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BEHAVIORAL ASSUMPTION-BASED PREDICTION F OR HIGH-LATENCY HIDING IN MOBILE GAMES

BEHAVIORAL ASSUMPTION-BASED PREDICTION F OR HIGH-LATENCY HIDING IN MOBILE GAMES. Giliam J.P. de Carpentier Rafael Bidarra. Computer Graphics and CAD/CAM Group Faculty of Electrical Engineering, Mathematics and Computer Science. The problem. Multi-player games Fast-paced racing

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BEHAVIORAL ASSUMPTION-BASED PREDICTION F OR HIGH-LATENCY HIDING IN MOBILE GAMES

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  1. BEHAVIORAL ASSUMPTION-BASED PREDICTIONFOR HIGH-LATENCY HIDING IN MOBILE GAMES Giliam J.P. de Carpentier Rafael Bidarra Computer Graphics and CAD/CAM Group Faculty of Electrical Engineering, Mathematics and Computer Science

  2. The problem • Multi-player games • Fast-paced racing • Network connections • Latency G.J.P. de Carpentier and R. Bidarra CGAMES 2005, France

  3. T = t1 : Transmit red position Network T = t1 + ΔTlatency : Receive position Actual position red Network Received position red The problem • Multi-player games • Fast-paced racing • Network connections • Latency G.J.P. de Carpentier and R. Bidarra CGAMES 2005, France

  4. A common technique T = t1 : Transmit red position • Prediction • Prediction errors • Dead reckoning Network T = t1 + ΔTlatency : Receive position Actual position red ≈ Predicted position red Network Received position red at t1 G.J.P. de Carpentier and R. Bidarra CGAMES 2005, France

  5. A common technique T = t1 : Transmit red position • Prediction • Prediction errors • Dead reckoning Network T = t1 + ΔTlatency : Receive position Actual position red Predicted position red Network Received position red at t1 G.J.P. de Carpentier and R. Bidarra CGAMES 2005, France

  6. Mobile games • Platform: Java, BREW, Symbian, … • Network: GPRS using HTTP/TCP/IP stack G.J.P. de Carpentier and R. Bidarra CGAMES 2005, France

  7. Prediction models ~ Xt Xt • Standard strategy: • Only extrapolate from older data • Our approach: • Assume track following behavior • Or assume racing line optimizing behavior Xt-1 Xt-2 G.J.P. de Carpentier and R. Bidarra CGAMES 2005, France

  8. Prediction models Xt ~ Xt • Standard strategy: • Only extrapolate from older data • Our approach: • Assume track following behavior • Or assume racing line optimizing behavior Xt-1 Xt-2 G.J.P. de Carpentier and R. Bidarra CGAMES 2005, France

  9. Continuity • Multiple simulations • Running 2 or 3 real-time simulations • Linear interpolation between simulations • Round robin G.J.P. de Carpentier and R. Bidarra CGAMES 2005, France

  10. Continuity • Multiple simulations • Running 2 or 3 real-time simulations • Linear interpolation between simulations • Round robin simA simB simC weight time G.J.P. de Carpentier and R. Bidarra CGAMES 2005, France

  11. A Test Drive • Creating a testbed • Comparing results • Razor G.J.P. de Carpentier and R. Bidarra CGAMES 2005, France

  12. A Test Drive • Creating a testbed • Comparing results • Razor http://www.exmachina.nl G.J.P. de Carpentier and R. Bidarra CGAMES 2005, France

  13. Conclusions • Mobile 2.5G networks: a problematic domain • Standard dead reckoning is insufficient • Behavioral assumptions improve prediction • Running multiple simulations: a good fit G.J.P. de Carpentier and R. Bidarra CGAMES 2005, France

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