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Performance evaluation of a multi-user virtual reality platform

Parthasarathy, Venkatesh Balavadhani, Simiscuka, Anderson Augusto orcid logoORCID: 0000-0002-0851-2452, O'Connor, Noel E. orcid logoORCID: 0000-0002-4033-9135 and Muntean, Gabriel-Miro orcid logoORCID: 0000-0002-9332-4770 (2020) Performance evaluation of a multi-user virtual reality platform. In: 16th International Wireless Communications & Mobile Computing Conference (IWCMC 2020), 15-19 June 2020, Limassol, Cyprus (Virtual).

Virtual Reality (VR) popularity is increasing as it is becoming more affordable for end users. Available VR hardware includes low-end inexpensive devices like Google Cardboard and high-end ones like HTC Vive or Oculus Rift, which are more expensive headsets. Using VR as a platform for content delivery allows better user engagement than other traditional methods, as VR headsets remove external distractions. Multi- user VR applications provide shared experiences where users can communicate and interact in the same virtual space. This shared environment, however, introduces challenges regarding network performance, quality of service (QoS) and sessions privacy. This paper presents a multi-user VR application and aims to evaluate network behaviour in a number of scenarios, including real VR headsets (i.e. Oculus Rift), as well as simulated ones. This QoS analysis is important for the understanding of how many VR users can be simultaneously connected with high image quality.
Item Type:Conference or Workshop Item (Paper)
Event Type:Conference
Uncontrolled Keywords:Virtual Reality; Multi-User; Network Performance; Quality of Service
Subjects:Computer Science > Computer networks
DCU Faculties and Centres:DCU Faculties and Schools > Faculty of Engineering and Computing > School of Electronic Engineering
Published in: 2020 International Wireless Communications and Mobile Computing (IWCMC). . IEEE.
Official URL:http://dx.doi.org/10.1109/IWCMC48107.2020.9148390
Copyright Information:© 2020 The Authors.
Use License:This item is licensed under a Creative Commons Attribution-NonCommercial-Share Alike 3.0 License. View License
Funders:EU Horizon 2020 Research and Innovation programme under Grant Agreement no. 870610 for the TRACTION project, Science Foundation Ireland (SFI) Research Centres Programme Grant Numbers 12/RC/2289_P2 (Insight) and 16/SP/3804 (ENABLE)
ID Code:24437
Deposited On:15 Jun 2020 10:13 by Anderson Augusto Simiscuka . Last Modified 05 Dec 2023 15:19

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