STEPS - An Approach for Human Mobility Modeling

  • Anh Dung Nguyen
  • Patrick Sénac
  • Victor Ramiro
  • Michel Diaz
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6640)


In this paper we introduce Spatio-TEmporal Parametric Stepping (STEPS) - a simple parametric mobility model which can cover a large spectrum of human mobility patterns. STEPS makes abstraction of spatio-temporal preferences in human mobility by using a power law to rule the nodes movement. Nodes in STEPS have preferential attachment to favorite locations where they spend most of their time. Via simulations, we show that STEPS is able, not only to express the peer to peer properties such as inter-contact/contact time and to reflect accurately realistic routing performance, but also to express the structural properties of the underlying interaction graph such as small-world phenomenon. Moreover, STEPS is easy to implement, flexible to configure and also theoretically tractable.


Mobility Model Preferential Attachment Short Path Length Pause Time Human Mobility 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


  1. 1.
    Brockmann, D., Hufnagel, L., Geisel, T.: The scaling laws of human travel. Nature 439(7075), 462–465 (2006)CrossRefGoogle Scholar
  2. 2.
    Cai, H., Eun, D.: Toward stochastic anatomy of inter-meeting time distribution under general mobility models. In: Proceedings of the 9th ACM International Symposium on Mobile Ad hoc Networking and Computing, MobiHoc 2008, pp. 273–282. ACM, New York (2008)CrossRefGoogle Scholar
  3. 3.
    Camp, T., Boleng, J., Davies, V.: A survey of mobility models for ad hoc network research. Wireless Communications and Mobile Computing 2(5), 483–502 (2002)CrossRefGoogle Scholar
  4. 4.
    Chaintreau, A., Hui, P., Crowcroft, J., Diot, C., Gass, R., Scott, J.: Impact of human mobility on opportunistic forwarding algorithms. IEEE Transactions on Mobile Computing 6(6), 606–620 (2007)CrossRefGoogle Scholar
  5. 5.
    Ekman, F., Keränen, A., Karvo, J., Ott, J.: Working day movement model. In: Proceeding of the 1st ACM SIGMOBILE Workshop on Mobility Models, pp. 33–40. ACM, New York (2008)CrossRefGoogle Scholar
  6. 6.
    González, M., Hidalgo, C., Barabási, A.: Understanding individual human mobility patterns. Nature 453(7196), 779–782 (2008)CrossRefGoogle Scholar
  7. 7.
    Hsu, W., Spyropoulos, T., Psounis, K., Helmy, A.: Modeling spatial and temporal dependencies of user mobility in wireless mobile networks. IEEE/ACM Transactions on Networking 17(5), 1564–1577 (2009)CrossRefGoogle Scholar
  8. 8.
    Karagiannis, T., Le Boudec, J., Vojnovic, M.: Power law and exponential decay of inter contact times between mobile devices. IEEE Transactions on Mobile Computing, 183–194 (2010)Google Scholar
  9. 9.
    Lee, K., Hong, S., Kim, S., Rhee, I., Chong, S.: Slaw: A mobility model for human walks. (2009)Google Scholar
  10. 10.
    Musolesi, M., Mascolo, C.: A community based mobility model for ad hoc network research. In: Proceedings of the 2nd International Workshop on Multi-hop Ad hoc Networks: from Theory to Reality, pp. 31–38. ACM, New York (2006)CrossRefGoogle Scholar
  11. 11.
    Tang, J., Musolesi, M., Mascolo, C., Latora, V.: Characterising temporal distance and reachability in mobile and online social networks. ACM SIGCOMM Computer Communication Review 40(1), 118–124 (2010)Google Scholar
  12. 12.
    Thakur, G.S., Kumar, U., Helmy, A., Hsu, W.-J.: Analysis of Spatio-Temporal Preferences and Encounter Statistics for DTN Performance (July 2010)Google Scholar
  13. 13.
    Watts, D., Strogatz, S.: Collective dynamics of small-world networks. Nature 393(6684), 440–442 (1998)CrossRefGoogle Scholar
  14. 14.
    Yoon, J., Liu, M., Noble, B.: Random waypoint considered harmful. In: IEEE Societies INFOCOM 2003, Twenty-Second Annual Joint Conference of the IEEE Computer and Communications, vol. 2 (2003)Google Scholar

Copyright information

© IFIP International Federation for Information Processing 2011

Authors and Affiliations

  • Anh Dung Nguyen
    • 1
    • 2
  • Patrick Sénac
    • 1
    • 2
  • Victor Ramiro
    • 3
  • Michel Diaz
    • 2
  1. 1.ISAE/University of ToulouseToulouseFrance
  2. 2.LAAS/CNRSToulouseFrance
  3. 3.NIC Chile Research LabsSantiagoChile

Personalised recommendations