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Modeling Resource Sharing Dynamics of VoIP Users over a WLAN Using Game Theory

Explore the performance consequences and adaptation processes of users choosing their rates in a VoIP scenario at a coffee shop or airport. Utilize a game-theoretic approach and symmetric strategic game to analyze user behavior and system saturation throughput testing. Understand equilibrium states, transient probabilities, and system fairness implications to optimize resource sharing. Discover strengths, weaknesses, and propose scalable experiments for further analysis.

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Modeling Resource Sharing Dynamics of VoIP Users over a WLAN Using Game Theory

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  1. Modeling Resource Sharing Dynamics of VoIP users over a WLAN Using a Game-Theoretic Approach INFOCOM 2008 Edson H. Watanabe, Daniel S. Menasch´e, Edmundo de Souza e Silva, Rosa M. M. Le˜ao Systems Engineering and Computer Science Department COPPE - Federal University of Rio de Janeiro, 21941-590 - Rio de Janeiro, RJ, Brazil Presenter: Po-Jung Wang

  2. outline • Scenario • Introduction • Game-theoretic model • Simulation • Experiment • Result • Conclusion

  3. Scenario – coffee shop

  4. airport

  5. Using VoIP through the wifi

  6. Now we have two Questions • What are the performance consequences of letting the users to freely choose their rates? • How to explain the adaptation process of the users?

  7. modeling

  8. Game theory equation

  9. symmetric strategic game • N is the number of users that share the access point. • S is the discrete set of strategies available, that is, the set of joint codec plus FEC mechanisms that any application user can select from. • U is the utility function.

  10. What is mos?

  11. Perspective from one user low, 20 kbps (Speex 6 kpbs, FEC 1:2::3:6); medium, 33.6 kbps (Speex 14.2 kbps, FEC 1:2) high, 47.5 kbps (Speex 14.2 kps, FEC 1:2::3:6).

  12. System saturation throughput testing

  13. Equilibrium States for the model and the experiment

  14. Transient probability

  15. Probability form one state to another

  16. Letting user exit the sys ifmosis to low

  17. Summary and conclusion • Free users with local information can reach an equilibrium which is close to optimal from the system perspective. However, the equilibrium can be unfair. • Using a game-theoretic model and propose a methodology to parameterize it. • Strength and weekness Discovery thephenomena of letting user to freely choose Need more scalable experiments

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