Ad-Hoc Information Spread between Mobile Devices: A Case Study in Analytical Modeling of Controlled Self-organization in IT Systems

  • Kamil Kloch
  • Jan W. Kantelhardt
  • Paul Lukowicz
  • Patrick Wüchner
  • Hermann de Meer
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5974)

Abstract

We present an example of the use of analytical models to predict global properties of large-scale information technology systems from the parameters of simple local interactions. The example is intended as a first step towards using complex systems modeling methods to control self-organization in organic systems. It is motivated by a concrete application scenario of information distribution in emergency situations, but is relevant to other domains such as malware spread or social interactions. Specifically, we show how the spread of information through ad-hoc interactions between mobile devices depends on simple local interaction rules and parameters such as user mobility and physical interaction range. We show how three qualitatively different regimes of information ‘infection rate’ can be analytically derived and validate our model in extensive simulations.

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. 1.
    Arai, T., Yoshida, E., Ota, J.: Information diffusion by local communication of multiple mobilerobots. In: Systems, Man and Cybernetics, 1993. Systems Engineering in the Service of Humans, Conference Proceedings, pp. 535–540 (1993)Google Scholar
  2. 2.
    Boccara, N.: Modeling Complex Systems. Springer, Heidelberg (2004)MATHGoogle Scholar
  3. 3.
    Chen, Z., Gao, L., Kwiat, K.: Modeling the spread of active worms. In: INFOCOM 2003. Twenty-Second Annual Joint Conference of the IEEE Computer and Communications Societies, vol. 3. IEEE, Los Alamitos (2003)Google Scholar
  4. 4.
    Ferscha, A., Zia, K.: Lifebelt: Silent directional guidance for crowd evacuation. In: IEEE ISWC 2009 (2009)Google Scholar
  5. 5.
    Mainzer, K.: Organic Computing and Complex Dynamical Systems Conceptual Foundations and Interdisciplinary Perspectives. Organic Computing, 105 (2008)Google Scholar
  6. 6.
    Nicol, D.M., Liljenstam, M.: Models of active worm defenses. In: Proc. of Measurement, Modeling and Analysis of the Internet Workshop, IMA 2004 (2004)Google Scholar
  7. 7.
    Staniford, S., Paxson, V., Weaver, N.: How to own the internet in your spare time. In: Proceedings of the 11th USENIX Security Symposium, Berkeley, CA, USA, pp. 149–167. USENIX Association (2002)Google Scholar
  8. 8.
    Zou, C.C., Gong, W., Towsley, D.: Code red worm propagation modeling and analysis. In: CCS 2002: Proceedings of the 9th ACM conference on Computer and communications security, pp. 138–147. ACM, New York (2002)CrossRefGoogle Scholar
  9. 9.
    Zou, C.C., Gong, W., Towsley, D.: Worm propagation modeling and analysis under dynamic quarantine defense. In: WORM 2003: Proceedings of the 2003 ACM workshop on Rapid malcode, pp. 51–60. ACM, New York (2003)CrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2010

Authors and Affiliations

  • Kamil Kloch
    • 1
  • Jan W. Kantelhardt
    • 2
  • Paul Lukowicz
    • 1
  • Patrick Wüchner
    • 3
  • Hermann de Meer
    • 3
  1. 1.Embedded Systems LabUniversity of PassauPassauGermany
  2. 2.Institut für PhysikMartin-Luther-Universität Halle-WittenbergHalle (Saale)Germany
  3. 3.Computer Networks and Computer CommunicationsUniversity of PassauPassauGermany

Personalised recommendations