Energy Consumption Analysis and Design of Energy-Aware WSN Agents in fUML

  • Luca Berardinelli
  • Antinisca Di Marco
  • Stefano PaceEmail author
  • Luigi Pomante
  • Walter Tiberti
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9153)


Wireless Sensor Networks (WSN) are nowadays applied to a wide set of domains (e.g., security, health). WSN are networks of spatially distributed, radio-communicating, battery-powered, autonomous sensor nodes. WSN are characterized by scarcity of resources, hence an application running on them should carefully manage its resources. The most critical resource in WSN is the nodes’ battery.

In this paper, we propose model-based engineering facilities to analyze the energy consumption and to develop energy-aware applications for WSN that are based on Agilla Middleware. For this aim i) we extend the Agilla Instruction Set with the new battery instruction able to retrieve the battery Voltage of a WSN node at run-time; ii) we measure the energy that the execution of each Agilla instruction consumes on a target platform; and iii) we extend the Agilla Modeling Framework with a new analysis that, leveraging the conducted energy consumption measurements, predicts the energy required by the Agilla agents running on the WSN. Such analysis, implemented in fUML, is based on simulation and it guides the design of WSN applications that guarantee low energy consumption. The approach is showed on the Reader agent used in the WildFire Tracker Application.


fUML Model-driven analysis Tool support WSN 


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  1. 1.
    Berardinelli, L., Di Marco, A., Pace, S., Marchesani, S., Pomante, L.: Modeling and timing simulation of agilla agents for WSN applications in executable UML. In: Balsamo, M.S., Knottenbelt, W.J., Marin, A. (eds.) EPEW 2013. LNCS, vol. 8168, pp. 300–311. Springer, Heidelberg (2013) CrossRefGoogle Scholar
  2. 2.
    Berardinelli, L., Di Marco, A., Pace, S.: fUML-driven design and performance analysis of software agents for wireless sensor network. In: Avgeriou, P., Zdun, U. (eds.) ECSA 2014. LNCS, vol. 8627, pp. 324–339. Springer, Heidelberg (2014) Google Scholar
  3. 3.
    Fok, C.L., Roman, G.C., Lu, C.: Agilla: A mobile agent middleware for self-adaptive wireless sensor networks. ACM Trans. Auton. Adap. 4(3), 16 (2009)Google Scholar
  4. 4.
    A Comparison of Primary Battery Performance using a Solartron 7150plus Multimeter.
  5. 5.
    OMG. Semantics of a foundational subset for executable UML models (2011)Google Scholar
  6. 6.
    OMG. UML, Superstructure, Version 2.4.1 (2011)Google Scholar
  7. 7.
    Berardinelli, L., Langer, P., Mayerhofer, T.: Combining fUML and profiles for non-functional analysis based on model execution traces. In: QoSA (2013)Google Scholar
  8. 8.
    Berardinelli, L., Cortellessa, V.: fUML-driven performance analysis through the moses model library. In: ACES-MB, MoDELS, pp. 34–43 (2014)Google Scholar
  9. 9.
    Tatibouet, J., Cuccuru, A., Gérard, S., Terrier, F.: Principles for the realization of an open simulation framework based on fuml (wip). In: Proc. of the Symposium on Theory of Modeling & Simulation-DEVS Integrative M&S Symposium, p. 4. Society for Computer Simulation International (2013)Google Scholar
  10. 10.
    Brosig, F., Meier, P., Becker, S., Koziolek, A., Koziolek, H., Kounev, S.: Quantitative evaluation of model-driven performance analysis and simulation of component-based architectures. IEEE Trans. Software Eng. 41(2), 157–175 (2015)CrossRefGoogle Scholar
