1. Dead Reckoning Irwin Chiu Hau Nicolas Ng Man Sun

2. Overview  Introduction  Solution  Modelling  Progress  Conclusion

3. Introduction  Online Multiplayer Games Multiple players/computers connected via the InternetMultiple players/computers connected via the Internet e.g. Quake, Half Lifee.g. Quake, Half Life  Characteristics: Players moving around rapidlyPlayers moving around rapidly Powerful computersPowerful computers Limited network capacityLimited network capacity

4. Introduction  Desired features: Minimize network trafficMinimize network traffic Accurately portray other players’ movementAccurately portray other players’ movement  Dilemma Without frequent updates the local model does not know the current position of remote players.Without frequent updates the local model does not know the current position of remote players.

5. Overview  Introduction  Solution  Modelling  Progress  Conclusion

6. Solution  Dead reckoning Approximate current position based on past observationsApproximate current position based on past observations  Ship sailing in the ocean example Use the stars to determine locationUse the stars to determine location What to do when it’s cloudyWhat to do when it’s cloudy

7. Overview  Introduction  Solution  Modelling  Progress  Conclusion

8. Modeling  Each player is an atomic DEV Moves at regular intervals independently of other playersMoves at regular intervals independently of other players Receives (external) updates about other players’ position at undetermined times.Receives (external) updates about other players’ position at undetermined times.  Each player “holds” a local Dead Reckoning Model (also an atomic DEV) of other players.  The network is also an atomic DEV Models latency.Models latency.

9. Modeling  Coupled DEVs [player1] [DRM p1] [network] [player2] [DRM p2] [DRM p1]

10. Modeling Zero order approximation with updates at regular intervals

11. Global View 0 20 40 60 80 100 012345 time position Modeling Zero order approximation with error threshold error threshold

12. Modeling First order approximation with error threshold

13. Overview  Introduction  Solution  Modelling  Progress  Conclusion

14. Progress  What have we done? Object Sim ADEVSObject Sim ADEVS Dead Reckoning ADEVSDead Reckoning ADEVS Network ADEVSNetwork ADEVS Object SimDRMNetworkDRM Computer 1Computer 2

15. Object Sim ADEVS  Diagonal Movement At time 0 to 2:At time 0 to 2: v_x, v_y = 2 At time 3 to 4:At time 3 to 4: v_x, v_y = 4 At time 5 to 6:At time 5 to 6: v_x, v_y = 6v_x, v_y = 6

16. Object Sim + DR  Diagonal Movement At time 0 to 2:At time 0 to 2: v_x, v_y = 2 At time 3 to 4:At time 3 to 4: v_x, v_y = 4 At time 5 to 6:At time 5 to 6: v_x, v_y = 6v_x, v_y = 6 send

17. Dead Reckoning ADEVS  Input From NetworkFrom Network From high fidelity (or real) modelFrom high fidelity (or real) model  Output To Graphics:High Refresh RateTo Graphics:High Refresh Rate To Network:SelectiveTo Network:Selective DR ADEVS IN To Network To Graphics

18. Network ADEVS  Broadcast  Delayed Network Network IN Port N Port 1 …

19. DR System  Our current DR System  Good results for Graphics view, DR view and Network UpdatesGraphics view, DR view and Network Updates Network Tx DRM OutIN Object Sim Graphics

20. Plan / Futurework  Player 1 Network DRM 1 IN Object Sim DRM 2 Graphics DRM N Graphics … Player 2 Player N

21. Overview  Introduction  Solution  Modelling  Progress  Conclusion

22. Conclusion  Dead Reckoning = Approximation  Advantages: Reduced network trafficReduced network traffic Fluid animation in between updatesFluid animation in between updates  Dead Reckoning is used in almost every distributed environment.

23. References  PythonDEVS http://moncs.cs.mcgill.ca/MSDL/research/projects/DEVS/ http://moncs.cs.mcgill.ca/MSDL/research/projects/DEVS/  Python http://www.python.org/ http://www.python.org/  “Parallel And Distributed Simulation Systems”, R. M. Fujimoto, PhD Georgia Institute of Technology. Chapter 7.5 – Dead Reckoning