A Distributed Computing Model for Dataflow, Controlflow, and Workflow in Fractionated Cyber-Physical Systems

Part of the Lecture Notes in Computer Science book series (LNCS, volume 8808)


With the ongoing trend to parallelize computations for scalability, better performance, and reliability, distributed dataflow models are attracting interest at all design levels, ranging from processorarchitectures to local- and wide-area computing clusters in the cloud. Data-driven computation has also been an important paradigm in sensor networks and embedded systems, which have evolved into a larger research effort on networked cyber-physical systems (NCPS), that can sense and affect their environment. Fractionated cyber-physical systems (FCPS) are an interesting subclass of NCPS where the redundancy and diversity of many unreliable and potentially heterogeneous networked components is exploited to improve scalability, reliability, and verifiability of the overall system. In this paper we present the theory of a new distributed computing model for such systems as a first step toward a model-based design methodology for FCPS. To uniformly capture dataflow, controlflow, and workflow, we use a subclass of Petri nets as an intuitive high-level model, which is translated into a weaker model — namely, a new variant of Petri nets that does not make any atomicity assumptions but instead uses a partial order to ensure eventual consistency. In the full version of this paper, we briefly discuss an application to unmanned aerial vehicle (UAV) swarms, which has been implemented on top of a prototype of our theory for both simulation models and real world deployments.


Unmanned Aerial Vehicle Label Transition System Strict Partial Order Causality Cone VHSIC Hardware Description Language 
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.


