Skip to main content
SpringerLink
Log in

Self-organisation for Survival in Complex Computer Architectures

  • Conference paper
Self-Organizing Architectures (SOAR 2009)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 6090))

Included in the following conference series:

  • 641 Accesses

Abstract

This chapter steps back from specific self-organisational architectural solutions to consider what self-organisation means in the context of complex systems. Drawing on insights in complexity and self-organisation, the chapter explores how the natural propensity of complex systems (such as the mammalian immune system) to self-organise could be exploited as a mechanism for adaptation in complex computer architectures. Drawing on experience of immune-inspired fault-tolerant swarm robotics, the chapter speculates on how complex systems such as global information systems could adopt self-organised survivability.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Log in via an institution
Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 39.99
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 54.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Alexander, R., Kazakov, D., Kelly, T.: System of systems hazard analysis using simulation and machine learning. In: Górski, J. (ed.) SAFECOMP 2006. LNCS, vol. 4166, pp. 1–14. Springer, Heidelberg (2006)

    Chapter  Google Scholar 

  2. Alexander, R., Kelly, T.: Simulation and prediction in safety case evidence. In: International System Safety Conference (2008)

    Google Scholar 

  3. Andersson, J., de Lemos, R., Malek, S., Weyns, D.: Reflecting on self-adaptive software systems. In: SEAMS, pp. 38–47. IEEE, Los Alamitos (2009)

    Google Scholar 

  4. Andras, P., Charlton, B.G.: Self-aware software – will it become a reality? In: Babaoğlu, Ö., Jelasity, M., Montresor, A., Fetzer, C., Leonardi, S., van Moorsel, A., van Steen, M. (eds.) SELF-STAR 2004. LNCS, vol. 3460, pp. 229–259. Springer, Heidelberg (2005)

    Chapter  Google Scholar 

  5. Andrews, P.S.: An investigation of a methodology for the development of artificial immune systems: a case study in immune receptor degeneracy. PhD thesis, Department of Computer Science, University of York, YCST-2008-17 (2008)

    Google Scholar 

  6. Andrews, P.S., Timmis, J.: Adaptable lymphocytes for artificial immune systems. In: Bentley, P.J., Lee, D., Jung, S. (eds.) ICARIS 2008. LNCS, vol. 5132, pp. 376–386. Springer, Heidelberg (2008)

    Chapter  Google Scholar 

  7. Ashby, W.R.: Principles of the self-organizing dynamic system. General Psychology 37, 125–128 (1947)

    Google Scholar 

  8. Mohd Azmi, N.F., Timmis, J., Polack, F.A.C.: Profile adaptation in adaptive information filtering: An immune inspired approach. In: SoCPaR, pp. 420–429. IEEE Press, Los Alamitos (2009)

    Google Scholar 

  9. Babaoğlu, Ö., Jelasity, M., Montresor, A., Fetzer, C., Leonardi, S., van Moorsel, A.P.A., van Steen, M.: SELF-STAR 2004. LNCS, vol. 3460. Springer, Heidelberg (2005)

    Book  Google Scholar 

  10. Cayzer, S., Smith, J.: Gene libraries: Coverage, efficiency and diversity. In: Bersini, H., Carneiro, J. (eds.) ICARIS 2006. LNCS, vol. 4163, pp. 136–149. Springer, Heidelberg (2006)

    Chapter  Google Scholar 

  11. Checkland, P.: Systems thinking, systems practice. Wiley, Chichester (1981)

    Google Scholar 

  12. Cohen, I.R.: Tending Adam’s Garden. Evolving the Cognitive Immune Self. Elsevier, Amsterdam (2000)

    Google Scholar 

  13. de Lemos, R., Timmis, J., Forrest, S., Ayara, M.: Immune-inspired adaptable error detection for automated teller machines. IEEE SMC Part C: Applications and Reviews 37(5), 873–886 (2007)

    Google Scholar 

  14. Dyer, M.: The cleanroom approach to quality software development. Wiley, Chichester (1992)

    MATH  Google Scholar 

  15. Edelman, G.M., Gally, J.A.: Degeneracy and complexity in biological systems. PNAS 98(24), 13763–13768 (2001)

    Article  Google Scholar 

  16. Ge, X., Polack, F., Laleau, R.: Secure databases: an analysis of Clark-Wilson model in a database environment. In: Persson, A., Stirna, J. (eds.) CAiSE 2004. LNCS, vol. 3084, pp. 234–247. Springer, Heidelberg (2004)

