Skip to main content
Springer Nature Link
Log in

Snapshot: a forwarding strategy based on analyzing network topology in opportunistic networks

  • Published:
Wireless Networks Aims and scope Submit manuscript

    We’re sorry, something doesn't seem to be working properly.

    Please try refreshing the page. If that doesn't work, please contact support so we can address the problem.

Abstract

We study a forwarding strategy in opportunistic networks which are one of the most challenging networks among mobile ad-hoc networks. In opportunistic networks, a node does not have knowledge about the entire network topology, which is essential in the mobile ad-hoc network’s forwarding strategy. Thus, node behavior is exploited to calculate future contact opportunities for forwarding a message. Utilizing social network analysis (e.g., similarity and centrality) has been proposed to improve the accuracy of the calculation task. This paper proposes a forwarding strategy based on an analysis of network topology. In the proposed strategy, each node takes a sequence of snapshots of its first-order neighbors during a warm-up period. Each node exchanges its own snapshots with each other, and then aggregates the snapshots in order to extract the network topology information. The extracted network topology is analyzed by social network analysis methods: compactness and algebraic connectivity. Forwarding decisions are made using the analysis of the features (compactness and algebraic connectivity). We present simulations using NS-2 and the home-cell community-based mobility model to show that the proposed forwarding strategy results in delay performances similar to the epidemic forwarding scheme, while maintaining reasonable network traffic. In addition, we demonstrate that the proposed strategy outperforms the SimBet and PRoPHET forwarding schemes with various communication ranges and memory space.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Subscribe and save

Springer+ Basic
$34.99 /Month
  • Get 10 units per month
  • Download Article/Chapter or eBook
  • 1 Unit = 1 Article or 1 Chapter
  • Cancel anytime
Subscribe now

Buy Now

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9
Fig. 10
Fig. 11
Fig. 12
Fig. 13

Similar content being viewed by others

References

  1. Boldrini, C., Conti, M., Jacopini, J., & Passarella, A. (2007). Hibop: A history based routing protocol for opportunistic networks. In Proceedings of WoWMoM 2007 (pp. 1–12).

  2. Boldrini, C., & Passarella, A. (2010). HCMM: Modelling spatial and temporal properties of human mobility driven by users’ social relationships. Computer Communications, 33(9), 1056–1074.

    Article  Google Scholar 

  3. Borgatti, S. P., Everett, M. G., & Johnson, J. C. (2013). Analyzing social networks. Washington, DC: SAGE Publications Limited.

    Google Scholar 

  4. Burns, B., Brock, O., & Levine, B. N. (2008). MORA routing and capacity building in disruption-tolerant networks. Ad Hoc Networks, 6(4), 600–620.

    Article  Google Scholar 

  5. Chung, F. R. (1997). Spectral graph theory (Vol. 92). Washington, DC: American Mathematical Society.

  6. Conti, M., Giordano, S., May, M., & Passarella, A. (2010). From opportunistic networks to opportunistic computing. IEEE Communications Magazine, 48(9), 126–139.

    Article  Google Scholar 

  7. Conti, M., & Kumar, M. (2010). Opportunities in opportunistic computing. IEEE Computer, 43(1), 42–50.

    Article  MATH  Google Scholar 

  8. Daly, E. M., & Haahr, M. (2009). Social network analysis for information flow in disconnected delay-tolerant MANETs. IEEE Transactions on Mobile Computing, 8(5), 606–621.

    Article  Google Scholar 

  9. Dang, H., & Wu, H. (2010). Clustering and cluster-based routing protocol for delay-tolerant mobile networks. IEEE Transactions on Wireless Communications, 9(6), 1874–1881.

    Article  MathSciNet  Google Scholar 

  10. Doria, A., Uden, M., & Pandey, D. (2009). Providing connectivity to the saami nomadic community. Generations, 1(2), 3.

    Google Scholar 

  11. Ferreira, A., Goldman, A., & Monteiro, J. (2010). Performance evaluation of routing protocols for MANETs with known connectivity patterns using evolving graphs. Wireless Networks, 16(3), 627–640.

    Article  Google Scholar 

  12. Gould, S. H. (1995). Variational methods for eigenvalue problems: An introduction to the methods of Rayleigh, Ritz, Weinstein, and Aronszajn. Mineola: Courier Dover.

    Google Scholar 

  13. Groenevelt, R., Nain, P., & Koole, G. (2005). The message delay in mobile ad hoc networks. Performance Evaluation, 62(1), 210–228.

    Article  Google Scholar 

  14. Grossglauser, M., & Tse, D. (2001). Mobility increases the capacity of ad-hoc wireless networks. In Proceedings of IEEE INFOCOM (pp. 1360–1369).

  15. Guangchun, L., Zhang, J., Ke, Q., & Haifeng, S. (2012). Location-aware social routing in delay tolerant networks. IEICE Transactions on Communications, 95(5), 1826–1829.

    Google Scholar 

  16. Hossmann, T., Spyropoulos, T., & Legendre, F. (2010). Know thy neighbor: Towards optimal mapping of contacts to social graphs for DTN routing. In Proceedings of IEEE INFOCOM (pp. 1–9).

