Proactive edge cloud optimization for mobile augmented reality applications

Zhaohui Huang, Vasilis Friderikos

Research output: Chapter in Book/Report/Conference proceedingConference paperpeer-review

10 Citations (Scopus)

Abstract

Undoubtedly mobile augmented reality (MAR) applications are starting to attract significant attention due to enhanced capabilities from both the network and the end devices which can propel their realization. However, despite the progress on the end user devices, MAR applications are inherently extremely hungry in terms of CPU and memory requirements since they are performing, inter alia, intense computer vision algorithms. To this end, edge cloud computing is envisioned as a key and integrated technology for supporting such applications where part of the intensive algorithms are offloaded to suitably selected edge clouds. In this paper an edge cloud resource optimization framework is presented that takes explicitly into account user mobility to proactively allocate resources to satisfy the required strict latency requirements of MAR applications. Numerical investigations reveal that significant gains can be achieved by creating MAR offloading tasks using mobility awareness.

Original languageEnglish
Title of host publication2021 IEEE Wireless Communications and Networking Conference, WCNC 2021
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781728195056
DOIs
Publication statusPublished - 2021
Event2021 IEEE Wireless Communications and Networking Conference, WCNC 2021 - Nanjing, China
Duration: 29 Mar 20211 Apr 2021

Publication series

NameIEEE Wireless Communications and Networking Conference, WCNC
Volume2021-March
ISSN (Print)1525-3511

Conference

Conference2021 IEEE Wireless Communications and Networking Conference, WCNC 2021
Country/TerritoryChina
CityNanjing
Period29/03/20211/04/2021

Keywords

  • 5G
  • Augmented Reality
  • Edge Clouds
  • Mobility
  • Network Optimization
  • Resource Management

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