ACM Transactions on Modeling and Computer Simulation (TOMACS)
An auto-adaptive dead reckoning algorithm for distributed interactive simulation
PADS '99 Proceedings of the thirteenth workshop on Parallel and distributed simulation
Supporting large-scale distributed simulation using HLA
ACM Transactions on Modeling and Computer Simulation (TOMACS)
A Review of Tele-Immersive Applications in the CAVE Research Network
VR '99 Proceedings of the IEEE Virtual Reality
A Hybrid Approach to Data Distribution Management
DS-RT '00 Proceedings of the Fourth IEEE International Workshop on Distributed Simulation and Real-Time Applications
An orientation update message filtering algorithm in collaborative virtual environments
Journal of Computer Science and Technology
A dynamic message filtering technique for 3D cyberspaces
Computer Communications
ACM Transactions on Modeling and Computer Simulation (TOMACS)
Comparison of predictive contract mechanisms from an information theory perspective
ACM Transactions on Multimedia Computing, Communications, and Applications (TOMCCAP)
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A fuzzy Dead Reckoning (DR) algorithm for distributed interactive applications is proposed in this paper. Since fixed threshold cannot adequately handle the dynamic relationships between moving entities, some multi-level threshold DR algorithms were proposed in the past few years. In these algorithms the level of threshold is adaptively adjusted based on the distance between entities. The proposed fuzzy DR algorithm is based on multi-level threshold DR algorithm and takes all properties of entity (e.g. position, size and view angle etc.) into consideration when adjusting the level of threshold. This algorithm employs fuzzy correlation degree to measure the relationships between entities and determine the level of threshold for DR algorithm. Fuzzy consistent relation is used to distribute weight for each property. Simulation results indicate that fuzzy DR algorithm can achieve a considerable reduction in the number of state update messages while maintaining adequate accuracy in extrapolation.