XRFlux: Virtual Reality Benchmark for Edge Caching Systems

Fuente: arXiv
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Autori principali: Alfares, Nader, Kesidis, George
Natura: Preprint
Pubblicazione: 2024
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author Alfares, Nader
Kesidis, George
author_facet Alfares, Nader
Kesidis, George
contents We introduce a Unity based benchmark XRFlux for evaluating Virtual Reality (VR) delivery systems using edge-cloud caching. As VR applications and systems progress, the need to meet strict latency and Quality of Experience (QoE) requirements is increasingly evident. In the context of VR, traditional cloud architectures (e.g., remote AWS S3 for content delivery) often struggle to meet these demands, especially for users of the same application in different locations. With edge computing, resources are brought closer to users in efforts to reduce latency and improve QoEs. However, VR's dynamic nature, with changing fields of view (FoVs) and user synchronization requirements, creates various challenges for edge caching. We address the lack of suitable benchmarks and propose a framework that simulates multiuser VR scenarios while logging users' interaction with objects within their actual and predicted FoVs. The benchmark's activity log can then be played back through an edge cache to assess the resulting QoEs. This tool fills a gap by supporting research in the optimization of edge caching (and other edge-cloud functions) for VR streaming.
format Preprint
id arxiv_https___arxiv_org_abs_2412_18960
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle XRFlux: Virtual Reality Benchmark for Edge Caching Systems
Alfares, Nader
Kesidis, George
Performance
Multimedia
We introduce a Unity based benchmark XRFlux for evaluating Virtual Reality (VR) delivery systems using edge-cloud caching. As VR applications and systems progress, the need to meet strict latency and Quality of Experience (QoE) requirements is increasingly evident. In the context of VR, traditional cloud architectures (e.g., remote AWS S3 for content delivery) often struggle to meet these demands, especially for users of the same application in different locations. With edge computing, resources are brought closer to users in efforts to reduce latency and improve QoEs. However, VR's dynamic nature, with changing fields of view (FoVs) and user synchronization requirements, creates various challenges for edge caching. We address the lack of suitable benchmarks and propose a framework that simulates multiuser VR scenarios while logging users' interaction with objects within their actual and predicted FoVs. The benchmark's activity log can then be played back through an edge cache to assess the resulting QoEs. This tool fills a gap by supporting research in the optimization of edge caching (and other edge-cloud functions) for VR streaming.
title XRFlux: Virtual Reality Benchmark for Edge Caching Systems
topic Performance
Multimedia
url https://arxiv.org/abs/2412.18960