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Efficient data processing and computation are essential for the industrialInternet of things (IIoT) to empower various applications, which yet can besignificantly bottlenecked by the limited energy capacity and computationcapability of the IIoT nodes. In this paper, we employ an unmanned aerialvehicle (UAV) as an edge server to assist IIoT data processing, whileconsidering the practical issue of UAV jittering. Specifically, we propose ajoint design on trajectory and offloading strategies to minimize energyconsumption due to local and edge computation, as well as data transmission. Weparticularly address the UAV jittering that induces Gaussian-distributeduncertainties associated with flying waypoints, resulting in probabilistic-formflying speed and data offloading constraints. We exploit the Bernstein-typeinequality to reformulate the constraints in deterministic forms and decomposethe energy minimization to solve for trajectory and offloading separatelywithin an alternating optimization framework. The subproblems are then tackledwith the successive convex approximation technique. Simulation results showthat our proposal strictly guarantees robustness under uncertainties andeffectively reduces energy consumption as compared with the baselines.

Robust Trajectory and Offloading for Energy-Efficient UAV Edge Computing in Industrial Internet of Things