Online Task Allocation and Flying Control in Fog-Aided Internet of Drones

Document Type

Article

Publication Date

5-1-2020

Abstract

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.

Identifier

85085192807 (Scopus)

Publication Title

IEEE Transactions on Vehicular Technology

External Full Text Location

https://doi.org/10.1109/TVT.2020.2982172

e-ISSN

19399359

ISSN

00189545

First Page

5562

Last Page

5569

Issue

5

Volume

69

Grant

1814748

Fund Ref

National Science Foundation

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