Advertisement

On StocS: A Stochastic Extension of SCEL

  • Diego Latella
  • Michele Loreti
  • Mieke Massink
  • Valerio Senni
Part of the Lecture Notes in Computer Science book series (LNCS, volume 8950)

Abstract

Predicate-based communication allows components of a system to send messages and requests to ensembles of components that are determined at execution time through the evaluation of a predicate, in a multicast fashion. Predicate-based communication can greatly simplify the programming of autonomous and adaptive systems. We present a stochastically timed extension of the Software Component Ensemble Language (SCEL) that was introduced in previous work. Such an extension allows for quantitative modelling and analysis of system behaviour (e.g. performance) but rises a number of non-trivial design and formal semantics issues with different options as possible solutions at different levels of abstraction.

Keywords

Operational Semantic Knowledge State Knowledge Item Source Component Autonomic Computing 
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.

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. 1.
    Bortolussi, L., Hillston, J.: Fluid model checking. In: Koutny, M., Ulidowski, I. (eds.) CONCUR 2012. LNCS, vol. 7454, pp. 333–347. Springer, Heidelberg (2012)CrossRefGoogle Scholar
  2. 2.
    Bortolussi, L., Hillston, J., Latella, D., Massink, M.: Continuous approximation of collective system behaviour: A tutorial. Perform. Eval. 70(5), 317–349 (2013)CrossRefGoogle Scholar
  3. 3.
    Bruni, R., Corradini, A., Gadducci, F., Lluch Lafuente, A., Vandin, A.: A conceptual framework for adaptation. In: de Lara, J., Zisman, A. (eds.) Fundamental Approaches to Software Engineering. LNCS, vol. 7212, pp. 240–254. Springer, Heidelberg (2012)CrossRefGoogle Scholar
  4. 4.
    De Nicola, R., Katoen, J.-P., Latella, D., Loreti, M., Massink, M.: Model Checking Mobile Stochastic Logic. Theoretical Computer 382(1), 42–70 (2007), http://dx.doi.org/10.1016/j.tcs.2007.05.008, doi:10.1016/j.tcs.2007.05.008.MathSciNetCrossRefzbMATHGoogle Scholar
  5. 5.
    De Nicola, R., Ferrari, G., Loreti, M., Pugliese, R.: A language-based approach to autonomic computing. In: Beckert, B., Damiani, F., de Boer, F.S., Bonsangue, M.M. (eds.) FMCO 2011. LNCS, vol. 7542, pp. 25–48. Springer, Heidelberg (2012)CrossRefGoogle Scholar
  6. 6.
    De Nicola, R., Latella, D., Loreti, M., Massink, M.: Rate-based transition systems for stochastic process calculi. In: Albers, S., Marchetti-Spaccamela, A., Matias, Y., Nikoletseas, S., Thomas, W. (eds.) ICALP 2009, Part II. LNCS, vol. 5556, pp. 435–446. Springer, Heidelberg (2009)CrossRefGoogle Scholar
  7. 7.
    Nicola, R.D., Latella, D., Loreti, M., Massink, M.: A uniform definition of stochastic process calculi. ACM Comput. Surv. 46(1), 5:1–5:35 (2013)Google Scholar
  8. 8.
    Nicola, R.D., Loreti, M., Pugliese, R., Tiezzi, F.: A formal approach to autonomic systems programming: The SCEL language. TAAS 9(2), 7 (2014)CrossRefGoogle Scholar
  9. 9.
    Feng, C., Hillston, J.: PALOMA: A process algebra for located markovian agents. In: Norman, G., Sanders, W. (eds.) QEST 2014. LNCS, vol. 8657, pp. 265–280. Springer, Heidelberg (2014)Google Scholar
  10. 10.
    N. Koch, M. Hölzl, A. Klarl, P. Mayer, T. Bures, J. Combaz, A.L. Lafuente, R.D. Nicola, S. Sebastio, F. Tiezzi, A. Vandin, F. Gadducci, V. Monreale, U. Montanari, M. Loreti, C. Pinciroli, M. Puviani, F. Zambonelli, N. Šerbedžija, E. Vassev.: JD3.2: Software engineering for self-aware SCEs. ASCENS Deliverable JD3.2 (2013)Google Scholar
  11. 11.
    Latella, D., Loreti, M., Massink, M., Senni, V.: Stochastically timed predicate-based communication primitives for autonomic computing. In: Bertrand, N., Bortolussi, L. (eds.) Proceedings Twelfth International Workshop on Quantitative Aspects of Programming Languages and Systems, QAPL 2014, Grenoble, France, April 12-13. EPTCS, vol. 154, pp. 1–16 (2014)Google Scholar
  12. 12.
    Nicola, R.D., Hölzl, M., Loreti, M., Lafuente, A.L., Montanari, U., Vassev, E., Zambonelli, F.: JD2.1: Languages and knowledge models for self-awareness and self-expression. ASCENS Deliverable JD2.1 (2012)Google Scholar
  13. 13.
    Šerbedžija, N., Hoch, N., Pinciroli, C., Kit, M., Bures, T., Monreale, V., Montanari, U., Mayer, P., Velasco, J.: D7.3: Third report on wp7 - integration and simulation report for the ascens case studies, ASCENS Deliverable D7.3 (2013)Google Scholar
  14. 14.
    Šerbedžija, N., Massink, M., Pinciroli, C., Brambilla, M., Latella, D., Dorigo, M., Birattari, M., Mayer, P., Velasco, J.A., Hoch, N., Bensler, H.P., Abeywickrama, D., Keznikl, J., Gerostathopoulos, I., Bures, T., Nicola, R.D., Loreti, M.: D7.2: Second report on wp7 - integration and simulation report for the ascens case studies. ASCENS Deliverable D7.2 (2012)Google Scholar

Copyright information

© Springer International Publishing Switzerland 2015

Authors and Affiliations

  • Diego Latella
    • 1
  • Michele Loreti
    • 2
  • Mieke Massink
    • 1
  • Valerio Senni
    • 3
  1. 1.Istituto di Scienza e Tecnologie dell’Informazione ‘A. Faedo’, CNRItaly
  2. 2.Università di FirenzeItaly
  3. 3.IMT-LuccaItaly

Personalised recommendations