Advertisement

A Framework for Flexible and Dependable Service-Oriented Embedded Systems

  • Shane Brennan
  • Serena Fritsch
  • Yu Liu
  • Ashley Sterritt
  • Jorge Fox
  • Éamonn Linehan
  • Cormac Driver
  • René Meier
  • Vinny Cahill
  • William Harrison
  • Siobhán Clarke
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6420)

Abstract

The continued development and deployment of distributed, real-time embedded systems technologies in recent years has resulted in a multitude of ecosystems in which service-oriented embedded systems can now be realised. Such ecosystems are often exposed to dynamic changes in user requirements, environmental conditions and network topologies that require service-oriented embedded systems to evolve at runtime. This paper presents a framework for service-oriented embedded systems that can dynamically adapt to changing conditions at runtime. Supported by model-driven development techniques, the framework facilitates lightweight dynamic service composition in embedded systems while predicting the temporal nature of unforeseen service assemblies and coping with adverse feature interactions following dynamic service composition. This minimises the complexity of evolving software where services are deployed dynamically and ultimately, enables flexible and dependable service-oriented embedded systems.

Keywords

Service-Oriented Architectures Dynamic Adaptation Predictable Reconfiguration Predictable Feature Interaction Embedded Systems 

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. 1.
    aiT. AbsInt: aiT tool homepage (2010), http://www.absint.com/ait/
  2. 2.
    Allen, R., Douence, R., Garlan, D.: Specifying and analyzing dynamic software architectures. In: Astesiano, E. (ed.) ETAPS 1998 and FASE 1998. LNCS, vol. 1382, p. 21. Springer, Heidelberg (1998)CrossRefGoogle Scholar
  3. 3.
    Assaf, A., Noyé, J.: Dynamic AspectJ. In: Proceedings of the 2008 symposium on Dynamic Languages (DLS 2008), pp. 1–12 (2008)Google Scholar
  4. 4.
    Bisbal, J., Cheng, B.H.C.: Resource-based approach to feature interaction in adaptive software. In. In: Proceedings of the 1st ACM SIGSOFT Workshop on Self-managed Systems, WOSS 2004, pp. 23–27. ACM, New York (2004)CrossRefGoogle Scholar
  5. 5.
    Tidorum, B.-T.: Bound-T tool homepage (2009), http://www.tidorum.fi/bound-t
  6. 6.
    Brennan, S., Cahill, V., Clarke, S.: Applying non-constant volatility analysis methods to software timeliness. In: Proceedings of the 12th Euromicro Conference on Real-Time Systems, Work-in-progress Session (2009)Google Scholar
  7. 7.
    Brinkschulte, U., Schneider, E., Picioroaga, F.: Dynamic real-time reconfiguration in distributed systems: Timing issues and solutions. In: ISORC 2005: Proceedings of the Eighth IEEE International Symposium on Object-Oriented Real-Time Distributed Computing, ISORC 2005 (2005)Google Scholar
  8. 8.
    Calder, M., Miller, A.: Using SPIN for feature interaction analysis - A case study. In: Dwyer, M.B. (ed.) SPIN 2001. LNCS, vol. 2057, pp. 143–162. Springer, Heidelberg (2001)CrossRefGoogle Scholar
  9. 9.
    Carton, A., Driver, C., Jackson, A., Clarke, S.: Model-driven Theme/UML. Transactions on Aspect-Oriented Software Development, 428–432 (2009)Google Scholar
  10. 10.
    Cottenier, T.: The motorola weavr: Model weaving in a large industrial context. In: Proceedings of the International Conference on Aspect Oriented Software Development, Industry Track (2006)Google Scholar
  11. 11.
    Didonet Del Fabro, M., Bézivin, J., Jouault, F., Breton, E., Gueltas, G.: AMW: a generic model weaver. Journées sur l’Ingénierie Dirigée par les Modèles (IDM 2005), 105–114 (2005), 2-7261-1284-6Google Scholar
  12. 12.
    Driver, C., Reilly, S., Linehan, E., Cahill, V., Clarke, S.: Managing embedded systems complexity with aspect-oriented model-driven engineering. ACM Transactions on Embedded Computing Systems (TECS) (to appear, 2010)Google Scholar
  13. 13.
    Edgar, S.: Estimation of worst-case execution time using statistical analysis, PhD thesis. PhD thesis, Department of Computer Science, University of York (2002)Google Scholar