  17. Hui, P., Crowcroft, J., & Yoneki, E. (2011). Bubble rap: Social-based forwarding in delay-tolerant networks. Mobile Computing, IEEE Transactions on, 10(11), 1576–1589.

    Article  Google Scholar 

  18. Issariyakul, T., & Hossain, E. (2011). Introduction to network simulator NS2. New York: Springer.

    Google Scholar 

  19. Jamakovic, A., & Van Mieghem, P. (2008). On the robustness of complex networks by using the algebraic connectivity. In Proceedings of NETWORKING 2008 Ad Hoc and Sensor Networks, Wireless Networks, Next Generation Internet (pp. 183–194).

  20. Juang, P., Oki, H., Wang, Y., Martonosi, M., Peh, L. S., & Rubenstein, D. (2002). Energy-efficient computing for wildlife tracking: Design tradeoffs and early experiences with ZebraNet. ACM Sigplan Notices, 37(10), 96–107.

    Article  Google Scholar 

  21. Lee, J., & Kim, S. (2011). FSRS routing method for energy efficiency through the new concept of flooding restriction in wireless ad-hoc networks. IEICE Transactions on Communications, 94(11), 3037–3048.

    Article  Google Scholar 

  22. Leguay, J., Friedman, T., & Conan, V. (2005). DTN routing in a mobility pattern space. In Proceedings of the 2005 ACM SIGCOMM Workshop on Delay-tolerant Networking (pp. 276–283).

  23. Lindgren, A., Doria, A., & Schelén, O. (2003). Probabilistic routing in intermittently connected networks. ACM SIGMOBILE Mobile Computing and Communications Review, 7(3), 19–20.

    Article  MATH  Google Scholar 

  24. Musolesi, M., Hailes, S., & Mascolo, C. (2005). Adaptive routing for intermittently connected mobile ad hoc networks. In Proceedings of IEEE WoWMoM 2005 (pp. 183–189).

  25. Network Simulator-2. (2014). http://www.isi.edu/nsnam/ns/. Accessed May 22, 2014.

  26. Ng, A. Y., Jordan, M. I., & Weiss, Y. (2001). On spectral clustering: Analysis and an algorithm. In Proceedings of Advances in Neural Information Processing Systems. Cambridge, MA: MIT Press.

  27. Pelusi, L., Passarella, A., & Conti, M. (2006). Opportunistic networking: Data forwarding in disconnected mobile ad hoc networks. IEEE Communications Magazine, 44(11), 134–141.

    Article  Google Scholar 

  28. Pentland, A., Fletcher, R., & Hasson, A. (2004). Daknet: Rethinking connectivity in developing nations. Computer, 37(1), 78–83.

    Article  Google Scholar 

  29. Ramanathan, R., Hansen, R., Basu, P., Rosales-Hain, R., & Krishnan, R. (2007). Prioritized epidemic routing for opportunistic networks. In Proceedings of MobiSys (pp. 62–66).

  30. Shih, T. F., & Yen, H. C. (2008). Location-aware routing protocol with dynamic adaptation of request zone for mobile ad hoc networks. Wireless Networks, 14(3), 321–333.

    Article  Google Scholar 

  31. Spielman, D. (2009). Spectral graph theory. Lecture Notes, Yale University.

  32. Stauffer, D., & Aharony, A. (1991). Introduction to percolation theory. New York: Taylor and Francis.

    Google Scholar 

  33. Vahdat, A., & Becker, D. (2000). Epidemic routing for partially connected ad hoc networks. Technical Report CS-200006, Duke University.

  34. Von Luxburg, U. (2007). A tutorial on spectral clustering. Statistics and Computing, 17(4), 395–416.

    Article  MathSciNet  Google Scholar 

  35. Widmer, J., & Le Boudec, J. Y. (2005). Network coding for efficient communication in extreme networks. In Proceedings of ACM SIGCOMM (pp. 284–291).

Download references

Acknowledgments

This research was supported by the Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Education, Science and Technology (2013R1A1A2011114).

Author information

Authors and Affiliations

  1. Department of Computer Science, Yonsei University, Seoul, Korea

    Junyeop Lee, Sun-Kyum Kim, Ji-Hyeun Yoon & Sung-Bong Yang

Authors
  1. Junyeop Lee
    View author publications

    You can also search for this author inPubMed Google Scholar

  2. Sun-Kyum Kim
    View author publications

    You can also search for this author inPubMed Google Scholar

  3. Ji-Hyeun Yoon
    View author publications

    You can also search for this author inPubMed Google Scholar

  4. Sung-Bong Yang
    View author publications

    You can also search for this author inPubMed Google Scholar

Corresponding author

Correspondence to Sung-Bong Yang.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Lee, J., Kim, SK., Yoon, JH. et al. Snapshot: a forwarding strategy based on analyzing network topology in opportunistic networks. Wireless Netw 21, 2055–2068 (2015). https://doi.org/10.1007/s11276-015-0900-9

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11276-015-0900-9

Keywords