From Real Neighbors to Imaginary Destination: Emulation of Large Scale Wireless Sensor Networks

  • Bogdan Pavkovic
  • Jovan Radak
  • Nathalie Mitton
  • Franck Rousseau
  • Ivan Stojmenovic
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7363)


The ultimate test for many network layer protocols designed for wireless sensor networks would be to run on a large scale testbed. However, setting up a real-world large scale wireless sensor network (WSN) testbed requires access to a huge surface as well as extensive financial and human resources. Due to limited access to such infrastructures, the vast majority of existing theoretical and simulation studies in WSN are far from being validated in realistic environments. A more affordable approach is needed to provide preliminary insights on network protocol performances in large WSN. To replace large and expensive realistic testbeds, we introduce a novel approach to emulation. We propose a specifically designed experimental setup using a relatively small number of nodes forming a real one-hop neighborhood used to emulate any real WSN. The source node is a fixed sensor, and all other sensors are candidate forwarding neighbors towards a virtual destination. The source node achieves one forwarding step, then the virtual destination position and neighborhood are adjusted. The same source is used again to repeat the process. The main novelty is to spread available nodes regularly following a hexagonal pattern around the central node, used as the source, and selectively use subsets of the surrounding nodes at each step of the routing process to provide the desired density and achieve changes in configurations. Compared to real testbeds, our proposition has the advantages of emulating networks with any desired node distribution and densities, which may not be possible in a small scale implementation, and of unbounded scalability since we can emulate networks with an arbitrary number of nodes. Finally, our approach can emulate networks of various shapes, possibly with holes and obstacles. It can also emulate recovery mode in geographic routing, which appears impossible with any existing approach.


emulation simulation routing wireless sensor networks 


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. 1.
    Burin des Roziers, C., Chelius, G., Ducrocq, T., Fleury, E., Fraboulet, A., Gallais, A., Mitton, N., Noél, T., Vandaele, J.: Using SensLAB as a First Class Scientific Tool for Large Scale Wireless Sensor Network Experiments. In: Domingo-Pascual, J., Manzoni, P., Palazzo, S., Pont, A., Scoglio, C. (eds.) NETWORKING 2011, Part I. LNCS, vol. 6640, pp. 147–159. Springer, Heidelberg (2011)CrossRefGoogle Scholar
  2. 2.
    Canonico, R., Di Gennaro, P., Manetti, V., Ventre, G.: Virtualization Techniques in Network Emulation Systems. In: Bougé, L., Forsell, M., Träff, J.L., Streit, A., Ziegler, W., Alexander, M., Childs, S. (eds.) Euro-Par Workshops 2007. LNCS, vol. 4854, pp. 144–153. Springer, Heidelberg (2008)CrossRefGoogle Scholar
  3. 3.
    Coulson, G., Porter, B., Chatzigiannakis, I., Koninis, C., Fischer, S., Pfisterer, D., Bimschas, D., Braun, T., Hurni, P., Anwander, M., Wagenknecht, G., Fekete, S.P., Kröller, A., Baumgartner, T.: Flexible experimentation in wireless sensor networks. Commun. ACM 55(1), 82–90 (2012)CrossRefGoogle Scholar
  4. 4.
    Fall, K.: Network Emulation in the Vint/NS Simulator. In: Proceedings of ISCC 1999, pp. 244–250 (1999)Google Scholar
  5. 5.
    Grau, A., Herrmann, K., Rothermel, K.: Efficient and scalable network emulation using adaptive virtual time. In: International Conference on Computer Communications and Networks, pp. 1–6 (2009)Google Scholar
  6. 6.
    Judd, G., Steenkiste, P.: Using emulation to understand and improve wireless networks and applications. In: NSDI (2005)Google Scholar
  7. 7.
    Ke, Q., Maltz, D.A., Johnson, D.B.: Emulation of multi-hop wireless ad hoc networks. In: Proceedings of the Seventh International Workshop on Mobile Multimedia Communications, MOMUC 2000. IEEE Communications Society (October 2000)Google Scholar
  8. 8.
    Liu, Y., He, Y., Li, M., Wang, J., Liu, K., Mo, L., Dong, W., Yang, Z., Xi, M., Zhao, J., Li, X.-Y.: Does Wireless Sensor Network Scale? A Measurement Study on GreenOrbs. In: 2011 Proceedings IEEE INFOCOM, pp. 873–881 (April 2011)Google Scholar
  9. 9.
    Lukic, M., Pavkovic, B., Mitton, N., Stojmenovic, I.: Greedy geographic routing algorithms in real environment. In: MSN, pp. 86–93 (2009)Google Scholar
  10. 10.
    Maier, S., Herrscher, D., Rothermel, K.: Experiences with node virtualization for scalable network emulation. Computer Communications 30(5), 943–956 (2007); Advances in Computer Communications Networks CrossRefGoogle Scholar
  11. 11.
    Onat, F.A., Stojmenovic, I., Yanikomeroglu, H.: Generating random graphs for the simulation of wireless ad hoc, actuator, sensor, and internet networks. Pervasive and Mobile Computing 4(5), 597–615 (2008)CrossRefGoogle Scholar
  12. 12.
    Park, S., Savvides, A., Srivastava, M.B.: Sensorsim: A simulation framework for sensor networks. In: Proceedings of MSWiM (August 2000)Google Scholar
  13. 13.
    Senslab. Very large scale open wireless sensor network testbed,
  14. 14.
    Sobeih, A., Hou, J.C., Lu-Chuan, K., Li, N., Zhang Ning, H., Chen, W.P., Tyan, H.Y., Lim, H.: J-sim: a simulation and emulation environment for wireless sensor networks. IEEE of Wireless Communications 13(4), 104–119 (2006)CrossRefGoogle Scholar
  15. 15.
    Stojmenovic, I.: Simulations in Wireless Sensor and Ad Hoc Networks: Matching and Advancing Models, Metrics, and Solutions. IEEE of Communications Magazine 46(12), 102–107 (2008)CrossRefGoogle Scholar
  16. 16.
    Stojmenovic, I.: Localized network layer protocols in wireless sensor networks based on optimizing cost over progress ratio. IEEE Network 20(1), 21–27 (2006)CrossRefGoogle Scholar
  17. 17.
    Sventek, J., Maclean, A., McIlroy, R., Milos, G.: Xenotiny: Emulating wireless sensor networks on xen. Technical report, University of Glasgow, Department of Computing Science (2008)Google Scholar
  18. 18.
    Wang, Y., Song, W.-Z., Wang, W., Li, X.-Y., Dahlberg, T.A.: Learn: Localized energy aware restricted neighborhood routing for ad hoc networks. In: The 3rd Annual IEEE Communications Society Conference on Sensor and Ad Hoc Communications and Networks, IEEE SECON (2006)Google Scholar
  19. 19.
    Wattenhofer, R., Zollinger, A.: Xtc: A practical topology control algorithm for ad-hoc networks. In: IPDPS (2004)Google Scholar
  20. 20.
    WISEBED. Wireless Sensor Network Testbeds,
  21. 21.

Copyright information

© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  • Bogdan Pavkovic
    • 1
  • Jovan Radak
    • 2
  • Nathalie Mitton
    • 2
  • Franck Rousseau
    • 1
  • Ivan Stojmenovic
    • 3
  1. 1.Grenoble Informatics Laboratory (LIG)University of GrenobleFrance
  2. 2.INRIA Lille – Nord EuropeFrance
  3. 3.SITEUniversity of OttawaCanada

Personalised recommendations