Efficient and Generalized Decentralized Monitoring of Regular Languages

  • Yliès Falcone
  • Tom Cornebize
  • Jean-Claude Fernandez
Part of the Lecture Notes in Computer Science book series (LNCS, volume 8461)


This paper proposes an efficient and generalized decentralized monitoring algorithm allowing to detect satisfaction or violation of any regular specification by local monitors alone in a system without central observation point. Our algorithm does not assume any form of synchronization between system events and communication of monitors, uses state machines as underlying mechanism for efficiency, and tries to keep the number and size of messages exchanged between monitors to a minimum. We provide a full implementation of the algorithm with an open-source benchmark to evaluate its efficiency in terms of number, size of exchanged messages, and delay induced by communication between monitors. Experimental results demonstrate the effectiveness of our algorithm which outperforms the previous most general one along several (new) monitoring metrics.


Global State Regular Language Linear Temporal Logic Atomic Proposition Local Component 
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.
    Falcone, Y., Jaber, M., Nguyen, T.H., Bozga, M., Bensalem, S.: Runtime verification of component-based systems. In: Barthe, G., Pardo, A., Schneider, G. (eds.) SEFM 2011. LNCS, vol. 7041, pp. 204–220. Springer, Heidelberg (2011)CrossRefGoogle Scholar
  2. 2.
    Zhou, W., Sokolsky, O., Loo, B.T., Lee, I.: dMaC: Distributed monitoring and checking. In: Bensalem, S., Peled, D.A. (eds.) RV 2009. LNCS, vol. 5779, pp. 184–201. Springer, Heidelberg (2009)CrossRefGoogle Scholar
  3. 3.
    Sen, K., Vardhan, A., Agha, G., Rosu, G.: Decentralized runtime analysis of multithreaded applications. In: 20th Parallel and Distributed Processing Symp. IEEE (2006)Google Scholar
  4. 4.
    Pnueli, A.: The temporal logic of programs. In: 18th Annual Symp. on Foundations of Computer Science, pp. 46–57 (1977)Google Scholar
  5. 5.
    Genon, A., Massart, T., Meuter, C.: Monitoring distributed controllers: When an efficient LTL algorithm on sequences is needed to model-check traces. In: Misra, J., Nipkow, T., Sekerinski, E. (eds.) FM 2006. LNCS, vol. 4085, pp. 557–572. Springer, Heidelberg (2006)CrossRefGoogle Scholar
  6. 6.
    Graf, S., Peled, D., Quinton, S.: Monitoring distributed systems using knowledge. In: Bruni, R., Dingel, J. (eds.) FMOODS/FORTE 2011. LNCS, vol. 6722, pp. 183–197. Springer, Heidelberg (2011)Google Scholar
  7. 7.
    Wang, Y., Yoo, T.S., Lafortune, S.: New results on decentralized diagnosis of discrete event systems. In: 42nd Ann. Allerton Conf. on Comm., Control, and Computing (2004)Google Scholar
  8. 8.
    Cassez, F.: The complexity of codiagnosability for discrete event and timed systems. In: Bouajjani, A., Chin, W.-N. (eds.) ATVA 2010. LNCS, vol. 6252, pp. 82–96. Springer, Heidelberg (2010)CrossRefGoogle Scholar
  9. 9.
    Tripakis, S.: Decentralized observation problems. In: 44th IEEE Conf. Decision and Control, pp. 6–11. IEEE (2005)Google Scholar
  10. 10.
    Bauer, A.K., Falcone, Y.: Decentralised LTL monitoring. In: Giannakopoulou, D., Méry, D. (eds.) FM 2012. LNCS, vol. 7436, pp. 85–100. Springer, Heidelberg (2012)CrossRefGoogle Scholar
  11. 11.
    Bacchus, F., Kabanza, F.: Planning for temporally extended goals. Annals of Mathematics and Artificial Intelligence 22, 5–27 (1998)CrossRefzbMATHMathSciNetGoogle Scholar
  12. 12.
    Bartocci, E.: Sampling-based decentralized monitoring for networked embedded systems. In: 3rd Int. Work. on Hybrid Autonomous Systems. EPTCS, vol. 124, pp. 85–99 (2013)Google Scholar
  13. 13.
    Bauer, A., Leucker, M., Schallhart, C.: Monitoring of real-time properties. In: Arun-Kumar, S., Garg, N. (eds.) FSTTCS 2006. LNCS, vol. 4337, pp. 260–272. Springer, Heidelberg (2006)CrossRefGoogle Scholar
  14. 14.
    Falcone, Y., Fernandez, J.-C., Mounier, L.: Runtime verification of safety-progress properties. In: Bensalem, S., Peled, D.A. (eds.) RV 2009. LNCS, vol. 5779, pp. 40–59. Springer, Heidelberg (2009)CrossRefGoogle Scholar
  15. 15.
    Falcone, Y., Fernandez, J.C., Mounier, L.: What can you verify and enforce at runtime? Software Tools for Technology Transfert 14, 349–382 (2012)CrossRefGoogle Scholar
  16. 16.
    Bauer, A., Leucker, M., Schallhart, C.: Runtime verification for LTL and TLTL. ACM Trans. Softw. Eng. Methodol. 20, 14 (2011)CrossRefGoogle Scholar
  17. 17.
    Cornebize, T., Falcone, Y.: DecentMon2 (2013),
  18. 18.
    Bauer, A.K.: LTL2Mon (2009),
  19. 19.
    Dwyer, M.B., Avrunin, G.S., Corbett, J.C.: Patterns in property specifications for finite-state verification. In: Intl. Conf. on Software Engineering (ICSE), pp. 411–420. ACM (1999)Google Scholar
  20. 20.
    Alavi, H., Avrunin, G., Corbett, J., Dillon, L., Dwyer, M., Pasareanu, C.: Specification patterns website (2011),
  21. 21.
    Falcone, Y., Mounier, L., Fernandez, J.C., Richier, J.L.: Runtime enforcement monitors: composition, synthesis, and enforcement abilities. Formal Methods in System Design 38, 223–262 (2011)CrossRefzbMATHGoogle Scholar

Copyright information

© IFIP International Federation for Information Processing 2014

Authors and Affiliations

  • Yliès Falcone
    • 1
  • Tom Cornebize
    • 1
  • Jean-Claude Fernandez
    • 1
  1. 1.Univ. Grenoble Alpes, LIG, VERIMAGGrenobleFrance

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