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Autonomic Road Transport Support Systems pp 181–195Cite as

Birkhäuser

Performance Maintenance of ARTS Systems

Finding and Managing Performance Deterioration by Undesired System Adaptation

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Part of the book series: Autonomic Systems ((ASYS))

Abstract

Autonomic Road Transportation Support (ARTS) systems will operate with adaptive system behavior to make them self-managing. In this chapter, we discuss methods for analyzing the performance of these kinds of systems. The performance of these systems not only depends on the state of the environment but also on the adaptation the system has made so far. Analyzing the performance can hardly be done analytically; we have to rely on empirical studies. A structured way for implementing such analysis of adaptive systems, like ARTS, is presented. Furthermore, we discuss different approaches and provide examples how such problems could be encountered during the design of ARTS systems.

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Notes

  1. 1.

    A traffic simulation for 1 h of real traffic can take several minutes in computational time.

  2. 2.

    The probability of a scenario can be computed by the probability of the modifier and the scenario from which it was derived.

  3. 3.

    It could be argued to subsume self-regulation, as an aspect of self-healing, according to the characterization used by Kephart and Chess [12], mentioned above.

References

  1. Abdulla, P.A., Delzanno, G., Rezine, A.: Parameterized verification of infinite-state processes with global conditions. In: Damm, W., Hermanns, H. (eds.) Computer Aided Verification. Lecture Notes in Computer Science, vol. 4590, pp. 145–157. Springer, Berlin/Heidelberg (2007)

    Chapter  Google Scholar 

  2. Alves, D., Ast, J.V., Cong, Z., Schutter, B.D., Babuska, R.: Ant colony optimization for traffic dispersion routing. In: Proceedings of the 13th International IEEE Conference on Intelligent Transportation Systems (ITSC 2010), pp. 683–688. IEEE, Funchal (2010)

    Google Scholar 

  3. Bedi, P., Mediratta, N., Dhand, S., Sharma, R., Singhal, A.: Avoiding traffic jam using ant colony optimization - a novel approach. In: International Conference on Computational Intelligence and Multimedia Applications, 2007, vol. 1, pp. 61–67 (2007)

    Google Scholar 

  4. Calinescu, R., Kikuchi, S., Kwiatkowska, M.: Formal Methods for the Development and Verification of Autonomic IT Systems. IGI Global, Hershey (2011)

    Google Scholar 

  5. Dallmeyer, J., Schumann, R., Lattner, A.D., Timm, I.J.: Don’t go with the ant flow: ant-inspired traffic routing in urban environments. In: Vasirani, M., Klügl, F., Camponogara, E., Hattori, H. (eds.) 7th International Workshop on Agents in Traffic and Transportation (ATT 2012) Held at AAMAS 2012, pp. 59–68 (2012). Pre-proceedings

    Google Scholar 

  6. Falilat, J., Chrpa, L., McCluskey, T.L., Shah, S.: Towards application of automated planning in urban traffic control. In: Proceedings of the 16th International IEEE Annual Conference on Intelligent Transportation Systems (ITSC 2013), pp. 985–990. IEEE, The Hague (2013)

    Google Scholar 

  7. Flötteröd, G., Bierlaire, M., Nagel, K.: Bayesian demand calibration for dynamic traffic simulations. Transp. Sci. 45(4), 541–561 (2011)

    Article  Google Scholar 

  8. Ge, Q., Menendez, M.: Final report of calibration study for vissim (csv). Project report, Institute for Transport Planning and Systems (IVT) ETH Zürich (2012)

    Google Scholar 

  9. Güdemann, M., Ortmeier, F., Reif, W.: Formal modeling and verification of systems with self-x properties. In: Yang, L., Jin, H., Ma, J., Ungerer, T. (eds.) Autonomic and Trusted Computing. Lecture Notes in Computer Science, vol. 4158, pp. 38–47. Springer, Berlin/Heidelberg (2006)

    Chapter  Google Scholar 

  10. Hudson, J., Denzinger, J., Kasinger, H., Bauer, B.: Efficiency testing of self-adapting systems by learning of event sequences. In: Proceedings of the 2nd International Conference on Adaptive and Self-adaptive Systems and Applications (ADAPTIVE 2010), pp. 200–205 (2010)

    Google Scholar 

  11. Kephart, J.O., Chess, D.M.: The vision of autonomic computing. Computer 36(1), 41–50 (2003)

    Article  MathSciNet  Google Scholar 

  12. Krömer, P., Martinovic, J., Radecký, M., Tomis, R., Snásel, V.: Ant colony inspired algorithm for adaptive traffic routing. In: Proceedings of the Third World Congress on Nature and Biologically Inspired Computing (NaBIC 2011), pp. 329–334. IEEE, Salamanca (2011)

