Title
Ready Player One: UAV-Clustering-Based Multi-Task Offloading for Vehicular VR/AR Gaming
Abstract
With rapid development of unmanned aerial vehicle (UAV) technology, application of UAVs for task offloading has received increasing interest in academia. However, real-time interaction between one UAV and the mobile edge computing node is required for processing the tasks of mobile end users, which significantly increases the system overhead and is unable to meet the demands of large-scale artificial intelligence (AI)-based applications. To tackle this problem, in this article, we propose a new architecture for UAV clustering to enable efficient multi-modal multi-task offloading. With the proposed architecture, the computing, caching, and communication resources are collaboratively optimized using AI-based decision making. This not only increases the efficiency of UAV clusters, but also provides insight into the fusion of computation and communication.
Year
DOI
Venue
2019
10.1109/MNET.2019.1800357
IEEE Network
Keywords
DocType
Volume
Task analysis,Computer architecture,Unmanned aerial vehicles,Real-time systems,Collaboration,Artificial intelligence,Quality of experience
Journal
33
Issue
ISSN
Citations 
3
0890-8044
6
PageRank 
References 
Authors
0.43
0
6
Name
Order
Citations
PageRank
long hu1904.00
Yuanwen Tian2421.44
Jun Yang3505.64
Tarik Taleb43111237.91
Lin Xiang51329.42
Yixue Hao658327.68