 3 can be converted to the stability constraint of virtual priority deficit queue F i (t ) that is, C 3 is satisfied when F i (t ) is mean rate stable [5]. Define the Lyapunov function as…”

“…C 3 can be converted to the stability constraint of virtual priority deficit queue $$F_i(t)$$ that is, C 3 is satisfied when $$F_i(t)$$ is mean rate stable [5]. Define the Lyapunov function as $$$$\begin{align} L(\Theta (t))=\frac{1}{2} \sum _{u_i \in \mathcal {U}} F_i^2(t) \end{align}$$$$…”

“…The fifth generation (5G) mobile communication technology provides a feasible solution for real‐time data transmission of carbon footprint monitoring [4]. 5G possesses the advantages of low latency, high reliability, and large bandwidth, which can be integrated with edge computing to enable data uploading, processing, and analysis through cloud‐edge‐device collaboration [5]. However, massive device access of carbon footprint monitoring evokes access collision due to limited available spectrum, which further worsens access delay and service priority guarantee.…”

Joint mission planning and spectrum resources optimization for multi‐UAV reconnaissance

“…Authors in [8] used a UAV-aided communication network to serve randomly moving users and proposed an adaptive deployment strategy. With the UAV being used to collect data of low-power ground sensor nodes in an obstacle environment, the completion time can be minimized by jointly optimizing the UAV trajectory and collection sequence of sensor nodes [9,10]. UAVs have significant advantages in high mobility, and a rational trajectory can effectively improve the quality of the network.…”

OADC: An Obstacle-Avoidance Data Collection Scheme Using Multiple Unmanned Aerial Vehicles

“…However, these studies did not consider the existence of obstacles in the paths of UAVs, whereas there can be many obstacles (e.g., buildings, mountains, big trees, and no-fly zone areas) in a UAV's trajectory that need to be avoided when it flies from one sensor to another. Although some studies considered obstacles in the UAV trajectories [16][17][18][19][20][21], they did not consider the UAV path as the Hamiltonian path, which is impractical because UAVs are battery-constrained devices and need to return to the base station (BS) to recharge their batteries after a given period of data collection.…”