Virtually Zero Delay Interaction Between Online Game Players Using Kalman Filter-Based Dead Reckoning with Density and Distance Gain Control Adaptation
| Autor: | Seong-Whan Kim, Jung-Yoon Kim |
|---|---|
| Rok vydání: | 2019 |
| Předmět: |
010505 oceanography
Computer Networks and Communications Computer science Game engine 05 social sciences 050301 education Kalman filter 01 natural sciences Computer Graphics and Computer-Aided Design Zero (linguistics) Artificial Intelligence Control theory Dead reckoning Automatic gain control Adaptation (computer science) 0503 education Software 0105 earth and related environmental sciences |
| Zdroj: | International Journal of Software Engineering and Knowledge Engineering. 29:1091-1101 |
| ISSN: | 1793-6403 0218-1940 |
| DOI: | 10.1142/s0218194019400102 |
| Popis: | Online 3D games require fast and efficient user interaction support over the network environments, and the networking support is usually implemented by the use of a network game engine. The network game engine should minimize the network delay and mitigate the network traffic congestion. To minimize the network traffic between game users, a client-based prediction (dead reckoning (DR) algorithm) is used. Each game entity uses the algorithm to estimate its own movement as well as the others’. In case the estimation error exceeds the threshold, the entity sends an UPDATE packet which includes velocity, position and the like to other entities. As the estimation accuracy is increased, each entity can minimize the transmission of the UPDATE packet. In this paper, a Kalman filter-based approach is proposed in order to improve the prediction accuracy and an adaptive Kalman gain control in order to minimize the number of UPDATE packets to distant devices. The BZFlag game was used in the experiment in order to verify the proposed approach and the results have shown that it is possible to increase prediction accuracy and reduce the network traffic by 12%. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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