  11. 11.
    Fleck, M., Berardinelli, L., Langer, P., Mayerhofer, T., Cortellessa, V.: Resource contention analysis of service-based systems through fUML-driven model execution. In: Proc. of NiM-ALP, p. 6 (2013)Google Scholar
  12. 12.
    Mayerhofer, T., Langer, P., Kappel, G.: A runtime model for fUML. In: Proc. of the Int’l Workshop on Models@run.time (MRT 2012) at MODELS (2012)Google Scholar
  13. 13.
    Taherkordi, A., Eliassen, F., Johnsen, E.B.: Behavioural design of sensor network applications using activity-driven states. In: Int’l Workshop on Soft. Eng. Sensor Network App. (SESENA), pp. 13–18 (2013)Google Scholar
  14. 14.
    Romero, A.G., Ferreira, M.G.V.: An approach to model-driven architecture applied to space real-time software. In: Proc. of the Int’l Conf. on Space Op. (2012)Google Scholar
  15. 15.
    Feiler, P.H., Gluch, D.P.: Model-based engineering with AADL: An introduction to the sae architecture analysis & design language. Addison-Wesley (2012)Google Scholar
  16. 16.
    Benyahia, A., Cuccuru, A., Taha, S., Terrier, F., Boulanger, F., Gérard, S.: Extending the standard execution model of UML for real-time systems. In: Hinchey, M., Kleinjohann, B., Kleinjohann, L., Lindsay, P.A., Rammig, F.J., Timmis, J., Wolf, M. (eds.) DIPES 2010. IFIP AICT, vol. 329, pp. 43–54. Springer, Heidelberg (2010) CrossRefGoogle Scholar
  17. 17.
    Abdelhalim, I., Schneider, S., Treharne, H.: An integrated framework for checking the behaviour of fUML models using CSP. Int’l Journal on Software Tools for Technology Transfer, 1–22 (2012)Google Scholar
  18. 18.
    Doddapaneni, K., Ever, E., Gemikonakli, O., Malavolta, I., Mostarda, L., Muccini, H.: A model-driven engineering framework for architecting and analysing wireless sensor networks. In: Int’l Workshop on Soft. Eng. Sensor Network App. (SESENA), pp. 1–7 (2012)Google Scholar
  19. 19.
    Anastasi, G., Conti, M., Di Francesco, M., Passarella, A.: Energy conservation in wireless sensor networks: A survey. Ad Hoc Networks 7(3), 537–568 (2009)CrossRefGoogle Scholar
  20. 20.
    Ye, W., Heidemann, J., Estrin, D.: An energy-efficient mac protocol for wireless sensor networks. In: Proceedings of the Twenty-First Annual Joint Conference of the IEEE Computer and Communications Societies, INFOCOM 2002, vol. 3, pp. 1567–1576. IEEE (2002)Google Scholar
  21. 21.
    Duarte-Melo, E.J., Liu, M.: Analysis of energy consumption and lifetime of heterogeneous wireless sensor networks. In: Global Telecommunications Conference, GLOBECOM 2002, vol. 1, pp. 21–25. IEEE (2002)Google Scholar
  22. 22.
    France, R.B., Rumpe, B.: Model-driven development of complex software: a research roadmap. In: Future of Software Engineering, pp. 37–54 (2007)Google Scholar
  23. 23.
    Malavolta, I., Lago, P., Muccini, H., Pelliccione, P., Tang, A.: What industry needs from architectural languages: A survey. IEEE Trans. Softw. Eng. 39(6) (2013)Google Scholar

Copyright information

© Springer International Publishing Switzerland 2015

Authors and Affiliations

  • Luca Berardinelli
    • 1
    • 3
  • Antinisca Di Marco
    • 1
    • 2
  • Stefano Pace
    • 1
    • 2
    Email author
  • Luigi Pomante
    • 1
    • 2
  • Walter Tiberti
    • 1
    • 2
  1. 1.Dipartimento DISIMUniversity of L’AquilaL’AquilaItaly
  2. 2.Center of Excellence DEWSUniversity of L’AquilaL’AquilaItaly
  3. 3.Business Informatics GroupVienna University of TechnologyWienAustria

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