    Google Scholar 

  13. Lattner, A.D., Bogon, T., Lorion, Y., Timm, I.J.: A knowledge-based approach to automated simulation model adaptation. In: Biaz, S. (ed.) Proceedings of the 43rd Annual Simulation Symposium (ANSS’10), Spring Simulation Multi-Conference (SpringSim’10), pp. 200–207 (2010)

    Google Scholar 

  14. Liu, H., Yu, Q., Ding, W., Ni, D., Wang, H., Shannon, S.: Feasibility study for automatic calibration of transportation simulation models. In: Proceedings of the 44th Annual Simulation Symposium, pp. 87–94. Society for Computer Simulation International, San Diego (2011)

    Google Scholar 

  15. Miller, J.H.: Active nonlinear tests (ANTs) of complex simulation models. Manag. Sci. 44(6), 820–830 (1998)

    Article  MATH  Google Scholar 

  16. Raney, B., Nagel, K.: Iterative route planning for modular transportation simulation. In: Proceedings of the Swiss Transport Research Conference, Monte Verita (2002)

    Google Scholar 

  17. Russell, S.J., Norvig, P.: Artificial Intelligence: A Modern Approach. Prentice Hall Series in Artificial Intelligence, 2nd edn. Pearson Education, Upper Sadle River (2003)

    Google Scholar 

  18. Schumann, R., Lattner, A.D., Timm, I.J.: Management-by-exception - a modern approach to managing self-organizing systems. Commun. SIWN 4, 168–172 (2008)

    Google Scholar 

  19. Schumann, R., Lattner, A.D., Timm, I.J.: Regulated autonomy: a case study. In: Mönch, L., Pankratz, G. (eds.) Intelligente Systeme zur Entscheidungsunterstützung,Teilkonferenz der Multikonferenz Wirtschaftsinformatik, pp. 83–98. SCS, München (2008)

    Google Scholar 

  20. Serugendo, G.D.M., Fitzgerald, J., Romanovsky, A.: Metaself – an architecture and a development method for dependable self-* systems. In: Shin, S.Y., Ossowski, S., Schumacher, M., Palakal, M.J., Hung, C.C. (eds.) Proceedings of the 2010 ACM Symposium on Applied Computing (SAC), pp. 457–461. ACM, New York (2010)

    Chapter  Google Scholar 

  21. Timm, I.J., Schumann, R.: Performance measurement of multiagent systems: towards dependable MAS. In: Proceedings of the 2009 Spring Simulation Multiconference ADS, BIS, MSE, MSEng. Simulation Series, vol. 41, pp. 177–184. SCS, San Diego (2009)

    Google Scholar 

  22. Wolf, T.D., Holvoet, T.: Emergence and self-organisation: a statement of similarities and differences. In: Brueckner, S.A., Serugendo, G.D.M., Karageorgos, A., Nagpal, R. (eds.) Proceedings of the International Workshop on Engineering Self-Organising Applications, pp. 96–110. Springer, New York (2004)

    Google Scholar 

  23. Wooldridge, M.: An Introduction to Multi Agent Systems, 2nd edn. Wiley, Chichester (2009)

    Google Scholar 

  24. Wooldridge, M., Fisher, M., Huget, M.P., Parsons, S.: Model checking multi-agent systems with mable. In: Proceedings of the First International Joint Conference on Autonomous Agents and Multiagent Systems: Part 2. AAMAS ’02, pp. 952–959. ACM, New York (2002)

    Google Scholar 

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Author information

Authors and Affiliations

  1. Institute of Information Systems, HES-SO Valais-Wallis, Sierre, Switzerland

    René Schumann

Authors
  1. René Schumann
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Correspondence to René Schumann .

Editor information

Editors and Affiliations

  1. University of Huddersfield, School of Computing and Engineering, Huddersfield, West Yorkshire, United Kingdom

    Thomas Leo McCluskey

  2. School of Engineering and Computing Scie, Durham University, Co Durham, United Kingdom

    Apostolos Kotsialos

  3. Department of Informatics, TU Clausthal, Clausthal-Zellerfeld, Niedersachsen, Germany

    Jörg P. Müller

  4. Örebro University, School of Science and Technology, Sweden

    Franziska Klügl

  5. School of Computer Science and Informati, Cardiff University, Cardiff, United Kingdom

    Omer Rana

  6. Institute of Information Systems, HES-SO Valais-Wallis, Sierre, Switzerland

    René Schumann

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Schumann, R. (2016). Performance Maintenance of ARTS Systems. In: McCluskey, T., Kotsialos, A., Müller, J., Klügl, F., Rana, O., Schumann, R. (eds) Autonomic Road Transport Support Systems. Autonomic Systems. Birkhäuser, Cham. https://doi.org/10.1007/978-3-319-25808-9_11

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  • DOI: https://doi.org/10.1007/978-3-319-25808-9_11

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  • Publisher Name: Birkhäuser, Cham

  • Print ISBN: 978-3-319-25806-5

  • Online ISBN: 978-3-319-25808-9

  • eBook Packages: Computer ScienceComputer Science (R0)

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