Exploiting Social Interactions in Mobile Systems

  • Andrew G. Miklas
  • Kiran K. Gollu
  • Kelvin K. W. Chan
  • Stefan Saroiu
  • Krishna P. Gummadi
  • Eyal de Lara
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4717)


The popularity of handheld devices has created a flurry of research activity into new protocols and applications that can handle and exploit the defining characteristic of this new environment – user mobility. In addition to mobility, another defining characteristic of mobile systems is user social interaction. This paper investigates how mobile systems could exploit people’s social interactions to improve these systems’ performance and query hit rate. For this, we build a trace-driven simulator that enables us to re-create the behavior of mobile systems in a social environment. We use our simulator to study three diverse mobile systems: DTN routing protocols, firewalls preventing a worm infection, and a mobile P2P file-sharing system. In each of these three cases, we find that mobile systems can benefit substantially from exploiting social information.


Social Information Mobile System Friend Network Worm Infection Reality Mining 
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.


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. 1.
    Adar, E., Huberman, B.: Free riding on Gnutella. First Monday 5(10) (October 2000)Google Scholar
  2. 2.
    Albert, R., Barabasi, A.-L.: Statistical mechanics of complex networks. Reviews of Modern Physics 74(1), 47–97 (2002)CrossRefGoogle Scholar
  3. 3.
    Barabasi, A.-L., Albert, R.: Emergence of scaling in random networks. Science 286(5439), 509–512 (1999)CrossRefGoogle Scholar
  4. 4.
    CNET Mobile browsing becomes mainstream  (2006),
  5. 5.
    Cole, R.G.: Initial Studies on Worm Propagation in MANETS for Future Army Combat Systems (2004),
  6. 6.
    Cole, R.G., Phamdo, N., Rajab, M.A., Terzis, A.: Requirements of Worm Mitigation Technologies in MANETS. In: Principles of Advanced and Distribution Simulation (2005)Google Scholar
  7. 7.
    ComputerWorld. Cabir Worm Wriggles into U.S. Mobile Phones (2005),,10801,99935,00.html
  8. 8.
    Ebel, H., Davidsen, J., Bornholdt, S.: Dynamics of social networks. Complexity 8(2), 24–27 (2002)CrossRefGoogle Scholar
  9. 9.
    Granovetter, M.S.: The strength of weak ties. The American Journal of Sociology 78(6), 1360–1380 (1973)CrossRefGoogle Scholar
  10. 10.
    Gummadi, K.P., Dunn, R.J., Saroiu, S., Gribble, S.D., Levy, H.M., Zahorjan, J.: Measurement, modeling, and analysis of a peer-to-peer file-sharing workload. In: 19th ACM Symposium on Operating Systems Principles (SOSP), Bolton Landing, NY, USA, October 2003, ACM Press, New York (2003)Google Scholar
  11. 11.
    Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(026107), 1–4 (2002)Google Scholar
  12. 12.
    InfoSyncWorld. First Symbian OS Virus to Replicate over MMS Appears (2005),
  13. 13.
    InfoWorld: More mobile Internet users than wired in Japan (July 2006),
  14. 14.
    Jain, S., Fall, K., Patra, R.: Routing in a delay tolerant network. In: Proceedings of ACM Sigcomm, Portland, OR, USA (2004)Google Scholar
  15. 15.
    Jin, E.M., Girvan, M., Newman, M.E.J.: The structure of growing social networks. Physical Review E 64(046132), 1–8 (2001)Google Scholar
  16. 16.
    Jones, E.P., Li, L., Ward, P.A.S.: Practical routing in delay-tolerant networks. In: Proc. of ACM Sigcomm Workshop on Delay-Tolerant Networking, Philadelphia, PA, USA (2005)Google Scholar
