Communication-and-Computing Latency Minimization for UAV-Enabled Virtual Reality Delivery Systems

Yi Zhou, Cunhua Pan, Phee Lep Yeoh, Kezhi Wang, Maged Elkashlan, Branka Vucetic, Yonghui Li*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

43 Citations (Scopus)
46 Downloads (Pure)

Abstract

In this paper, we propose a low-latency virtual reality (VR) delivery system where an unmanned aerial vehicle (UAV) base station (U-BS) is deployed to deliver VR content from a cloud server to multiple ground VR users. Each VR input data requested by the VR users can be either projected at the U-BS before transmission or processed locally at each user. Popular VR input data is cached at the U-BS to further reduce backhaul latency from the cloud server. For this system, we design a low-complexity iterative algorithm to minimize the maximum communications and computing latency among all VR users subject to the computing, caching and transmit power constraints, which is guaranteed to converge. Numerical results indicate that our proposed algorithm can achieve a lower latency compared to other benchmark schemes. Moreover, we observe that the maximum latency mainly comes from communication latency when the bandwidth resource is limited, while it is dominated by computing latency when computing capacity is low. In addition, we find that caching is helpful to reduce latency.
Original languageEnglish
Pages (from-to)1723-1735
Number of pages14
JournalIEEE Transactions on Communications
Volume69
Issue number3
Early online date24 Nov 2020
DOIs
Publication statusPublished - 1 Mar 2021

Keywords

  • Cloud computing
  • Clouds
  • Minimization
  • Resource management
  • Servers
  • Telecommunication computing
  • UAV communication
  • Unmanned aerial vehicles
  • caching
  • computing
  • joint optimization
  • latency minimization

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