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A Simulation Model of Object Movement for Evaluating the Communication Load in Networked Virtual Environments

  • Lim, Mingyu (Dept. of Internet & Multimedia, Konkuk University) ;
  • Lee, Yunjin (Division of Digital Media, Ajou University)
  • Received : 2012.06.20
  • Accepted : 2012.07.24
  • Published : 2013.09.30

Abstract

In this paper, we propose a common simulation model that can be reused for different performance evaluations of networked virtual environments. To this end, we analyzed the common features of NVEs, in which multiple regions compose a shared space, and where a user has his/her own interest area. Communication architecture can be client-server or peer-server models. In usual simulations, users move around the world while the number of users varies with the system. Our model provides various simulation parameters to customize the region configuration and user movement pattern. Furthermore, our model introduces a way to mimic a lot of users in a minimal experiment environment. The proposed model is integrated with our network framework, which supports various scalability approaches. We specifically applied our model to the interest management and load distribution schemes to evaluate communication overhead. With the proposed simulation model, a new simulation can be easily designed in a large-scale environment.

Keywords

References

  1. S. Singhal and M. Zyda, Networked Virtual Environments: design and implementation, Addison-Wesley, New York, 1999.
  2. K. Morse, L. Bic and M. Dillencourt, "Interest Management in Large-scale Virtual Environments," PRESENCE - Teleoperators and Virtual Environments, vol. 9, no.1, 2000, pp. 52-68. https://doi.org/10.1162/105474600566619
  3. C. Greenhalgh and S. Benford, "MASSIVE: A Collaborative Virtual Environment for Teleconferencing," ACM Trans. Computer-Human Interaction, vol. 2, no. 3, 1995, pp. 239-261. https://doi.org/10.1145/210079.210088
  4. S. Han, M. Lim, D. Lee and S. Hyun, "A Scalable Interest Management Scheme for Distributed Virtual Environments," Computer Animation and Virtual Worlds, vol. 19, no. 2, 2008, pp. 129-149. https://doi.org/10.1002/cav.218
  5. P. Morillo, J. Orduna, M. Fernandez and J. Duato, "Improving the Performance of Distributed Virtual Environment Systems," IEEE Trans. Parallel and Distributed Systems, vol. 16, no. 7, 2005, pp. 637-649. https://doi.org/10.1109/TPDS.2005.83
  6. J. Chen, B. Wu, M. Delap, B. Knutsson, H. Lu and C. Amya, "Locality Aware Dynamic Load Management for Massively Multiplayer Games," Proceedings of the Tenth ACM SIGPLAN Symposium on Principles and Practices of Parallel Programming, Chicago, Illinois, USA, June 15-17, 2005, pp. 289-300.
  7. M. Lim and D. Lee, "A Task-Based Load Distribution Scheme for Multi-Server-Based Distributed Virtual Environment Systems," PRESENCE - Teleoperators and Virtual Environments, vol. 18, no. 1, 2009, pp. 16-38. https://doi.org/10.1162/pres.18.1.16
  8. D. Lee, M. Lim, S. Han and K. Lee, "ATLAS - A Scalable Network Framework for Distributed Virtual Environments," PRESENCE - Teleoperators and Virtual Environments, vol. 16, no. 2, 2007, pp. 125-156. https://doi.org/10.1162/pres.16.2.125

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