    Google Scholar 

  17. Greensmith, J., Twycross, J., Aickelin, U.: Dendritic cells for anomaly detection. In: Congress on Evolutionary Computation, pp. 664–671. IEEE Press, Los Alamitos (2006)

    Google Scholar 

  18. Harel, D., Setty, Y., Efroni, S., Swerdlin, N., Cohen, I.R.: Concurrency in biological modeling: Behavior, execution and visualization. In: FBTC 2007. ENTCS, vol. 194(3), pp. 119–131. Elsevier, Amsterdam (2007)

    Google Scholar 

  19. Herrmann, K., Timmis, J., Fairclough, S.: Challenges in pervasive adaptation (under review, 2009)

    Google Scholar 

  20. Hinchey, M.G., Sterritt, R.: Self-managing software. IEEE Computer 39(2), 107–109 (2006)

    Google Scholar 

  21. Kernbach, S., Hamann, H., Stradner, J., Thenius, R., Schmickl, T., van Rossum, A.C., Sebag, M., Bredeche, N., Yao, Y., Baele, G., Van de Peer, Y., Timmis, J., Mohktar, M., Tyrrell, A., Eiben, A.E., McKibbin, S.P., Liu, W., Winfield, A.F.T.: On adaptive self-organization in artificial robot organisms. In: Adaptive and Self-adaptive Systems and Applications. IEEE Press, Los Alamitos (2009)

    Google Scholar 

  22. Knight, J.C., Strunk, E.A.: Achieving critical system survivability through software architectures. In: de Lemos, R., Gacek, C., Romanovsky, A. (eds.) Architecting Dependable Systems II. LNCS, vol. 3069, pp. 51–78. Springer, Heidelberg (2004)

    Google Scholar 

  23. Kurd, Z., Kelly, T., Austin, J.: Developing artificial neural networks for safety critical systems. Neural Computing and Applications 16(1), 11–19 (2006)

    Article  Google Scholar 

  24. Miller, B.: The autonomic computing edge: Can you chop up autonomic computing? IBM Technical Library (March 2008), http://www.ibm.com/developerworks/library/ac-edge4/index.html

  25. Mokhtar, M., Bi, R., Timmis, J., Tyrrell, A.M.: A modified dendritic cell algorithm for on-line error detection in robotic systems. In: Congress on Evolutionary Computation, pp. 2055–2062. IEEE Press, Los Alamitos (2009)

    Chapter  Google Scholar 

  26. Owens, N.D., Timmis, J., Greensted, A.J., Tyrrell, A.M.: On immune inspired homeostasis for electronic systems. In: de Castro, L.N., Von Zuben, F.J., Knidel, H. (eds.) ICARIS 2007. LNCS, vol. 4628, pp. 216–227. Springer, Heidelberg (2007)

    Chapter  Google Scholar 

  27. Owens, N.D.L., Greensted, A.J., Timmis, J., Tyrrell, A.M.: T cell receptor signalling inspired kernel density estimation and anomaly detection. In: Andrews, P.S. (ed.) ICARIS 2009. LNCS, vol. 5666, pp. 122–135. Springer, Heidelberg (2009)

    Google Scholar 

  28. Polack, F., Stepney, S., Turner, H., Welch, P., Barnes, F.: An architecture for modelling emergence in CA-like systems. In: Capcarrère, M.S., Freitas, A.A., Bentley, P.J., Johnson, C.G., Timmis, J. (eds.) ECAL 2005. LNCS (LNAI), vol. 3630, pp. 433–442. Springer, Heidelberg (2005)

    Chapter  Google Scholar 

  29. Polack, F.A.C., Andrews, P.S., Sampson, A.T.: The engineering of concurrent simulations of complex systems. In: Congress on Evolutionary Computation, pp. 217–224. IEEE Press, Los Alamitos (2009)

    Chapter  Google Scholar 

  30. Polack, F.A.C., Hoverd, T., Sampson, A.T., Stepney, S., Timmis, J.: Complex systems models: Engineering simulations. In: ALife XI. MIT Press, Cambridge (2008)

