Ready Player One: UAV-Clustering-Based Multi-Task Offloading for Vehicular VR/AR Gaming

Research output: Contribution to journalArticleScientificpeer-review

Researchers

  • Long Hu
  • Yuanwen Tian
  • Jun Yang
  • Tarik Taleb

  • Lin Xiang
  • Yixue Hao

Research units

  • University of Luxembourg
  • Huazhong University of Science and Technology
  • Sejong University

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 Al-based decision making. This not only increases the efficiency of UAV clusters, but also provides insight into the fusion of computation and communication.

Details

Original languageEnglish
Article number8726071
Pages (from-to)42-48
Number of pages7
JournalIEEE NETWORK
Volume33
Issue number3
Publication statusPublished - 1 May 2019
MoE publication typeA1 Journal article-refereed

ID: 34747757