An Edge Network Orchestrator for Mobile Augmented Reality

Qiang Liu, Siqi Huang, Johnson Opadere, Tao Han

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

160 Citations (Scopus)


Mobile augmented reality (MAR) involves high complexity computation which cannot be performed efficiently on resource limited mobile devices. The performance of MAR would be significantly improved by offloading the computation tasks to servers deployed with the close proximity to the users. In this paper, we design an edge network orchestrator to enable fast and accurate object analytics at the network edge for MAR. The measurement-based analytical models are built to characterize the tradeoff between the service latency and analytics accuracy in edge-based MAR systems. As a key component of the edge network orchestrator, a server assignment and frame resolution selection algorithm named FACT is proposed to mitigate the latency-accuracy tradeoff. Through network simulations, we evaluate the performance of the FACT algorithm and show the insights on optimizing the performance of edge-based MAR systems. We have implemented the edge network orchestrator and developed the corresponding communication protocol. Our experiments validate the performance of the proposed edge network orchestrator.

Original languageEnglish
Title of host publicationINFOCOM 2018 - IEEE Conference on Computer Communications
PublisherInstitute of Electrical and Electronics Engineers Inc.
Number of pages9
ISBN (Electronic)9781538641286
Publication statusPublished - 8 Oct 2018
Externally publishedYes
Event2018 IEEE Conference on Computer Communications, INFOCOM 2018 - Honolulu, United States
Duration: 15 Apr 201819 Apr 2018

Publication series

NameProceedings - IEEE INFOCOM
ISSN (Print)0743-166X


Conference2018 IEEE Conference on Computer Communications, INFOCOM 2018
Country/TerritoryUnited States


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