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. 1.
    OpenCL 1.1 Specification (September 2010)Google Scholar
  2. 2.
    Arvind, B.: A language for hardware design, simulation, synthesis and verification. In: Proc. First ACM/IEEE Int. Conf. Formal Methods and Models for Co-Design, MEMOCODE 2003, pp. 249 (2003)Google Scholar
  3. 3.
    Baccelli, F., Furmento, N., Gaujal, B.: Parallel and distributed simulation of free choice Petri nets. SIGSIM Simul. Dig. 25, 3–10 (1995)CrossRefGoogle Scholar
  4. 4.
    Best, E.: Structure theory of Petri nets: The free choice hiatus. In: Advances in Petri Nets 1986, Part I on Petri Nets: Central Models and Their Properties, pp. 168–205. Springer-Verlag (1987)Google Scholar
  5. 5.
    Brown, O., Eremenko, P.: Fractionated space architectures: A vision for responsive space. In: 4th Responsive Space Conf. (2006)Google Scholar
  6. 6.
    Chiola, G., Ferscha, A.: Distributed simulation of timed Petri nets: Exploiting the net structure to obtain efficiency. In: 14th Int. Conf. Application and Theory of Petri Nets, pp. 14–6 (1993)Google Scholar
  7. 7.
    Dean, J., Ghemawat, S.: MapReduce: Simplified data processing on large clusters. Commun. ACM 51, 107–113 (2008)CrossRefGoogle Scholar
  8. 8.
    Deelman, E., Singh, G., Su, M.-H., Blythe, J., Gil, Y., Kesselman, C., Mehta, G., Vahi, K., Berriman, G.B., Good, J., Laity, A., Jacob, J.C., Katz, D.S.: Pegasus: A framework for mapping complex scientific workflows onto distributed systems. Sci. Program. 13, 219–237 (2005)Google Scholar
  9. 9.
    Desel, J., Esparza, J.: Free Choice Petri Nets. CUP (1995)Google Scholar
  10. 10.
    Dressler. F.: Self-Organization in Sensor and Actor Networks. Wiley (2008)Google Scholar
  11. 11.
    Farrell, S., Cahill, V.: Delay- and Disruption-Tolerant Networking. Artech House Inc, Norwood, MA, USA (2006)Google Scholar
  12. 12.
    Ferscha, A.: Optimistic distributed execution of business process models. In: Proc. 31st Annual Hawaii Int. Conf. System Sciences-Volume 7, HICSS (1998)Google Scholar
  13. 13.
    Gehani, A., Lindqvist, U.: Bonsai: Balanced lineage authentication. In: IEEE Annual Computer Security Applications Conf. (ACSAC) (2007)Google Scholar
  14. 14.
    Girard, J.-Y.: Linear logic. Theor. Comput. Sci. 50, 1–102 (1987)MathSciNetCrossRefzbMATHGoogle Scholar
  15. 15.
    Girault, C., Valk, R.: Petri Nets for System Engineering: A Guide to Modeling, Verification, and Applications. Springer-Verlag (2001)Google Scholar
  16. 16.
    Jacobson, V., Smetters, D.K., Thornton, J.D., Plass, M.F., Briggs, N.H., Braynard, R.L.: Networking named content. In: Proc. 5th Int. Conf. Emerging Networking Experiments and Technologies, CoNEXT 2009, pp. 1–12 (2009)Google Scholar
  17. 17.
    Jensen, K.: Coloured Petri Nets: Basic Concepts, Analysis Methods and Practical Use, Vol. 1. Springer-Verlag (1995)Google Scholar
  18. 18.
    Kim, M., Stehr, M.O., Kim, J., Ha, S.: An application framework for loosely coupled networked cyber-physical systems. In: IEEE/IFIP Int. Conf. Embedded and Ubiquitous Computing, EUC 2010, pp. 144–153 (2010)Google Scholar
  19. 19.
    Kim, M., Stehr, M.-O., Talcott, C.: A distributed logic for networked cyber-physical systems. In: Arbab, F., Sirjani, M. (eds.) FSEN 2011. LNCS, vol. 7141, pp. 190–205. Springer, Heidelberg (2012)CrossRefGoogle Scholar
  20. 20.
    Knoke, M., Zimmermann, A.: Distributed simulation of colored stochastic Petri nets with timenet 4.0. In: Proc. 3rd Int. Conf. Quantitative Evaluation of Systems, pp. 117–118 (2006)Google Scholar
  21. 21.
    Koponen, T., Chawla, M., Chun, B.-G., Ermolinskiy, A., Kim, K.H., Shenker, S., Stoica, I.: A data-oriented (and beyond) network architecture. SIGCOMM Comput. Commun. Rev. 37, 181–192 (2007)CrossRefGoogle Scholar
  22. 22.
    Kummer, O., Stehr, M.O.: Petri’s axioms of concurrency- a selection of recent results. In: Proc. 18th Int. Conf. Application and Theory of Petri Nets, pp. 195–214. Springer-Verlag (1997)Google Scholar
  23. 23.
