A Self-Adaptive Filtering Algorithm Based on Consistency QoS in CVE Systems


Article Preview

In the Collaborative Virtual Environments (CVE), there is a conflict between maintaining the state consistency and supporting more users sharing the virtual environment. A self-adaptive message filtering algorithm based on consistency QoS is proposed to improve both the consistency and scalability. Each user in the virtual environment has active workspace, influence area and dormancy zone according to the different requirement of consistency QoS. Time-space bounding sphere is defined to predict user’s active workspace to provide high consistency QoS. When two users’ time-space bounding spheres overlap, the key updates of two users are sent to each other in time to keep the state consistency. A self-adaptive threshold function model is used when two users’ influence areas overlap, which makes a tradeoff between consistency and scalability and provides a medium consistency QoS. Heart-beat packets are sent when two users’ dormancy zones overlap to filter messages in order to reduce the system traffic since the low consistency QoS is required. The results of traffic test and consistency QoS test in the experiment show that our algorithm can maintain the state consistency and reduce the consumption of network resources simultaneously.



Advanced Materials Research (Volumes 225-226)

Edited by:

Helen Zhang, Gang Shen and David Jin




X. M. Hu et al., "A Self-Adaptive Filtering Algorithm Based on Consistency QoS in CVE Systems", Advanced Materials Research, Vols. 225-226, pp. 301-306, 2011

Online since:

April 2011




[1] M.R. Macedonia, M.J. Zyda: Taxonomy for Networked Virtual Environments. IEEE Multimedia, Vol. 4(1997), pp.48-56.

DOI: https://doi.org/10.1109/93.580395

[2] K. Michael, and W. W. Johnny: Scalability Analysis of the Hierarchical Architecture for Distributed Virtual Environments. IEEE transactions on parallel and distributed systems, Vol. 19 (2008), pp.408-417.

DOI: https://doi.org/10.1109/tpds.2007.70730

[3] N. Gupta, A. Demers, J. Gehrke, P. Unterbrunner, W. White: Scalability for Virtual Worlds. Proceedings of IEEE 25th International Conference on Data Engineering, (2009), pp.1311-1314.

DOI: https://doi.org/10.1109/icde.2009.228

[4] L. Chen, G.C. Chen, C.G. Ye: Using Collaborative Knowledge Base to Realize Adaptive Message Filtering in Collaborative Virtual Environment. In Proceedings of ICCT, (2003), pp.1655-1661.

DOI: https://doi.org/10.1109/icct.2003.1209845

[5] W. Cai, F.B.S. Lee, L. Chen: An auto-adaptive Dead Reckoning Alogrithm for Distributed Interactive Simulation. In Proceedings of Workshop on Parallel and Distributed Simulation, (1999), pp.82-89.

DOI: https://doi.org/10.1109/pads.1999.766164

[6] L. Chen, G.C. Chen: A Fuzzy Dead Reckoning Algorithm for Distributed Interactive Applications. In Proceedings of International Conference on Fuzzy Systems and Knowledge Discovery, (2005), pp.961-971.

DOI: https://doi.org/10.1007/11540007_121

Fetching data from Crossref.
This may take some time to load.