Task Offloading in UAV-Aided Edge Computing: Bit Allocation and Trajectory Optimization

Jingyu Xiong; Hongzhi Guo; Jiajia Liu

doi:10.1109/LCOMM.2019.2891662

Task Offloading in UAV-Aided Edge Computing: Bit Allocation and Trajectory Optimization

Jingyu Xiong, Hongzhi Guo, Jiajia Liu

Xidian University

Research output: Contribution to journal › Article › peer-review

153 Scopus citations

Abstract

The deployment of unmanned aerial vehicles (UAVs) in wireless communication systems promises to provide services for devices with limited or without infrastructure coverage. With the emergence of diverse Internet of Things (IoT) applications, there is an ever-increasing demand for computation resources of IoT mobile devices (IMDs) in UAV communication scenarios. Motivated by this, we consider a UAV-aided edge computing scenario and study the task offloading problem between the IMDs and the UAV, aiming to minimize the overall energy consumption for accomplishing the tasks. An alternative optimization algorithm is proposed as our solution, which jointly optimizes task offloading decision-making, bit allocation during transmission, and the UAV trajectory. Numerical results demonstrate the significant energy savings of the proposed scheme.

Original language	English
Article number	8607062
Pages (from-to)	538-541
Number of pages	4
Journal	IEEE Communications Letters
Volume	23
Issue number	3
DOIs	https://doi.org/10.1109/LCOMM.2019.2891662
State	Published - Mar 2019
Externally published	Yes

Keywords

bit allocation
energy minimization
Task offloading
trajectory optimization
UAV-aided edge computing

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

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10.1109/LCOMM.2019.2891662

Cite this

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title = "Task Offloading in UAV-Aided Edge Computing: Bit Allocation and Trajectory Optimization",

abstract = "The deployment of unmanned aerial vehicles (UAVs) in wireless communication systems promises to provide services for devices with limited or without infrastructure coverage. With the emergence of diverse Internet of Things (IoT) applications, there is an ever-increasing demand for computation resources of IoT mobile devices (IMDs) in UAV communication scenarios. Motivated by this, we consider a UAV-aided edge computing scenario and study the task offloading problem between the IMDs and the UAV, aiming to minimize the overall energy consumption for accomplishing the tasks. An alternative optimization algorithm is proposed as our solution, which jointly optimizes task offloading decision-making, bit allocation during transmission, and the UAV trajectory. Numerical results demonstrate the significant energy savings of the proposed scheme.",

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author = "Jingyu Xiong and Hongzhi Guo and Jiajia Liu",

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Task Offloading in UAV-Aided Edge Computing: Bit Allocation and Trajectory Optimization

Abstract

Keywords

UN SDGs

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