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An evaluation framework for energy aware buildings using statistical model checking

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Abstract

Cyber-physical systems are to be found in numerous applications throughout society. The principal barrier to develop trustworthy cyber-physical systems is the lack of expressive modelling and specification formalisms supported by efficient tools and methodologies. To overcome this barrier, we extend in this paper the modelling formalism of the tool UPPAAL-SMC to stochastic hybrid automata, thus providing the expressive power required for modelling complex cyber-physical systems. The application of Statistical Model Checking provides a highly scalable technique for analyzing performance properties of this formalisms.

A particular kind of cyber-physical systems are Smart Grids which together with Intelligent, Energy Aware Buildings will play a major role in achieving an energy efficient society of the future. In this paper we present a framework in UPPAAL-SMC for energy aware buildings allowing to evaluate the performance of proposed control strategies in terms of their induced comfort and energy profiles under varying environmental settings (e.g. weather, user behavior etc.). To demonstrate the intended use and usefulness of our framework, we present an application to the Hybrid Systems Verification Benchmark.

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References

  1. Lee E A. Cyber physical systems: Design challenges. In: ISORC2008, Washington DC: IEEE Computer Society, 2008. 363–369

    Google Scholar 

  2. Deshpande A, Godbole D N, Göllü A, et al. Design and evaluation tools for automated highway systems. In: Alur R, Henzinger T A, Sontag E D, eds. Hybrid Systems 1995, Lecture Notes in Computer Science, Vol. 1066. Berlin/Heidelberg: Springer, 1995. 138–148

    Chapter  Google Scholar 

  3. Tomlin C, Pappas G J, Lygeros J, et al. Hybrid control models of next generarion air traffic management. In: Antsaklis P J, Kohn W, Nerode A, et al., eds. Lecture Notes in Computer Science, Vol. 1273. Berlin/Heidelberg: Springer, 1997. 378–404

    Google Scholar 

  4. Jiang Z, Pajic M, Moarref S, et al. Modeling and verification of a dual chamber implantable pacemaker. In: Flanagan C, König B, eds. Lecture Notes in Computer Science, Vol. 7214. Berlin/Heidelberg: Springer, 2012. 188–203

    Google Scholar 

  5. David A, Larsen K G, Legay A, et al. Statistical model checking for networks of priced timed automata. In: FORMATS 2011. Berlin/Heidelberg: Springer, 2011. 80–96

    Google Scholar 

  6. David A, Larsen K G, Legay A, et al. Time for statistical model checking of real-time systems. In: Proceedings of the 23rd International Conference on Computer Aided Verification. Berlin/Heidelberg: Springer-Verlag, 2011. 349–355

    Chapter  Google Scholar 

  7. Alur R, Dill D L. A theory of timed automata. Theor Comput Sci, 1994, 126: 183–235

    Article  MathSciNet  MATH  Google Scholar 

  8. Alur R, Courcoubetis C, Halbwachs N, et al. The algorithmic analysis of hybrid systems. Theor Comput Sci, 1995, 138: 3–34

    Article  MathSciNet  MATH  Google Scholar 

  9. Legay A, Delahaye B, Bensalem S. Statistical model checking: An overview. In: Lecture Notes in Computer Science, Vol. 6418. Berlin/Heidelberg: Springer, 2010. 122–135

    Google Scholar 

  10. Younes H L S, Simmons R G. Statistical probabilistic model checking with a focus on time-bounded properties. Inf Comput, 2006, 204: 1368–1409

    Article  MathSciNet  MATH  Google Scholar 

  11. Sen K, Viswanathan M, Agha G. Statistical model checking of black-box probabilistic systems. In: Lecture Notes in Computer Science, Vol. 3114. Berlin/Heidelberg: Springer, 2004. 202–215

    Google Scholar 

  12. Katoen J P, Zapreev I S, Hahn E M, et al. The ins and outs of the probabilistic model checker MRMC. J Perform Eval, 2011, 68: 90–104

    Article  Google Scholar 

  13. Basu A, Bensalem S, Bozga M, et al. Statistical abstraction and model-checking of large heterogeneous systems. In: Hatcliff J, Zucca E, eds. Formal Techniques for Distributed Systems, Lecture Notes in Computer Science, Vol. 6117. Berlin/Heidelberg: Springer, 2010. 32–46

    Chapter  Google Scholar 

  14. Bulychev P E, David A, Larsen K G, et al. Checking and distributing statistical model checking. In: NASA Formal Methods 2012, Lecture Notes in Computer Science, Vol. 7226. Berlin/Heidelberg: Springer, 2012. 449–463

    Chapter  Google Scholar 

  15. Brunner H, de Nigris M, Gallo A D, et al. Mapping & gap analysis of current european smart grids projects. Technical Report, Smart Grids ERA-Net, 2012

  16. State Grid Corporation of China. Sgcc white paper on green development (the first among Chinese corporations). http://www.sgcc.com.cn/ywlm/socialresponsiility/whitepaper.

  17. The White House Office of the Press Secretary. Us white house press release on smart grids, 2009. http://www.whitehouse.gov/the-press-office/president-obama-announces-34-billion-investment-spur-transition-smart-energy-grid

  18. Fehnker A, Ivancic F. Benchmarks for hybrid systems verification. In: Alur R, Pappas G J, eds. Lecture Notes in Computer Science, Vol. 2993. Berlin/Heidelberg: Springer, 2004. 326–341

    Google Scholar 

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Correspondence to DeHui Du or Kim G. Larsen.

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David, A., Du, D., Larsen, K.G. et al. An evaluation framework for energy aware buildings using statistical model checking. Sci. China Inf. Sci. 55, 2694–2707 (2012). https://doi.org/10.1007/s11432-012-4742-0

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  • DOI: https://doi.org/10.1007/s11432-012-4742-0

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