A Context and Content-Based Routing Protocol for Mobile Sensor Networks

  • Gianpaolo Cugola
  • Matteo Migliavacca
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5432)


The need of monitoring people, animals, and things in general, brings to consider mobile WSNs besides traditional, fixed ones. Moreover, several advanced scenarios, like those including actuators, involve multiple sinks. Mobility and multiple sinks radically changes the way routing is performed, while the peculiarities of WSNs make it difficult to reuse protocols designed for other types of mobile networks.

In this paper, we describe CCBR, a Context and Content-Based Routing protocol explicitly designed for multi-sink, mobile WSNs. CCBR adopts content-based addressing to effectively support the data-centric communication paradigm usually adopted by WSN applications. It also takes into account the characteristics (i.e., context) of the sensors to filter data.

Simulations show that CCBR outperforms alternative approaches in the multi-sink, mobile scenarios it was designed for, while providing good performance in more traditional (fixed) scenarios.


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. 1.
    Carzaniga, A., Wolf, A.L.: Content-based networking: A new communication infrastructure. In: König-Ries, B., Makki, K., Makki, S.A.M., Pissinou, N., Scheuermann, P. (eds.) IMWS 2001. LNCS, vol. 2538, pp. 59–68. Springer, Heidelberg (2002)CrossRefGoogle Scholar
  2. 2.
    Intanagonwiwat, C., Govindan, R., Estrin, D., Heideman, J., Silva, F.: Directed diffusion for wireless sensor networking. Trans. on Netw. 11(1), 2–16 (2003)CrossRefGoogle Scholar
  3. 3.
    Hauer, J.H., Handziski, V., Köpke, A., Willig, A., Wolisz, A.: A component framework for content-based publish/subscribe in sensor networks. Wireless Sensor Networks, 369–385 (2008)Google Scholar
  4. 4.
    Mottola, L., Cugola, G., Picco, G.P.: A self-repairing tree topology enabling content-based routing in mobile ad hoc networks. IEEE Trans. on Mobile Computing 7(8), 946–960 (2008)CrossRefGoogle Scholar
  5. 5.
    Baldoni, R., Beraldi, R., Querzoni, L., Cugola, G., Migliavacca, M.: Content-based routing in highly dynamic mobile ad hoc networks. Int. Journ. of Perv. Comp. and Comm. 1(4), 277–288 (2005)Google Scholar
  6. 6.
    Costa, P., Migliavacca, M., Picco, G.P., Cugola, G.: Epidemic algorithms for reliable content-based publish-subscribe: An evaluation. In: ICDCS, pp. 552–561 (2004)Google Scholar
  7. 7.
    Picco, G.P., Cugola, G., Murphy, A.L.: Efficient content-based event dispatching in the presence of topological reconfiguration. In: ICDCS, pp. 234–243 (2003)Google Scholar
  8. 8.
    OMNeT++ Web page, http://www.omnetpp.org
  9. 9.
    Mobility Framework for OMNeT++ Web page, http://mobility-fw.sourceforge.net
  10. 10.
    Luo, H., Ye, F., Cheng, J., Lu, S., Zhang, L.: Ttdd: Two-tier data dissemination in large-scale wireless sensor networks. Wireless Networks 11(1-2), 161–175 (2005)CrossRefGoogle Scholar
  11. 11.
    Kim, H.S., Abdelzaher, T.F., Kwon, W.H.: Minimum-energy asynchronous dissemination to mobile sinks in wireless sensor networks. In: SenSys (2003)Google Scholar
  12. 12.
    Hwang, K.-i., In, J., Eom, D.-S.: Distributed dynamic shared tree for minimum energy data aggregation of multiple mobile sinks in wireless sensor networks. In: Römer, K., Karl, H., Mattern, F. (eds.) EWSN 2006. LNCS, vol. 3868, pp. 132–147. Springer, Heidelberg (2006)CrossRefGoogle Scholar
  13. 13.
    Shah, R., Roy, S., Jain, S., Brunette, W.: Data mules: Modeling a three-tier architecture for sparse sensor networks. In: IEEE SNPA Workshop (2003)Google Scholar
  14. 14.
    Somasundara, A., Kansal, A., Jea, D., Estrin, D., Srivastava, M.: Controllably mobile infrastructure for low energy embedded networks. IEEE Transactions on Mob. Comp. 5(8), 958–973 (2006)CrossRefGoogle Scholar
