Evolution of Cooperation in Packet Forwarding with the Random Waypoint Model

Jeffrey Hudack, Nathaniel Gemelli, Jae Oh

2013

Abstract

In multi-agent systems with self-interested individuals interacting locally, it can be difficult to determine if cooperative behavior will emerge. Evolutionary Game Theory provides some valuable tools to this end, but is not suited to systems with dynamic models of interaction. Mobile ad hoc networks provide a compelling application for evolutionary game theory, but there are still significant gaps between the theoretical results and the practical challenges. We discuss and provide some of the assumptions necessary to apply previous work in evolutionary game theory to the ad hoc network packet routing domain. We then analyze the similarities and differences between Brownian mobility and Random Waypoint mobility and show that convergence to cooperation requires a significant reduction in velocity for the Random Waypoint model. Our contribution is to provide evidence that more realistic mobility models can make convergence to cooperation more difficult than previously shown using random methods.

References

  1. Assenza, S. (2008). Enhancement of cooperation in highly clustered scale-free networks. In Physical Review E.
  2. Axelrod, R. (1992). The evolution of cooperation. Science.
  3. Axelrod, R. (2000). On six advances in cooperation theory. Analyse & Kritik, 22(1):130-151.
  4. Bai, F. and Helmy, A. (2004). A survey of mobility models. Wireless Adhoc Networks. University of Southern California, USA, 206:1-30.
  5. Boccaletti, S., Latora, V., Moreno, Y., Chavez, M., and Hwang, D. (2006). Complex networks: Structure and dynamics. Physics Reports, 424(4-5):175-308.
  6. Cho, S. and Hayes, J. (2005). Impact of mobility on connection in ad hoc networks. In Wireless Communications and Networking Conference, 2005 IEEE, volume 3, pages 1650-1656. IEEE.
  7. Cohen, M., Riolo, R., and Axelrod, R. (1999). The emergence of social organization in the prisoner's dilemma: How context-preservation and other factors promote cooperation. Working Papers.
  8. Helbing, D. and Yu, W. (2009). The outbreak of cooperation among success-driven individuals under noisy conditions. In Proceedings of the National Academy of Sciences, volume 106, page 3680. National Acad Sciences.
  9. Ho, C., Obraczka, K., Tsudik, G., and Viswanath, K. (1999). Flooding for reliable multicast in multi-hop ad hoc networks. In Proceedings of the 3rd international workshop on Discrete algorithms and methods for mobile computing and communications, pages 64- 71. ACM.
  10. Johnson, D. and Maltz, D. (1996). Dynamic source routing in ad hoc wireless networks. pages 153-181. Springer.
  11. Kamhoua, C., Pissinou, N., Miller, J., and Makki, S. (2010). Mitigating routing misbehavior in multi-hop networks using evolutionary game theory. In IEEE Globecom workshop on advances in communications and networks.
  12. Kendall, G., Yao, X., and Chong, S. (2007). The iterated prisoners' dilemma: 20 years on, volume 4. World Scientific Pub Co Inc.
  13. Luke, S., Cioffi-Revilla, C., Panait, L., Sullivan, K., and Balan, G. (2005). Mason: A multi-agent simulation environment. In Simulation: Transactions of the society for Modeling and Simulation International, volume 82(7), pages 517-527.
  14. Marti, S., Giuli, T., Lai, K., and Baker, M. (2000). Mitigating routing misbehavior in mobile ad hoc networks. In Proceedings of the 6th annual international conference on Mobil computing and networking, pages 255- 265.
  15. Meloni, S., Buscarino, A., Fortuna, L., and Frasca, M. (2009). Effects of mobility in a population of prisoner's dilemma players. Physical Review E, pages 1- 4.
  16. Nisan, N. (2007). Algorithmic Game Theory. Cambridge University Press, Cambridge.
  17. Nowak, M. (1992). Evolutionary games and spatial chaos. Nature.
  18. Oliphant, M. (1994). Evolving cooperation in the noniterated prisoner's dilemma: The importance of spatial organization. In Proceedings of the fourth artificial life workshop, Cambridge, MA, pages 349--352.
  19. Penrose, M. (2003). Random geometric graphs, volume 5. Oxford University Press, Oxford.
  20. Perc, M. and Szolnoki, A. (2008). Social diversity and promotion of cooperation in the spatial prisoners dilemma game. Physical Review E, 77(1):011904.
  21. Poncela, J., Gómez-Garden˜es, J., Floría, L., Sánchez, A., and Moreno, Y. (2008). Complex cooperative networks from evolutionary preferential attachment. volume 3, page e2449. Public Library of Science.
  22. Poncela, J., Gómez-Garden˜es, J., Traulsen, A., and Moreno, Y. (2009). Evolutionary game dynamics in a growing structured population. New Journal of Physics, 11.
  23. Szolnoki, A., Perc, M., and Danku, Z. (2008). Making new connections towards cooperation in the prisoner's dilemma game. EPL (Europhysics Letters), 84:50007.
  24. Tanachaiwiwat, S., Dave, P., Bhindwale, R., and Helmy, A. (2004). Location-centric isolation of misbehavior and trust routing in energy-constrained sensor networks. In 2004 IEEE international conference on performance, computing, and communications.
  25. Viennot, L., Jacquet, P., and Clausen, T. (2004). Analyzing control traffic overhead versus mobility and data traffic activity in mobile ad-hoc network protocols. Wireless Networks, 10(4):447-455.
  26. Weibull, J. (1997). Evolutionary game theory. The MIT press.
Download


Paper Citation


in Harvard Style

Hudack J., Gemelli N. and Oh J. (2013). Evolution of Cooperation in Packet Forwarding with the Random Waypoint Model . In Proceedings of the 5th International Conference on Agents and Artificial Intelligence - Volume 1: ICAART, ISBN 978-989-8565-38-9, pages 58-66. DOI: 10.5220/0004234800580066


in Bibtex Style

@conference{icaart13,
author={Jeffrey Hudack and Nathaniel Gemelli and Jae Oh},
title={Evolution of Cooperation in Packet Forwarding with the Random Waypoint Model},
booktitle={Proceedings of the 5th International Conference on Agents and Artificial Intelligence - Volume 1: ICAART,},
year={2013},
pages={58-66},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0004234800580066},
isbn={978-989-8565-38-9},
}


in EndNote Style

TY - CONF
JO - Proceedings of the 5th International Conference on Agents and Artificial Intelligence - Volume 1: ICAART,
TI - Evolution of Cooperation in Packet Forwarding with the Random Waypoint Model
SN - 978-989-8565-38-9
AU - Hudack J.
AU - Gemelli N.
AU - Oh J.
PY - 2013
SP - 58
EP - 66
DO - 10.5220/0004234800580066