  17. 17.
    JuiceCaster. Share your mobile life with juicecaster (2007),
  18. 18.
    Kangourouge:Proxidating, the first ever Bluetooth dating software for mobile phones (2007),
  19. 19.
    Lindgren, A., Doria, A., Shelen, O.: Probabilistic routing in intermittenly connected networks. In: Proceedings of ACM Mobihoc, Annapolis, MD, USA (2003)Google Scholar
  20. 20.
    Liogkas, N., Nelson, R., Kohler, E., Zhang, L.: Exploiting bittorrent for fun (but not profit). In: Proceedings of Proceedings of 5th International Workshop on Peer-to-Peer Systems (IPTPS), Santa Barbara, CA, USA (2006)Google Scholar
  21. 21.
    Locher, T., Moor, P., Schmid, S., Wattenhofer, R.: Free riding in bittorrent is cheap. In: Proceedings of HotNets, Irvine, CA, USA (2006)Google Scholar
  22. 22.
    Milgram, S.: The Familiar Stranger: An Aspect of Urban Anonymity. Addison-Wesley, Reading (1977)Google Scholar
  23. 23.
    MIT Media Lab: Reality Mining.
  24. 24.
    Moore, D., Paxson, V., Savage, S., Shannon, C., Staniford, S., Weaver, N.: The Spread of the Sapphire/Slammer Worm. Technical Report CAIDA, ICSI, Sillicon Defense, UC Berkeley EECS and UC San Diego (January 2003)Google Scholar
  25. 25.
    Moore, D., Shannon, C., Brown, J.: Code-red: a case study on the spread and victims of an internet worm. In: 2002 Internet Measurement Workshop (November 2002)Google Scholar
  26. 26.
    Niculescu, D., Nath, B.: Trajectory based forwarding and its applications. In: Proceedings of Mobicom, San Diego, CA, USA (2003)Google Scholar
  27. 27.
    Piatek, M., Isdal, T., Anderson, T., Krishnamurthy, A.: Do incentives build robustness in bittorrent. In: Proceedings of 4th Usenix Symposium on Networked Systems Design and Implementation (NSDI), Cambridge, MA, USA (2007)Google Scholar
  28. 28.
    Pogo. Pogo browser (2007),
  29. 29.
    Su, J., Chan, K.K.W., Miklas, A.G., Po, K., Akhavan, A., Saroiu, S., de Lara, E., Goel, A.: A preliminary investigation of worm infections in a bluetooth environment. In: 4th Workshop of Recurring Malcode (WORM), Fairfax, VA, USA (2006)Google Scholar
  30. 30.
    Su, J., Goel, A., de Lara, E.: An empirical evaluation of the student-net delay tolerant network. In: 3rd International Conference on Mobile and Ubiquitous Systems: Networks and Services (MOBIQUITOUS), San Jose, CA, USA (2006)Google Scholar
  31. 31.
    Vahdat, A., Becker, D.: Epidemic routing for partially-connected ad hoc networks. Technical Report CS-200006, Department of Computer Science, Duke University (April 2000)Google Scholar
  32. 32.
    Wang, Y., Jain, S., Martonosi, M., Fall, K.: Erasure-coding based routing for opportunistic networks. In: WDTN 2005: Proceeding of the 2005 ACM SIGCOMM workshop on Delay-tolerant networking, pp. 229–236. ACM Press, New York (2005)CrossRefGoogle Scholar
  33. 33.
    Watts, D.J., Strogatz, S.H.: Collective dynamics of ’small-world’ networks. Nature 393(6684), 440–442 (1998)CrossRefGoogle Scholar
  34. 34.
    Yan, G., Eidenbenz, S.: Bluetooth worms: Models, dynamics, and defense implications. In: 22nd Annual Computer Security Applications Conference, Miami Beach, FL, USA (2006)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2007

Authors and Affiliations

  • Andrew G. Miklas
    • 1
  • Kiran K. Gollu
    • 1
  • Kelvin K. W. Chan
    • 2
  • Stefan Saroiu
    • 1
  • Krishna P. Gummadi
    • 3
  • Eyal de Lara
    • 1
  1. 1.University of Toronto 
  2. 2.Google 
  3. 3.MPI for Software Systems 

Personalised recommendations