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Studying Cloud-Based Virtual Reality Traffic

  • DATA TRANSMISSION IN COMPUTER NETWORKS
  • Published:
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Abstract

The traffic of cloud-based interactive virtual reality (VR) applications will significantly differ from that typical of the modern Internet in terms of structure and quality of service requirements. To improve data transmission technologies and develop solutions that will provide the required quality of service for VR traffic, a set of models should be developed that describe a new traffic type and user behavior. These models can be used to assess the impact of various network performance indicators (for example, channel bandwidth, packet transmission delays, and reliability of their delivery) on the quality of experience perceived by VR end user. The traffic properties of common VR applications are studied and a detailed and flexible VR application model is developed. The model can be used to generate VR video streams that have the same properties as those generated by existing VR applications. The effect of encoding parameters of a VR video stream on the efficiency of its delivery over a wireless network is examined. It is shown that the correct choice of these parameters significantly increases the network capacity compared with those used in existing cloud-based VR applications.

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Notes

  1. This standard also defines other types of segment; however, they are not used in live video encoding.

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Funding

The research was supported by the Russian Science Foundation, grant no. 21-79-10431.

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Authors and Affiliations

  1. Kharkevich Institute for Information Transmission Problems, Russian Academy of Sciences, 127051, Moscow, Russia

    E. S. Korneev, M. V. Liubogoshchev & E. M. Khorov

Authors
  1. E. S. Korneev
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  2. M. V. Liubogoshchev
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  3. E. M. Khorov
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Corresponding authors

Correspondence to E. S. Korneev, M. V. Liubogoshchev or E. M. Khorov.

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The authors declare that they have no conflicts of interest.

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Translated by M. Shmatikov

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Korneev, E.S., Liubogoshchev, M.V. & Khorov, E.M. Studying Cloud-Based Virtual Reality Traffic. J. Commun. Technol. Electron. 67, 1500–1505 (2022). https://doi.org/10.1134/S1064226922120099

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  • DOI: https://doi.org/10.1134/S1064226922120099

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