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Node Mobility Modeling in Ad Hoc Networks through a Birth and Death Process

  • Carlos A. V. Campos
  • Luis F. M. de Moraes
  • Eduardo M. Hargreaves
  • Bruno A. A. Nunes
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6869)

Abstract

Mobility models are used to represent the movement behavior of mobile devices in ad hoc networks simulations. As a consequence, the results obtained via simulations for specific characteristics related to mobile ad hoc networks are expected to be significantly dependent upon the choice of a particular mobility model under consideration. In this context, we present in this work a new mobility model, based on Birth-Death stochastic processes, which allows us to adjust mobility parameters according to the movement profile intended to be represented. The impact of mobility models in the simulation of ad hoc networks is observed through the performance evaluation of metrics related to the AODV routing protocol, by comparing the results obtained under the Birth-Death framework used in this paper with those calculated under the Generic Individual Mobility Markovian and the Random Waypoint models.

Keywords

MANETs mobility model birth-death process 

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References

  1. 1.
    Baumann, R., Legendre, F., Sommer, P.: Generic Mobility Simulation Framework GMSF. In: ACM Mobility Models, Hong Kong, China (2008)Google Scholar
  2. 2.
    Bettstetter, C.: Smooth is better than sharp: a random mobility model for simulation of wireless networks. In: MSWIM 2001, pp. 19–27 (2001)Google Scholar
  3. 3.
    Broch, J., Maltz, D.A., Johnson, D.B., Hu, Y.C., Jetcheva, J.: A performance comparison of multi-hop wireless ad hoc network routing protocols. In: ACM/IEEE MOBICOM 1998, pp. 85–97 (1998)Google Scholar
  4. 4.
    Camp, T., Boleng, J., Davies, V.: A survey of mobility models for ad hoc network research. Wireless Communications & Mobile Computing 2(5), 483–502 (2002)CrossRefGoogle Scholar
  5. 5.
    Campos, C.A.V., de Moraes, L.F.M.: A markovian model representation of individual mobility scenarios in ad hoc networks and its evaluation. EURASIP Journal on Wireless Communications and Networking (January 2007)Google Scholar
  6. 6.
    Fall, K., Varadhan, K.: The NS manual, http://www.isi.edu/nsnam/ns/ns-documentation.html (last access in April 15, 2011)
  7. 7.
    Haverkort, B.R.: Performance of Computer Communication Systems: A Model-Based Approach. John Wiley & Sons, New York (1998)CrossRefGoogle Scholar
  8. 8.
    Jardosh, A., Belding-Royer, E.M., Almeroth, K.C., Suri, S.: Towards realistic mobility models for mobile ad hoc networks. In: MobiCom 2003, pp. 217–229 (2003)Google Scholar
  9. 9.
    Kim, S., Lee, C.H., Eun, D.Y.: Super-diffusive Behavior of Mobile Nodes from GPS Traces. In: ACM Mobicom Poster Abstract 2007 (2007)Google Scholar
  10. 10.
    Kleinrock, L.: Queuing Systems, vol. 1. John Wiley & Sons Publishers, Chichester (1975)zbMATHGoogle Scholar
  11. 11.
    Le Boudec, J.Y., Vojnovic, M.: Perfect Simulation and Stationarity of a Class of Mobility Models. In: INFOCOM 2005 (2005)Google Scholar
  12. 12.
    Musolesi, M., Mascolo, C.: Designing Mobility Models Based on Social Network Theory. ACM M2CR 11(3), 59–70 (2007)Google Scholar
  13. 13.
    Rhee, I., Shin, M., Hong, S., Lee, K., Chong, S.: On the Levy-walk Nature Human Mobility. In: IEEE Infocom 2008, Phoenix, USA (2008)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2011

Authors and Affiliations

  • Carlos A. V. Campos
    • 1
  • Luis F. M. de Moraes
    • 2
  • Eduardo M. Hargreaves
    • 2
  • Bruno A. A. Nunes
    • 2
  1. 1.Department of Applied InformaticsFederal University of State of Rio de Janeiro - UNIRIORio de JaneiroBrazil
  2. 2.Laboratory of High Speed Networks - RAVEL/COPPEFederal University of Rio de Janeiro - UFRJRio de JaneiroBrazil

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