91 research outputs found
Joint Trajectory-Task-Cache Optimization in UAV-Enabled Mobile Edge Networks for Cyber-Physical System
This paper studies an unmanned aerial vehicle (UAV)-enabled mobile edge network for Cyber-Physical System (CPS), where UAV with fixed-wing or rotary-wing is dispatched to provide communication and mobile edge computing (MEC) services to ground terminals (GTs). To minimize the energy consumption so as to extend the endurance of the UAV, we intend to jointly optimize its 3D trajectory and the task-cache strategies among GTs to save the energies spent on flight propulsion and GT tasks. Such joint trajectory-task-cache problem is difficult to be optimally solved, as it is non-convex and involves multiple constraints. To tackle this problem, we reformulate the optimizing of task offloading and cache into two tractable linear program (LP) problems, and the optimizing of UAV trajectory into three convex Quadratically Constrained Quadratically Program (QCQP) problems on horizontal trajectory, vertical trajectory and flight time of the UAV respectively. Then a block coordinate descent algorithm is proposed to iteratively solve the formed sub-problems through a successive convex optimization (SCO) process. A high-quality sub-optimal solution to the joint problem then will be obtained, after the algorithm converging to a prescribed accuracy. The numerical results show the proposed solution significantly outperforms the baseline solution
3D Trajectory Design for UAV-Assisted Oblique Image Acquisition
In this correspondence, we consider a new unmanned aerial vehicle
(UAV)-assisted oblique image acquisition system where a UAV is dispatched to
take images of multiple ground targets (GTs). To study the three-dimensional
(3D) UAV trajectory design for image acquisition, we first propose a novel
UAV-assisted oblique photography model, which characterizes the image
resolution with respect to the UAV's 3D image-taking location. Then, we
formulate a 3D UAV trajectory optimization problem to minimize the UAV's
traveling distance subject to the image resolution constraints. The formulated
problem is shown to be equivalent to a modified 3D traveling salesman problem
with neighbourhoods, which is NP-hard in general. To tackle this difficult
problem, we propose an iterative algorithm to obtain a high-quality suboptimal
solution efficiently, by alternately optimizing the UAV's 3D image-taking
waypoints and its visiting order for the GTs. Numerical results show that the
proposed algorithm significantly reduces the UAV's traveling distance as
compared to various benchmark schemes, while meeting the image resolution
requirement
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