Characterizing Distributed Mobile Augmented Reality Applications at the Edge

Bartolomeo, Giovanni; Cao, Jacky; Su, Xiang; Mohan, Nitinder

Characterizing Distributed Mobile Augmented Reality Applications at the Edge

Conference paper (2023)

Authors

Giovanni Bartolomeo

Jacky Cao

Xiang Su

Nitinder Mohan Technische Universität München

Affiliation

External organisation

Augmented reality Containers Edge computing Orchestration Distributed stream processing

To reference this document use:

http://resolver.tudelft.nl/uuid:3c3e3101-95d8-4a06-843a-fb8ff2e1630e

More Info

expand_more

Published Date

2023

Language

English

Reuse Rights

Other than for strictly personal use, it is not permitted to download, forward or distribute the text or part of it, without the consent of the author(s) and/or copyright holder(s), unless the work is under an open content license such as Creative Commons.

Affiliation

External organisation

Abstract

Mobile Augmented Reality (AR) is gaining traction as a compelling application due to recent advancements in hardware and software. Previous studies have suggested that distributing AR services on an edge computing infrastructure can offer significant performance benefits, especially for consolidating concurrent clients. In this study, we shed light on several research challenges directly impacting the effective integration of distributed AR and edge computing. Specifically, we conduct extensive experiments by deploying our distributed stream processing-based AR pipeline, scAtteR, on a representative edge-cloud infrastructure managed by the Oakestra framework. We uncover several unapparent challenges that inhibit the effective marriage of distributed AR when deployed on edge and demonstrate the potential improvements through scAtteR++. We offer valuable insights and best practices to the growing AR research community, specifically those interested in leveraging edge and public cloud technologies for large-scale AR operations.