Dynamic Resource Reallocation between Deployment Components

  • Einar Broch Johnsen
  • Olaf Owe
  • Rudolf Schlatte
  • Silvia Lizeth Tapia Tarifa
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6447)


Today’s software systems are becoming increasingly configurable and designed for deployment on a plethora of architectures, ranging from sequential machines via multicore and distributed architectures to the cloud. Examples of such systems are found in, e.g., software product lines, service-oriented computing, information systems, embedded systems, operating systems, and telephony. To model and analyze systems without a fixed architecture, the models need to naturally capture and range over relevant deployment scenarios. For this purpose, it is interesting to lift aspects of low-level deployment concerns to the abstraction level of the modeling language. In this paper, the object-oriented modeling language Creol is extended with a notion of dynamic deployment components with parametric processing resources, such that processor resources may be explicitly reallocated. The approach is compositional in the sense that functional models and reallocation strategies are both expressed in Creol, and functional models can be run alone or in combination with different reallocation strategies. The formal semantics of deployment components is given in rewriting logic, extending the semantics of Creol, and executes on Maude, which allows simulations and test suites to be applied to models which vary in their available resources as well as in their resource reallocation strategies.


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. 1.
    Ábrahám-Mumm, E., de Boer, F.S., de Roever, W.-P., Steffen, M.: Verification for Java’s reentrant multithreading concept. In: Nielsen, M., Engberg, U. (eds.) FOSSACS 2002. LNCS, vol. 2303, pp. 5–20. Springer, Heidelberg (2002)CrossRefGoogle Scholar
  2. 2.
    Agha, G.A.: ACTORS: A Model of Concurrent Computations in Distributed Systems. The MIT Press, Cambridge (1986)Google Scholar
  3. 3.
    Ahrendt, W., Dylla, M.: A verification system for distributed objects with asynchronous method calls. In: Breitman, K., Cavalcanti, A. (eds.) ICFEM 2009. LNCS, vol. 5885, pp. 387–406. Springer, Heidelberg (2009)CrossRefGoogle Scholar
  4. 4.
    Armstrong, J.: Programming Erlang: Software for a Concurrent World. Pragmatic Bookshelf (2007)Google Scholar
  5. 5.
    Balsamo, S., Marco, A.D., Inverardi, P., Simeoni, M.: Model-based performance prediction in software development: A survey. IEEE Trans. on Software Engineering 30(5), 295–310 (2004)CrossRefGoogle Scholar
  6. 6.
    Caromel, D., Henrio, L.: A Theory of Distributed Object. Springer, Heidelberg (2005)MATHGoogle Scholar
  7. 7.
    Chakrabarti, A., de Alfaro, L., Henzinger, T.A., Stoelinga, M.: Resource interfaces. In: Alur, R., Lee, I. (eds.) EMSOFT 2003. LNCS, vol. 2855, pp. 117–133. Springer, Heidelberg (2003)CrossRefGoogle Scholar
  8. 8.
    Chen, X., Hsieh, H., Balarin, F.: Verification approach of metropolis design framework for embedded systems. Intl. J. Parallel Programming 34(1), 3–27 (2006)CrossRefMATHGoogle Scholar
  9. 9.
    Clavel, M., Durán, F., Eker, S., Lincoln, P., Martí-Oliet, N., Meseguer, J., Quesada, J.F.: Maude: Specification and programming in rewriting logic. Theoretical Computer Science 285, 187–243 (2002)MathSciNetCrossRefMATHGoogle Scholar
  10. 10.
    de Boer, F.S., Clarke, D., Johnsen, E.B.: A complete guide to the future. In: De Nicola, R. (ed.) ESOP 2007. LNCS, vol. 4421, pp. 316–330. Springer, Heidelberg (2007)CrossRefGoogle Scholar
  11. 11.
    Epifani, I., Ghezzi, C., Mirandola, R., Tamburrelli, G.: Model evolution by run-time parameter adaptation. In: Proc. ICSE 2009, pp. 111–121. IEEE, Los Alamitos (2009)Google Scholar
