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Evaluation of 2D and 3D interest management techniques in the distributed virtual environment DiVE

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Abstract

We present DiVE, a networking framework for the rapid development of massively multiuser three-dimensional (3D) virtual world applications. The primary contribution of the paper is twofold. First, we investigate zone-based area of interest (AOI) techniques aimed at improving DiVE’s scalability. Specifically, we present an interest management technique that is based on dividing the world into two-dimensional (2D) zones and a ‘double’ (inner/outer) AOI concept. Here the novelty is the investigation of different movement patterns of client entities to determine the optimal AOI/zone ratio. The empirical evaluation of our approach shows promising results on four metrics: bandwidth, frames per second, CPU, and RAM. Second, we extend the AOI concept from 2D space to 3D space, which has not yet been addressed in the literature. Among others, 3D space suggests interesting applications for the safety of unmanned aerial vehicles. Besides the investigation of the optimal size of volumetric AOI, we also consider different forms of volumetric zone alignment. The secondary contribution consists in a technical description of the DiVE framework, which has already been used successfully in multiuser applications in the traffic and evacuation domains.

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Notes

  1. http://secondlife.com/.

  2. http://opensimulator.org/.

  3. http://realxtend.org/.

  4. http://www.jenkinssoftware.com/.

  5. http://www.opentnl.org/.

  6. We are aware of a framework with a similar name (DIVE) Frecon and Stenius (1998).

  7. Liu et al. (2012) call this method ‘region’ based.

  8. In this paper, when the verb ‘see’ appears in context of an entity, it simply means that the entity receives and disseminates status updates to all other entities within its AOI.

  9. http://sourceforge.net/apps/trac/reddwarf/.

  10. Although commonly referred to as 3D virtual environments, the movement patters are two dimensions, rather than three dimensions.

  11. We note that the thread programming model of the agent-based social movement pattern should ideally be replaced by another model that is similar to the other two movement patterns.

  12. http://www.exitgames.com/.

  13. http://unity3d.com/.

  14. http://www.mono-project.com/.

  15. https://code.google.com/p/protobuf/.

  16. http://oauth.net/2/.

  17. Note that the client can still see the whole zone where the AOI is located in.

  18. As we can only shift in one direction in 2D, we performed shifting only in 3D case.

  19. http://utm.arc.nasa.gov/index.shtml.

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Acknowledgements

We would like to thank Martin Lindner for implementing several components of DiVE. We would also like to thank Artur Gonçalves for strengthening the literature review of this paper. This work was partly supported by the ‘Global Lab’ NII Grand Challenge grant, a Kiban Kenkyu B grant from the Japan Society of the Promotion of Science (JSPS), and by FCT (INESC-ID multiannual funding) through the PIDDAC Program PEst- OE/EEI/LA0021/2011.

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Authors and Affiliations

  1. National Institute of Informatics 2-1-2 Hitotsubashi, Chiyoda-ku, Tokyo, 101-8430, Japan

    Helmut Prendinger, Raghvendra Jain & Tristian Imbert

  2. INESC-ID and Instituto Superior Técnico, Universidade de Lisboa, Lisbon, Portugal

    João Oliveira

  3. University of Essex, Wivenhoe Park, Colchester, CO4 3SQ, UK

    Ruijiao Li

  4. Manifesto Games, New York City, NY, USA

    Marconi Madruga

Authors
  1. Helmut Prendinger
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  2. Raghvendra Jain
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  3. Tristian Imbert
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  4. João Oliveira
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  5. Ruijiao Li
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  6. Marconi Madruga
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Corresponding author

Correspondence to Helmut Prendinger.

Additional information

Helmut Prendinger, Raghvendra Jain, and Tristian Imbert have contributed equally to this paper.

Appendix

Appendix

See Table 1.

Table 1 Comparison of interest management in DiVE to selected related proposals
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Prendinger, H., Jain, R., Imbert, T. et al. Evaluation of 2D and 3D interest management techniques in the distributed virtual environment DiVE. Virtual Reality 22, 263–280 (2018). https://doi.org/10.1007/s10055-017-0322-3

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