Article (Scientific journals)
Ready Player One: UAV Clustering based Multi-Task Offloading for Vehicular VR/AR Gaming
Hu, Long; Tian, Yuanwen; Yang, Jun et al.
2019In IEEE Network
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Keywords :
Unmanned aerial vehicle (UAV); Computing, caching, and communication (3C); Artificial Intelligence (AI)
Abstract :
[en] 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.
Research center :
Interdisciplinary Centre for Security, Reliability and Trust (SnT) > SIGCOM
Disciplines :
Electrical & electronics engineering
Author, co-author :
Hu, Long
Tian, Yuanwen
Yang, Jun
Taleb, Tarik
Xiang, Lin ;  University of Luxembourg > Interdisciplinary Centre for Security, Reliability and Trust (SNT)
Hao, Yixue
External co-authors :
yes
Language :
English
Title :
Ready Player One: UAV Clustering based Multi-Task Offloading for Vehicular VR/AR Gaming
Publication date :
May 2019
Journal title :
IEEE Network
ISSN :
1558-156X
Publisher :
Institute of Electrical and Electronics Engineers, New York, United States - New York
Peer reviewed :
Peer Reviewed verified by ORBi
Focus Area :
Security, Reliability and Trust
Name of the research project :
AGNOSTIC
Funders :
CER - Conseil Européen de la Recherche [BE]
Available on ORBilu :
since 21 May 2019

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