Group Based Routing in Disconnected Ad Hoc Networks

  • Markose Thomas
  • Arobinda Gupta
  • Srinivasan Keshav
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4297)


In this paper, we propose a routing protocol for disconnected ad hoc networks where most nodes tend to move about in groups. To the best of our knowledge, no routing protocol for disconnected ad hoc networks has been designed earlier keeping in mind possible group patterns formed by the movement of nodes. Our protocol works by identifying groups using an efficient distributed group membership protocol, and then routing at the group level, rather than at the node level. The protocol is designed so that existing concepts of routing in disconnected ad hoc networks can be extended to work at the group level. Initial simulations across a broad spectrum of parameters suggest that our protocol performs better in terms of delivery ratio and latency over traditional approaches like AODV [1], and also over disconnected routing approaches like the 2-Hop routing protocol [2].


Destination Node Delivery Ratio Group Leader Mobility Model Communication Range 
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.
    Perkins, C.E., Belding-Royer, E.M.: Ad-hoc on-demand distance vector routing. In: WMCSA, pp. 90–100 (1999)Google Scholar
  2. 2.
    Grossglauser, M., Tse, D.N.C.: Mobility increases the capacity of ad hoc wireless networks. IEEE/ACM Trans. Netw. 10, 477–486 (2002)CrossRefGoogle Scholar
  3. 3.
    Perkins, C., Bhagwat, P.: Highly dynamic destination-sequenced distance-vector routing (DSDV) for mobile computers. In: ACM SIGCOMM 1994 Conference on Communications Architectures, Protocols and Applications, pp. 234–244 (1994)Google Scholar
  4. 4.
    Johnson, D.B., Maltz, D.A.: Dynamic source routing in ad hoc wireless networks. In: Mobile Computing, vol. 353. Kluwer Academic Publishers, Dordrecht (1996)Google Scholar
  5. 5.
    Vahdat, A., Becker, D.: Epidemic routing for partially connected ad hoc networks. Technical Report CS-200006, Duke University (2000)Google Scholar
  6. 6.
    Jain, S., Fall, K., Patra, R.: Routing in a delay tolerant network. In: SIGCOMM 2004: Proceedings of the 2004 conference on Applications, technologies, architectures, and protocols for computer communications, pp. 145–158. ACM Press, New York (2004)CrossRefGoogle Scholar
  7. 7.
    Lindgren, A., Doria, A., Schelén, O.: Probabilistic routing in intermittently connected networks. In: Dini, P., Lorenz, P., de Souza, J.N. (eds.) SAPIR 2004. LNCS, vol. 3126, pp. 239–254. Springer, Heidelberg (2004)CrossRefGoogle Scholar
  8. 8.
    Musolesi, M., Hailes, S., Mascolo, C.: Adaptive routing for intermittently connected mobile ad hoc networks. In: Proceedings of the IEEE 6th International Symposium on a World of Wireless, Mobile, and Multimedia Networks (WoWMoM 2005), Taormina, Italy. IEEE Press, Los Alamitos (2005)Google Scholar
  9. 9.
    Jones, E.P.C., Li, L., Ward, P.A.S.: Practical routing in delay-tolerant networks. In: WDTN 2005: Proceeding of the 2005 ACM SIGCOMM workshop on Delay-tolerant networking, pp. 237–243. ACM Press, New York (2005)CrossRefGoogle Scholar
  10. 10.
    Shah, R.C., Roy, S., Jain, S., Brunette, W.: Data mules: modeling a three-tier architecture for sparse sensor networks. In: Proceedings of the First IEEE International Workshop on Sensor Network Protocols and Applications, pp. 30–41 (2003)Google Scholar
  11. 11.
    Camp, T., Boleng, J., Davies, V.: A survey of mobility models for ad hoc network research. Wireless Communications and Mobile Computing (WCMC): Special issue on Mobile Ad Hoc Networking: Research, Trends and Applications 2, 483–502 (2002)Google Scholar
  12. 12.
    Hong, X., Gerla, M., Pei, G., Chiang, C.: A group mobility model for ad hoc wireless networks. In: Proceedings of ACM/IEEE MSWiM 1999, Seattle, WA, pp. 53–60 (1999)Google Scholar
  13. 13.
    Musolesi, M., Hailes, S., Mascolo, C.: An ad hoc mobility model founded on social network theory. In: Proceedings of ACM/IEEE MSWiM 2004, Venice, Italy, pp. 20–24. ACM Press, New York (2004)CrossRefGoogle Scholar
  14. 14.
    Juang, P., Oki, H., Wang, Y., Martonosi, M., Peh, L., Rubenstein, D.: Energy-efficient computing for wildlife tracking: Design tradeoffs and early experiences with zebranet. In: ASPLOS, San Jose, CA (2002)Google Scholar
  15. 15.
    Franz, W., Eberhardt, E., Luchenbach, T.: Fleetnet - Internet on the road. In: Proceedings of 8th World Congress on Intelligent Transport Systems (2001)Google Scholar
  16. 16.
    McCanne, S., Floyd, S.: ns network simulator (2005),

Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Markose Thomas
    • 1
  • Arobinda Gupta
    • 2
  • Srinivasan Keshav
    • 3
  1. 1.Google, Inc.BangaloreIndia
  2. 2.Dept. of Computer Science & EngineeringIndian Institute of TechnologyKharagpur
  3. 3.School of Computer ScienceUniversity of Waterloo 

Personalised recommendations