  14. 14.
    Felty, A.P., Namjoshi, K.S.: Feature specification and automated conflict detection. ACM Transactions on Software Engineering and Methodology 12(1), 3–27 (2003)CrossRefGoogle Scholar
  15. 15.
    France, R., Fleurey, F., Reddy, R., Baudry, B., Ghosh, S.: Providing support for model composition in metamodels. In: Proceedings of the 11th IEEE International Enterprise Distributed Object Computing Conference, EDOC 2007, Washington, DC, USA, p. 253. IEEE Computer Society, Los Alamitos (2007)CrossRefGoogle Scholar
  16. 16.
    Galpin, D., Driver, C., Clarke, S.: Modelling hardware verification concerns specified in the e language: An experience report. In: Proceedings of the International Conference on Aspect-Oriented Software Development (AOSD), Industry Track, pp. 207–212 (2009)Google Scholar
  17. 17.
    Groher, I., Voelter, M.: XWeave: models and aspects in concert. In: Proceedings of the 10th International Workshop on Aspect-Oriented Modeling, AOM 2007, pp. 35–40. ACM Press, New York (2007)CrossRefGoogle Scholar
  18. 18.
    Hansen, J., Hissam, S., Moreno, G.: Statistical-Based WCET Estimation and Validation. In: 9th International Workshop on Worst-Case Execution Time Analysis (WCET 2009), pp. 123–133 (2009)Google Scholar
  19. 19.
    Hissam, S., Ivers, J.: Prediction-Enabled Component Technology (PECT) Infrastructure: A Rough Sketch. Technical Report CMU/SEI-2002-TN-033, Software Engineering Institute, Carnegie-Mellon University (2002)Google Scholar
  20. 20.
    Hovsepyan, A., Baelen, S.V., Vanhooff, B., Joosen, W., Berbers, Y.: Key Research Challenges for Successfully Applying MDD Within Real-Time Embedded Software Development. In: Vassiliadis, S., Wong, S., Hämäläinen, T.D. (eds.) SAMOS 2006. LNCS, vol. 4017, pp. 49–58. Springer, Heidelberg (2006)CrossRefGoogle Scholar
  21. 21.
    Jayaraman, P.K., Whittle, J., Elkhodary, A.M., Gomaa, H.: Model composition in product lines and feature interaction detection using critical pair analysis. In: Engels, G., Opdyke, B., Schmidt, D.C., Weil, F. (eds.) MODELS 2007. LNCS, vol. 4735, pp. 151–165. Springer, Heidelberg (2007)CrossRefGoogle Scholar
  22. 22.
    Kim, H.-C., Choi, H.-J., Ko, I.-Y.: An Architectural Model to Support Adaptive Software Systems for Sensor Networks. In: Proceedings of the 11th Asia-Pacific Software Engineering Conference (APSEC 2004), pp. 670–677 (2004)Google Scholar
  23. 23.
    Klein, J., Fleurey, F., Jézéquel, J.M.: Weaving multiple aspects in sequence diagrams. In: Rashid, A., Aksit, M. (eds.) Transactions on AOSD III. LNCS, vol. 4620, pp. 167–199. Springer, Heidelberg (2007)CrossRefGoogle Scholar
  24. 24.
    Klus, H., Niebuhr, D., Rausch, A.: A component model for dynamic adaptive systems. In: International Workshop on Engineering of Software Services for Pervasive Environments, ESSPE 2007, pp. 21–28. ACM, New York (2007)Google Scholar
  25. 25.
    Krüger, I., Mathew, R.: Systematic development and exploration of service-oriented software architectures. In: Proceedings of Fourth Working IEEE/IFIP Conference on Software Architecture, WICSA 2004. (June 12-15), pp. 177–187 (2004)Google Scholar
  26. 26.
    Kumar, T., Cledat, R., Sreeram, J., Pande, S.: Statistically Analyzing Execution Variance for Soft Real-Time Applications. In: 6th Joint Meeting of the European Software Engineering Conference and the ACM SIGSOFT Symposium (ESEC/FSE 2007), pp. 529–532 (2007)Google Scholar
  27. 27.
    Lampert, A., Koenig, S.: Configuration management in a heterogeneous target environment. In: Proceedings of Third Israel Conference on Computer Systems and Software Engineering, June 6-7, pp. 148–158 (1988)Google Scholar
  28. 28.
    Linehan, E., Clarke, S.: Managing hardware verification complexity with aspect-oriented model-driven engineering. In: Proceedings of the 1st Workshop on Model Based Engineering for Embedded Systems Design (M-BED), pp. 54–60 (2010)Google Scholar
  29. 29.
    Liu, Y., Meier, R.: Feature Interaction in Pervasive Computing Systems. Electronic Communications of the EASST Journal 11, 1–7 (2008)MATHGoogle Scholar