  12. 12.
    Fersman, E., Krcál, P., Pettersson, P., Yi, W.: Task automata: Schedulability, decidability and undecidability. Inf. and Comp. 205(8), 1149–1172 (2007)MathSciNetCrossRefMATHGoogle Scholar
  13. 13.
    Haller, P., Odersky, M.: Scala actors: Unifying thread-based and event-based programming. Theoretical Computer Science 410(2-3), 202–220 (2009)MathSciNetCrossRefMATHGoogle Scholar
  14. 14.
    Happe, J., Koziolek, H., Reussner, R.: Parametric performance contracts for software components with concurrent behaviour. In: Proc. 3rd Intl. Workshop on Formal Aspects of Component Software (FACS 2006). ENTCS, vol. 182, pp. 91–106 (2007)Google Scholar
  15. 15.
    Hennessy, M., Riely, J.: Information flow vs. resource access in the asynchronous pi-calculus. ACM Trans. on Prog. Languages and Systems 24(5), 566–591 (2002)CrossRefMATHGoogle Scholar
  16. 16.
    Jaghoori, M.M., de Boer, F.S., Chothia, T., Sirjani, M.: Schedulability of asynchronous real-time concurrent objects. Journal of Logic and Algebraic Programming 78(5), 402–416 (2009)MathSciNetCrossRefMATHGoogle Scholar
  17. 17.
    Johnsen, E.B., Owe, O.: An asynchronous communication model for distributed concurrent objects. Software and Systems Modeling 6(1), 35–58 (2007)CrossRefGoogle Scholar
  18. 18.
    Johnsen, E.B., Owe, O., Bjørk, J., Kyas, M.: An object-oriented component model for heterogeneous nets. In: de Boer, F.S., Bonsangue, M.M., Graf, S., de Roever, W.-P. (eds.) FMCO 2007. LNCS, vol. 5382, pp. 257–279. Springer, Heidelberg (2008)CrossRefGoogle Scholar
  19. 19.
    Katelman, M., Meseguer, J., Hou, J.C.: Redesign of the lmst wireless sensor protocol through formal modeling and statistical model checking. In: Barthe, G., de Boer, F.S. (eds.) FMOODS 2008. LNCS, vol. 5051, pp. 150–169. Springer, Heidelberg (2008)CrossRefGoogle Scholar
  20. 20.
    Katoen, J.-P., Baier, C., Latella, D.: Metric semantics for true concurrent real time. Theoretical Computer Science 254(1-2), 501–542 (2001)MathSciNetCrossRefMATHGoogle Scholar
  21. 21.
    Meseguer, J.: Conditional rewriting logic as a unified model of concurrency. Theoretical Computer Science 96, 73–155 (1992)MathSciNetCrossRefMATHGoogle Scholar
  22. 22.
    Petriu, D.B., Woodside, C.M.: An intermediate metamodel with scenarios and resources for generating performance models from UML designs. Software and System Modeling 6(2), 163–184 (2007)CrossRefGoogle Scholar
  23. 23.
    Pohl, K., Böckle, G., Van Der Linden, F.: Software Product Line Engineering: Foundations, Principles, and Techniques. Springer, Heidelberg (2005)CrossRefMATHGoogle Scholar
  24. 24.
    Schäfer, J., Poetzsch-Heffter, A.: JCoBox: Generalizing active objects to concurrent components. In: D’Hondt, T. (ed.) ECOOP 2010 – Object-Oriented Programming. LNCS, vol. 6183, pp. 275–299. Springer, Heidelberg (2010)CrossRefGoogle Scholar
  25. 25.
    Verhoef, M., Larsen, P.G., Hooman, J.: Modeling and validating distributed embedded real-time systems with VDM++. In: Misra, J., Nipkow, T., Sekerinski, E. (eds.) FM 2006. LNCS, vol. 4085, pp. 147–162. Springer, Heidelberg (2006)CrossRefGoogle Scholar
  26. 26.
    Welc, A., Jagannathan, S., Hosking, A.: Safe futures for Java. In: Proc. OOPSLA 2005, pp. 439–453. ACM, New York (2005)Google Scholar
  27. 27.
    Yacoub, S.M.: Performance analysis of component-based applications. In: Chastek, G.J. (ed.) SPLC 2002. LNCS, vol. 2379, pp. 299–315. Springer, Heidelberg (2002)CrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2010

Authors and Affiliations

  • Einar Broch Johnsen
    • 1
  • Olaf Owe
    • 1
  • Rudolf Schlatte
    • 1
  • Silvia Lizeth Tapia Tarifa
    • 1
  1. 1.Department of InformaticsUniversity of OsloNorway

Personalised recommendations