A Probabilistic Formal Analysis Approach to Cross Layer Optimization in Distributed Embedded Systems

  • Minyoung Kim
  • Mark-Oliver Stehr
  • Carolyn Talcott
  • Nikil Dutt
  • Nalini Venkatasubramanian
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4468)


We present a novel approach, based on probabilistic formal methods, to developing cross-layer resource optimization policies for resource limited distributed systems. One objective of this approach is to enable system designers to analyze designs in order to study design tradeoffs and predict the possible property violations as the system evolves dynamically over time. Specifically, an executable formal specification is developed for each layer under consideration (for example, application, middleware, operating system). The formal specification is then analyzed using statistical model checking and statistical quantitative analysis, to determine the impact of various resource management policies for achieving desired end-to-end QoS properties. We describe how existing statistical approaches have been adapted and improved to provide analyses of given cross-layered optimization policies with quantifiable confidence. The ideas are tested in a multi-mode multi-media case study. Experiments from both theoretical analysis and Monte-Carlo simulation followed by statistical analyses demonstrate the applicability of this approach to the design of resource-limited distributed systems.


Probabilistic Formal Methods Statistical Analysis  Cross-layer Optimization Resource Management 


  1. 1.
    Forge Project:
  2. 2.
    Mohapatra, S., Cornea, R., Oh, H., Lee, K., Kim, M., Dutt, N.D., Gupta, R., Nicolau, A., Shukla, S.K., Venkatasubramanian, N.: A cross-layer approach for power-performance optimization in distributed mobile systems. In: IPDPS ’05. International Parallel and Distributed Processing Symposium (2005)Google Scholar
  3. 3.
    Kim, M., Dutt, N., Venkatasubramanian, N.: Policy construction and validation for energy minimization in cross layered systems: A formal method approach. In: Real-Time and Embedded Technology and Applications Symposium (RTAS ’06) Work-in-Progress Session. pp. 25–28 (2006)Google Scholar
  4. 4.
    Clavel, M., Durán, F., Eker, S., Lincoln, P., Martí-Oliet, N., Meseguer, J., Talcott, C.: All about maude, a high-performance logical framework. LNCS, vol. 4350. Springer, Heidelberg (2007)zbMATHGoogle Scholar
  5. 5.
    Kim, D., Kim, M., Ha, S.: A Case Study of System Level Specification and Software Synthesis of Multimode Multimedia Terminal. In: Embedded Systems for Real-Time Multimedia (ESTImedia ’03), pp. 57–64 (2003)Google Scholar
  6. 6.
    Kim, M., Ha, S.: Hybrid Run-time Power Management Technique for Real-time Embedded System with Voltage Scalable Processor. ACM SIGPLAN Notices 36(8), 11–19 (2001)CrossRefGoogle Scholar
  7. 7.
    Kim, M., Oh, H., Dutt, N., Nicolau, A., Venkatasubramanian, N.: PBPAIR: an energy-efficient error-resilient encoding using probability based power aware intra refresh. SIGMOBILE Mob. Comput. Commun. Rev. 10(3), 58–69 (2006)CrossRefGoogle Scholar
  8. 8.
    Clavel, M., Durán, F., Eker, S., Lincoln, P., Martí-Oliet, N., Meseguer, J., Talcott, C.: The maude 2.0 system. In: Nieuwenhuis, R. (ed.) RTA 2003. LNCS, vol. 2706, Springer, Heidelberg (2003)CrossRefGoogle 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(2), 187–243 (2002)MathSciNetCrossRefzbMATHGoogle Scholar
  10. 10.
    Meseguer, J.: Conditional Rewriting Logic as a unified model of concurrency. Theoretical Computer Science 96(1), 73–155 (1992)MathSciNetCrossRefzbMATHGoogle Scholar
  11. 11.
  12. 12.
    Agha, G.A., Meseguer, J., Sen, K.: PMaude: Rewrite-based specification language for probabilistic object systems. Electr. Notes Theor. Comput. Sci. 153(2), 213–239 (2006)CrossRefGoogle Scholar
  13. 13.
    Wald, A.: Sequential tests of statistical hypotheses. Annals of Mathematical Statistics 16(2), 117–186 (1945)MathSciNetCrossRefzbMATHGoogle Scholar
  14. 14.
    Sen, K., Viswanathan, M., Agha, G.: Statistical model checking of black-box probabilistic systems. In: Alur, R., Peled, D.A. (eds.) CAV 2004. LNCS, vol. 3114, pp. 202–215. Springer, Heidelberg (2004)CrossRefGoogle Scholar
  15. 15.
    Younes, H.: Ymer: A statistical model checker. In: Etessami, K., Rajamani, S.K. (eds.) CAV 2005. LNCS, vol. 3576, pp. 429–433. Springer, Heidelberg (2005)CrossRefGoogle Scholar
  16. 16.
    Younes, H., Kwiatkowska, M., Norman, G., Parker, D.: Numerical vs. statistical probabilistic model checking. International Journal on Software Tools for Technology Transfer (STTT) 8(3), 216–228 (2006)CrossRefzbMATHGoogle Scholar
  17. 17.
    Jarque, C., Bera, A.: A test for normality of observations and regression residuals. Internat. Statist. Rev. 55(2), 163–172 (1987)MathSciNetCrossRefzbMATHGoogle Scholar
  18. 18.
    Hogg, R., Craig, A.: Introduction to Mathematical Statistics. 5th edn. (1995)Google Scholar
  19. 19.
    Aziz, A., Sanwal, K., Singhal, V., Brayton, R.: Model-checking continuous-time Markov chains. ACM Trans. Comput. Logic 1(1), 162–170 (2000)MathSciNetCrossRefGoogle Scholar
  20. 20.
    Image Process Lab. Univ. British Columbia: TMN 10 (H.263+), ver. 3.2.0 (1998)Google Scholar
  21. 21.
  22. 22.
    Kim, M., Stehr, M.O., Talcott, C., Dutt, N., Venkatasubramanian, N.: Modeling and Exploiting Cross-Layer Optimization in Distributed Embedded Systems. Technical Report SRI-CSL-07-02, SRI International (February 2007)Google Scholar
  23. 23.
    Kumar, N., Sen, K., Meseguer, J., Agha, G.: A rewriting based model for probabilistic distributed object systems. In: Najm, E., Nestmann, U., Stevens, P. (eds.) FMOODS 2003. LNCS, vol. 2884, pp. 32–46. Springer, Heidelberg (2003)CrossRefGoogle Scholar
  24. 24.
    Hinton, A., Kwiatkowska, M., Norman, G., Parker, D.: PRISM: A tool for automatic verification of probabilistic systems. In: Hermanns, H., Palsberg, J. (eds.) TACAS 2006 and ETAPS 2006. LNCS, vol. 3920, pp. 441–444. Springer, Heidelberg (2006)CrossRefGoogle Scholar

Copyright information

© IFIP International Federation for Information Processing 2007

Authors and Affiliations

  • Minyoung Kim
    • 1
  • Mark-Oliver Stehr
    • 2
  • Carolyn Talcott
    • 2
  • Nikil Dutt
    • 1
  • Nalini Venkatasubramanian
    • 1
  1. 1.University of California, IrvineUSA
  2. 2.SRI InternationalUSA

Personalised recommendations