MetaVRadar: Measuring Metaverse Virtual Reality Network Activity


연구 분야: Cryptography



학회: SIGMETRICS/PERFORMANCE '24: Abstracts of the 2024 ACM SIGMETRICS/IFIP PERFORMANCE Joint International Conference on Measurement and Modeling of Computer Systems


초록

The ''metaverse'', wherein users can immerse in virtual worlds through their VR headsets to work, study, play, shop, socialize, and entertain, is fast becoming a reality. However, little is known about the network dynamics of metaverse VR applications, which are needed to make telecommunications network infrastructure ''metaverse ready'' to support superlative user experience. This work is an empirical measurement study of metaverse VR network behavior. By analyzing metaverse sessions on the Oculus VR headset, we first develop a categorization of user activity into distinct states ranging from login home to streetwalking and event attendance to asset trading, characterizing network traffic per state, thereby highlighting the vastly more complex nature of a metaverse session compared to streaming video or gaming. Our second contribution develops a real-time method MetaVRadar to detect metaverse session and classify the user activity state leveraging formalized flow signatures and volumetric attributes. Our third contribution practically implements MetaVRadar in a large university campus network to demonstrate its usability.


Author Profile
Minzhao Lyu

University of New South Wales Sydney NSW Australia

Australia
Author Profile
Rahul Dev Tripathi

University of New South Wales Sydney NSW Australia

Australia
Author Profile
Vijay Sivaraman

University of New South Wales Sydney NSW Australia

Australia

📄 논문 정보

발행 연도 2024년
인용수 2
출판 국가 Australia
사이트 ACM
좋아요 수 0

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