    Google Scholar 

  31. Read, M., Andrews, P.S., Timmis, J., Kumar, V.: A domain model of Experimental Autoimmune Encephalomyelitis. In: Workshop on Complex Systems Modelling and Simulation, pp. 9–44. Luniver Press (2009)

    Google Scholar 

  32. Sargent, R.G.: The use of graphical models in model validation. In: 18th Winter Simulation Conference, pp. 237–241. ACM, New York (1986)

    Google Scholar 

  33. Sargent, R.G.: Verification and validation of simulation models. In: 37th Winter Simulation Conference, pp. 130–143. ACM, New York (2005)

    Chapter  Google Scholar 

  34. Shalizi, C.R.: Causal Architecture, Complexity, and Self-Organization in Time Series and Cellular Automata. PhD thesis, Physics Department, University of Wisconsin at Madison (2001)

    Google Scholar 

  35. Shalizi, C.R., Shalizi, K.L., Haslinger, R.: Quantifying self-organization with optimal predictors. Physical Review Letters 93(11), 118701 (2004)

    Article  Google Scholar 

  36. Stepney, S., Smith, R.E., Timmis, J., Tyrrell, A.M.: Towards a conceptual framework for artificial immune systems. In: Nicosia, G., Cutello, V., Bentley, P.J., Timmis, J. (eds.) ICARIS 2004. LNCS, vol. 3239, pp. 53–64. Springer, Heidelberg (2004)

    Google Scholar 

  37. Tabatabaie, M., Paige, R.F., Kimble, C.: Exploring enterprise information systems. In: Cruz-Cunha, M. (ed.) Social, Managerial, and Organizational Dimensions of Enterprise Information Systems, pp. 415–433. IGI Global (2010)

    Google Scholar 

  38. Timmis, J., Tyrrell, A., Mokhtar, M., Ismail, A., Owens, N., Bi, R.: An artificial immune system for robot organisms. In: Levi, P., Kernbach, S. (eds.) Symbiotic Multi-Robot Organisms: Reliability, Adaptability, Evolution, pp. 268–288. Springer, Heidelberg (April 2010) (to appear)

    Google Scholar 

  39. Tononi, G., Sporns, O., Edelman, G.M.: Measures of degeneracy and redundancy in biological networks. PNAS 96(6), 3257–3262 (1999)

    Article  Google Scholar 

  40. Tsankova, D., Georgieva, V., Zezulka, F., Bradac, Z.: Immune network control for stigmergy based foraging behaviour of autonomous mobile robots. International Journal of Adaptive Control and Signal Processing 21(2), 265–286 (2006)

    Article  MathSciNet  Google Scholar 

  41. Wenkstern, R.Z., Steel, T., Leask, G.: A self-organizing architecture for traffic management. In: Self-Organizing Architectures (2009)

    Google Scholar 

  42. Whitbrook, A., Aickelin, U., Garibaldi, J.: An idiotypic immune network as a short-term learning architecture for mobile robots. In: Bentley, P.J., Lee, D., Jung, S. (eds.) ICARIS 2008. LNCS, vol. 5132, pp. 266–278. Springer, Heidelberg (2008)

    Chapter  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Department of Computer Science, University of York, UK, YO10 5DD

    Fiona A. C. Polack

Authors
  1. Fiona A. C. Polack
    View author publications

    You can also search for this author in PubMed Google Scholar

Editor information

Editors and Affiliations

  1. Katholieke Universiteit Leuven, Belgium

    Danny Weyns

  2. George Manson University, Fairfax, USA

    Sam Malek

  3. Computing Laboratory, University of Kent, CT2 7NF, Canterbury, Kent, UK

    Rogério de Lemos

  4. Linnaeus University, Växjö, Sweden

    Jesper Andersson

Rights and permissions

Reprints and permissions

Copyright information

© 2010 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Polack, F.A.C. (2010). Self-organisation for Survival in Complex Computer Architectures. In: Weyns, D., Malek, S., de Lemos, R., Andersson, J. (eds) Self-Organizing Architectures. SOAR 2009. Lecture Notes in Computer Science, vol 6090. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-14412-7_4

Download citation

  • DOI: https://doi.org/10.1007/978-3-642-14412-7_4

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-14411-0

  • Online ISBN: 978-3-642-14412-7

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics

Search

Navigation