  30. 30.
    Liu, Y., Meier, R.: Resource-aware contracts for addressing feature interaction in dynamic adaptive systems. In: Proceedings of the 2009 Fifth International Conference on Autonomic and Autonomous Systems, ICAS 2009, Washington, DC, USA, pp. 346–350. IEEE Computer Society, Los Alamitos (2009)CrossRefGoogle Scholar
  31. 31.
    Mitchell, S., Naguib, H., Coulouris, G., Kindberg, T.: Dynamically reconfiguring multimedia components: a model-based approach. In: Proceedings of the 8th ACM SIGOPS European workshop on Support for composing distributed applications, EW 1998, pp. 40–47. ACM, New York (1998)CrossRefGoogle Scholar
  32. 32.
    I.Object Management Group. Marte specification beta 2 2008), http://www.omgmarte.org/Documents/Specifications/08-06-09.pdf
  33. 33.
    Rasche, A., Polze, A.: Dynamic reconfiguration of component-based real-time software. In: Proceedings of the 10th IEEE International Workshop on Object-Oriented Real-Time Dependable Systems, WORDS 2005 (2005)Google Scholar
  34. 34.
    Reddy, Y.R., Ghosh, S., France, R.B., Straw, G., Bieman, J.M., McEachen, N., Song, E., Georg, G.: Directives for Composing Aspect-Oriented Design Class Models. pp. 75–105 (2006)Google Scholar
  35. 35.
    Reiff-Marganiec, S.: Runtime Resolution of Feature Interactions in Evolving Telecommunications Systems. PhD thesis, University of Glasgow (2002)Google Scholar
  36. 36.
    Schneider, E., Picioroagǎ, F., Brinkschulte, U.: Dynamic reconfiguration through osa+, a real-time middleware. In: Proceedings of the 1st International Doctoral Symposium on Middleware, DSM 2004, pp. 319–323. ACM, New York (2004)CrossRefGoogle Scholar
  37. 37.
    Sharma, P.K., Loyall, J.P., Heineman, G.T., Schantz, R.E., Shapiro, R., Duzan, G.: Component-Based Dynamic QoS Adaptations in Distributed Real-Time and Embedded Systems. In: International Symposium on Distributed Objects and Applications, DOA (2004)Google Scholar
  38. 38.
    Souyris, J., Pavec, E.L., Himbert, G., Jégu, V., Borios, G.: Computing the worst case execution time of an avionics program by abstract interpretation. In: Proceedings of the 5th Intl Workshop on Worst-Case Execution Time Analysis (WCET 2005), pp. 21–24 (2005)Google Scholar
  39. 39.
    Stewart, D., Volpe, R., Khosla, P.: Design of dynamically reconfigurable real-time software using port-based objects. IEEE Trans. Softw. Eng. 23(12), 759–776 (1997)CrossRefGoogle Scholar
  40. 40.
    Thiel, S., Hein, A.: Modeling and using product line variability in automotive systems. IEEE Software 19, 66–72 (2002)CrossRefGoogle Scholar
  41. 41.
    Wehrmeister, M.A., Freitas, E.P., Pereira, C.E., Wagner, F.R.: An Aspect-Oriented Approach for Dealing with Non-Functional Requirements in a Model-Driven Development of Distributed Embedded Real-Time Systems. In: Proceedings of the 10th IEEE International Symposium on Object and Component-Oriented Real-Time Distributed Computing SORC 007, Washington, DC, USA, pp. 428–432. IEEE Computer Society, Los Alamitos (2007)CrossRefGoogle Scholar
  42. 42.
    Wermelinger, M.: A hierarchic architecture model for dynamic reconfiguration. In: Proceedings of the Second International Workshop on Software Engineering for Parallel and Distributed Systems, pp. 243–254. IEEE Computer Society, Los Alamitos (1997)CrossRefGoogle Scholar
  43. 43.
    Zhao, Z., Li, W.: Influence control for dynamic reconfiguration. In: Australian Software Engineering Conference, pp. 59–70 (2007)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2010

Authors and Affiliations

  • Shane Brennan
    • 1
  • Serena Fritsch
    • 1
  • Yu Liu
    • 1
  • Ashley Sterritt
    • 1
  • Jorge Fox
    • 1
  • Éamonn Linehan
    • 1
  • Cormac Driver
    • 1
  • René Meier
    • 1
  • Vinny Cahill
    • 1
  • William Harrison
    • 1
  • Siobhán Clarke
    • 1
  1. 1.Lero - The Irish Software Engineering Research Centre, Distributed Systems Group, School of Computer Science and StatisticsTrinity CollegeDublinIreland

Personalised recommendations