Parameterized Verification of Track Topology Aggregation Protocols

  • Sergio Feo-Arenis
  • Bernd Westphal
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7892)


We present an approach for the verification aggregation protocols, which may be used to perform critical tasks and thus should be verified. We formalize the class of track topology aggregation protocols and provide a parameterized proof of correctness where the problem is reduced to checking a property of the node’s aggregation algorithm. We provide a verification rule based on our property and illustrate the approach by verifying a non-trivial aggregation protocol.


Wireless Sensor Network Model Check Sink Node Aggregation Function Aggregation Relation 
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.


  1. 1.
    Apt, K.R., Kozen, D.: Limits for automatic verification of finite-state concurrent systems. Inf. Process. Lett. 22(6), 307–309 (1986)MathSciNetCrossRefGoogle Scholar
  2. 2.
    Barnett, M., Chang, B.-Y.E., DeLine, R., Jacobs, B., Leino, K.R.M.: Boogie: A modular reusable verifier for object-oriented programs. In: de Boer, F.S., Bonsangue, M.M., Graf, S., de Roever, W.P. (eds.) FMCO 2005. LNCS, vol. 4111, pp. 364–387. Springer, Heidelberg (2006)CrossRefGoogle Scholar
  3. 3.
    Brown, O., Eremenko, P.: The value proposition for Fractionated space architectures. In: AIAA Space 2006. No. 7506. AIAA (2006)Google Scholar
  4. 4.
    Clarke, E.M., Grumberg, O., Jha, S.: Verifying parameterized networks. ACM Trans. Program. Lang. Syst. 19(5), 726–750 (1997)CrossRefGoogle Scholar
  5. 5.
    Delzanno, G., Sangnier, A., Zavattaro, G.: Verification of ad hoc networks with node and communication failures. In: Giese, H., Rosu, G. (eds.) FORTE 2012 and FMOODS 2012. LNCS, vol. 7273, pp. 235–250. Springer, Heidelberg (2012)CrossRefGoogle Scholar
  6. 6.
    Emerson, E.A., Namjoshi, K.S.: On reasoning about rings. Int. J. Found. Comput. Sci. 14(4), 527–550 (2003)MathSciNetzbMATHCrossRefGoogle Scholar
  7. 7.
    Feng, J., Eager, D.L., Makaroff, D.J.: Aggregation protocols for high rate, low delay data collection in sensor networks. In: Fratta, L., Schulzrinne, H., Takahashi, Y., Spaniol, O. (eds.) NETWORKING 2009. LNCS, vol. 5550, pp. 26–39. Springer, Heidelberg (2009)CrossRefGoogle Scholar
  8. 8.
    Feo-Arenis, S., Westphal, B.: Formal verification of a parameterized data aggregation protocol. In: Brat, G., Rungta, N., Venet, A. (eds.) NFM 2013. LNCS, vol. 7871, pp. 428–434. Springer, Heidelberg (2013)Google Scholar
  9. 9.
    Gobriel, S., Khattab, S., Mossé, D., Brustoloni, J., Melhem, R.: Ridesharing: Fault tolerant aggregation in sensor networks using corrective actions. In: IEEE Communications Society Conference on Sensor, Mesh and Ad Hoc Communications and Networks, pp. 595–604 (2006)Google Scholar
  10. 10.
    Iskander, M.K., Lee, A.J., et al.: Privacy and robustness for data aggregation in wireless sensor networks. In: 17th ACM Conference on Computer and Communications Security, pp. 699–701. ACM (2010)Google Scholar
  11. 11.
    Kesten, Y., Pnueli, A., Shahar, E., Zuck, L.D.: Network invariants in action. In: Brim, L., Jančar, P., Křetínský, M., Kučera, A. (eds.) CONCUR 2002. LNCS, vol. 2421, pp. 101–115. Springer, Heidelberg (2002)CrossRefGoogle Scholar
  12. 12.
    Liu, M., Gong, H.G., Mao, Y.C., Chen, L.J., Xie, L.: A distributed energy-efficient data gathering and aggregation protocol for wireless sensor networks. Journal of Software 16(12), 2106–2116 (2005)zbMATHCrossRefGoogle Scholar
  13. 13.
    Montresor, A., Jelasity, M., Babaoglu, O.: Robust aggregation protocols for large-scale overlay networks. In: 2004 International Conference on Dependable Systems and Networks, pp. 19–28. IEEE (2004)Google Scholar
  14. 14.
    Namjoshi, K.S., Trefler, R.J.: Uncovering symmetries in irregular process networks. In: Giacobazzi, R., Berdine, J., Mastroeni, I. (eds.) VMCAI 2013. LNCS, vol. 7737, pp. 496–514. Springer, Heidelberg (2013)CrossRefGoogle Scholar
  15. 15.
    Pnueli, A., Ruah, S., Zuck, L.D.: Automatic deductive verification with invisible invariants. In: Margaria, T., Yi, W. (eds.) TACAS 2001. LNCS, vol. 2031, pp. 82–97. Springer, Heidelberg (2001)CrossRefGoogle Scholar

Copyright information

© IFIP International Federation for Information Processing 2013

Authors and Affiliations

  • Sergio Feo-Arenis
    • 1
  • Bernd Westphal
    • 1
  1. 1.Albert-Ludwigs-Universität FreiburgGermany

Personalised recommendations