  15. 15.
    Chatzigiannakis, I., Kinalis, A., Nikoletseas, S.: Efficient data propagation strategies in wireless sensor networks using a single mobile sink. Comput. Commun. 31(5) (2008)Google Scholar
  16. 16.
    Ammari, H.M., Das, S.K.: Promoting heterogeneity, mobility, and energy-aware voronoi diagram in wireless sensor networks. IEEE TPDS 19(7), 995–1008 (2008)Google Scholar
  17. 17.
    Bonnet, P., Leopold, M., Madsen, K.: Hogthrob: towards a sensor network infrastructure for sow monitoring. In: DATE (2006)Google Scholar
  18. 18.
    Butler, Z., Corke, P., Peterson, R., Rus, D.: Dynamic virtual fences for controlling cows. In: Experim. Robotics IX. Springer Tracts in Adv. Rob. Springer, Heidelberg (2006)Google Scholar
  19. 19.
    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 (October 2002)Google Scholar
  20. 20.
    Pasztor, B., Musolesi, M., Mascolo, C.: Opportunistic mobile sensor data collection with scar. In: MASS (2007)Google Scholar
  21. 21.
    Henriksson, D., Abdelzaher, T., Ganti, R.: A caching-based approach to routing in delay-tolerant networks. In: ICCCN 2007, August 2007, pp. 69–74 (2007)Google Scholar
  22. 22.
    Luo, T.L., Huang, C., Abdelzaher, Stankovic, J.: Envirostore: A cooperative storage system for disconnected operation in sensor networks (2007)Google Scholar
  23. 23.
    Petrovic, M., Muthusamy, V., Jacobsen, H.A.: Content-based routing in mobile ad hoc networks. In: MobiQuitous, pp. 45–55 (2005)Google Scholar
  24. 24.
    Ye, F., Zhong, G., Lu, S., Zhang, L.: Gradient broadcast: a robust data delivery protocol for large scale sensor networks. Wirel. Netw. 11(3), 285–298 (2005)CrossRefGoogle Scholar
  25. 25.
    Bokareva, T., Bulusu, N., Jha, S.: A performance comparison of data dissemination protocols for wireless sensor networks. In: GlobeCom Workshops 2004, November -3 December 2004, pp. 85–89. IEEE, Los Alamitos (2004)Google Scholar
  26. 26.
    He, T., Blum, B.M., Cao, Q., Stankovic, J.A., Son, S.H., Abdelzaher, T.F.: Robust and timely communication over highly dynamic sensor networks. Real-Time Syst. 37(3), 261–289 (2007)CrossRefMATHGoogle Scholar
  27. 27.
    Heissenbüttel, M., Braun, T., Wälchli, M., Bernoulli, T.: Evaluating the limitations of and alternatives in beaconing. Ad Hoc Netw 5(5), 558–578 (2007)CrossRefGoogle Scholar
  28. 28.
    Zorzi, M., Rao, R.R.: Geographic random forwarding (geraf) for ad hoc and sensor networks: Multihop performance. IEEE Trans. Mob. Comput. 2(4), 337–348 (2003)CrossRefGoogle Scholar
  29. 29.
    Heissenbüttel, M., Braun, T., Bernoulli, T., Wälchli, M.: Blr: Beacon-less routing algorithm for mobile ad hoc networks. Comp. Comm. 27(11), 1076–1086 (2004)CrossRefGoogle Scholar
  30. 30.
    Biswas, S., Morris, R.: Exor: opportunistic multi-hop routing for wireless networks. In: SIGCOMM, pp. 133–144 (2005)Google Scholar
  31. 31.
    Mastrogiovanni, M., Petrioli, C., Rossi, M., Vitaletti, A., Zorzi, M.: Integrated data delivery and interest dissemination techniques for wireless sensor networks. In: GLOBECOM (2006)Google Scholar
  32. 32.
    Bletsas, A., Khisti, A., Reed, D.P., Lippman, A.: A simple cooperative diversity method based on network path selection. IEEE JSAC 24(3), 659–672 (2006)Google Scholar
  33. 33.
    Dutta, P., Culler, D., Shenker, S.: Procrastination might lead to a longer and more useful life. In: 6th Workshop on Hot Topics in Networks (HotNets VI) (2007)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2009

Authors and Affiliations

  • Gianpaolo Cugola
    • 1
  • Matteo Migliavacca
    • 1
  1. 1.Dipartimento di Elettronica e InformazionePolitecnico di MilanoItaly

Personalised recommendations