Paper Info
Title
Energy-Efficient Resource Management in UAV-Assisted Mobile Edge Computing
Abstract
Unmanned aerial vehicles (UAVs) have been deployed to enhance the network capacity and provide services to mobile users with or without infrastructure coverage. At the same time, we have observed the exponential growth in Internet of Things (IoTs) devices and applications. However, as IoT devices have limited computation capacity and battery lifetime, it is challenging to process data locally on the devices. To this end, in this letter, a UAV-aided mobile edge computing system is proposed. The problem to jointly minimize the energy consumption at the IoT devices and the UAVs during task execution is studied by optimizing the task offloading decision, resource allocation mechanism and UAV's trajectory while considering the communication and computation latency requirements. A non-convex structure of the formulated problem is revealed and shown to be challenging to solve. To address this challenge, a block successive upper-bound minimization (BSUM) algorithm is introduced. Finally, simulation results are provided to show the efficiency of our proposed algorithm.
Year
DOI
Venue
2021
10.1109/LCOMM.2020.3026033
IEEE Communications Letters
Keywords
DocType
Volume
Unmanned aerial vehicles (UAVs),mobile edge computing,tasks assignment,block successive upper-bound minimization (BSUM)
Journal
25
Issue
ISSN
Citations 
1
1089-7798
10
PageRank 
References 
Authors
0.46
0
6
Name
Order
Citations
PageRank
Yan Kyaw Tun1486.18
Yu Min Park2111.83
Nguyen H. Tran339952.48
Walid Saad44450279.64
Shashi Raj Pandey5858.95
Choong Seon Hong62044277.88