    Lamport, L.: Time, clocks, and the ordering of events in a distributed system. Commun. ACM 21, 558–565 (1978)CrossRefzbMATHGoogle Scholar
  24. 24.
    Loo, B.T., Condie, T., Garofalakis, M., Gay, D.E., Hellerstein, J.M., Maniatis, P., Ramakrishnan, R., Roscoe, T., Stoica, I.: Declarative networking: Language, execution and optimization. In: Proc. 2006 ACM SIGMOD Int. Conf. Management of Data, pp. 97–108 (2006)Google Scholar
  25. 25.
    Meseguer, J.: Conditional rewriting logic as a unified model of concurrency. Theo. Comput. Sci. 96, 73–155 (1992)MathSciNetCrossRefzbMATHGoogle Scholar
  26. 26.
    Montanari, U., Rossi, F.: Contextual nets. Acta Informatica, 32(6) (1995)Google Scholar
  27. 27.
    Murphy, A.L., Picco, G.P., Roman, G.-C.: Lime: A coordination model and middleware supporting mobility of hosts and agents. ACM Trans. Softw. Eng. Methodol. 15(3), 279–328 (2006)CrossRefGoogle Scholar
  28. 28.
    Murray, D.G., Schwarzkopf, M., Smowton, C., Smith, S., Madhavapeddy, A., Hand, S.: CIEL: A universal execution engine for distributed data-flow computing. In: Proc. 8th USENIX Conf. Networked Systems Design and Implementation, NSDI 2011 (2011)Google Scholar
  29. 29.
    Pereira, J., Rodrigues, L., Oliveira, R.: Semantically reliable multicast: Definition, implementation, and performance evaluation. IEEE Trans. Comput. 52(2), 150–165 (2003)CrossRefGoogle Scholar
  30. 30.
    Petri, C.A.: Nets, time and space. Theor. Comput. Sci. 153, 3–48 (1996)MathSciNetCrossRefzbMATHGoogle Scholar
  31. 31.
    Reisig, W.: Elements of Distributed Algorithms: Modeling and Analysis with Petri Nets. Springer-Verlag (1998)Google Scholar
  32. 32.
    Sgroi, M., Lavagno, L., Watanabe, Y., Sangiovanni-Vincentelli, A.: Synthesis of embedded software using free-choice Petri nets. In: Proc. ACM/IEEE Design Automation Conf., DAC 1999, pp. 805–810 (1999)Google Scholar
  33. 33.
    Stehr, M.O., Kim, M., McCarthy, T.: A distributed computing model for dataflow, controlflow, and workflow in fractionated cyber-physical systems (full version) (2014).
  34. 34.
    Stehr, M.-O., Kim, M., Talcott, C.: Toward distributed declarative control of networked cyber-physical systems. In: Yu, Z., Liscano, R., Chen, G., Zhang, D., Zhou, X. (eds.) UIC 2010. LNCS, vol. 6406, pp. 397–413. Springer, Heidelberg (2010)CrossRefGoogle Scholar
  35. 35.
    Stehr, M.-O., Meseguer, J., Ölveczky, P.C.: Rewriting Logic as a Unifying Framework for Petri Nets. In: Ehrig, H., Juhás, G., Padberg, J., Rozenberg, G. (eds.) APN 2001. LNCS, vol. 2128, pp. 250–303. Springer, Heidelberg (2001)CrossRefGoogle Scholar
  36. 36.
    Stehr, M.O., Talcott, C.: Planning and learning algorithms for routing in disruption-tolerant networks. In: IEEE Military Communications Conf. (2008)Google Scholar
  37. 37.
    Stehr, M.-O., Talcott, C., Rushby, J., Lincoln, P., Kim, M., Cheung, S., Poggio, A.: Fractionated software for networked cyber-physical systems: research directions and long-term vision. In: Agha, G., Danvy, O., Meseguer, J. (eds.) Formal Modeling: Actors, Open Systems, Biological Systems. LNCS, vol. 7000, pp. 110–143. Springer, Heidelberg (2011)CrossRefGoogle Scholar
  38. 38.
    Talcott, C., Dill, D.L.: Multiple representations of biological processes. Trans, Computational Systems Biology (2006)CrossRefGoogle Scholar
  39. 39.
    van der Aalst, W.M.P.: The application of Petri nets to workflow management. J. of Circuits, Systems, and Computers 8(1), 21–66 (1998)CrossRefGoogle Scholar
  40. 40.
    Vogler, W., Semenov, A., Yakovlev, A.: Unfolding and finite prefix for nets with read arcs. In: Sangiorgi, D., de Simone, R. (eds.) CONCUR 1998. LNCS, vol. 1466, pp. 501–516. Springer, Heidelberg (1998)CrossRefGoogle Scholar
  41. 41.
    Winskel, G.: Event structures. In: Advances in Petri Nets 1986, Part II on Petri nets: Applications and Relationships to Other Models of Concurrency, pp. 325–392. Springer (1987)Google Scholar

Copyright information

© Springer International Publishing Switzerland 2014

Authors and Affiliations

  1. 1.SRI InternationalMenlo ParkUSA

Personalised recommendations