Advertisement

Through a Glass, Darkly? Taking a Network Perspective on System-of-Systems Architectures

  • Matthew PottsEmail author
  • Pia Sartor
  • Angus Johnson
  • Seth Bullock
Conference paper

Abstract

A system-of-systems architecture can be thought of as a complex network comprising a set of entities of different types, connected together by a set of relationships, also of different types. A systems architect might attempt to make use of the analytic tools associated with network science when evaluating such architectures, anticipating that taking a “network perspective” might offer insights into their structure. However, taking a network perspective on real-world system-of-systems architectures is fraught with challenges. The relationship between the architecture and a network representation can be overly simplistic, meaning that network-theoretic models can struggle to respect, inter alia, the heterogeneity of system entities and their relationships, the richness of their behavior, and the vital role of context in an architecture. A more mature conceptualization of the relationship between architectures and their network representations is required before the lens of network science can offer a usefully clear view of architecture properties.

References

  1. 1.
    Potts, M., Sartor, P., Johnson, A., Bullock, S.: Hidden structures: using graph theory to explore complex system of systems architectures. In: Paper presented at the International Conference on Complex Systems Design & Management. CSD&M, Paris, France, December 2017Google Scholar
  2. 2.
    North Atlantic Treaty Organization: NATO architecture framework v4.0 documentation (draft) (2017). http://nafdocs.org/
  3. 3.
    Diestel, R.: Graph Theory, Electronic. In: Graduate Texts in Mathematics, vol. 173. Springer, Berlin (2005)Google Scholar
  4. 4.
    Blondel, V.D., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. J. Stat. Mech. Theory Exp. 10, P10008 (2008)CrossRefGoogle Scholar
  5. 5.
    Biggs, B.: Ministry of defence architectural framework (MODAF) (2005)Google Scholar
  6. 6.
    Newman, M.: Networks: an Introduction. Oxford University Press, Oxford (2010)CrossRefGoogle Scholar
  7. 7.
    Okami, S., Kohtake, N.: Transitional complexity of health information system of systems: managing by the engineering systems multiple-domain modeling approach. IEEE Syst. J., 1–12 (2017)Google Scholar
  8. 8.
    Bartolomei, J.E., Hastings, D.E., de Neufville, R., Rhodes, D.H.: Engineering systems multiple-domain matrix: an organizing framework for modeling large-scale complex systems. Syst. Eng. 15(1), 41–61 (2012)CrossRefGoogle Scholar
  9. 9.
    Santana, A., Kreimeyer, M., Clo, P., Fischbach, K., de Moura, H.: An empirical investigation of enterprise architecture analysis based on network measures and expert knowledge: a case from the automotive industry. In: Modern Project Management, pp. 46–56 (2016)Google Scholar
  10. 10.
    Iyer, B., Dreyfus, D., Gyllstrom, P.: A network-based view of enterprise architecture. In: Handbook of Enterprise Systems Architecture in Practice, p. 500. PFPC Worldwide Inc., USA (2007)CrossRefGoogle Scholar
  11. 11.
    Freeman, L.C.: Centrality in social networks conceptual clarification. Soc. Netw. 1(3), 215–239 (1978)CrossRefGoogle Scholar
  12. 12.
    Boldi, P., Vigna, S.: Axioms for centrality. Internet Math. 10(3–4), 222–262 (2014)MathSciNetCrossRefGoogle Scholar
  13. 13.
    Brandes, U.: A faster algorithm for betweenness centrality. J. Math. Sociol. 25(2), 163–177 (2001)CrossRefGoogle Scholar
  14. 14.
    Newman, M.E.: The mathematics of networks. In: The New Palgrave Encyclopedia of Economics, 2nd edn., pp 1–12 (2008)Google Scholar
  15. 15.
    IEEE/ISO/IEC Draft Standard for Systems and Software Engineering - Architecture Evaluation, pp. 1–76 (2017). ISO/IEC/IEEE DIS P42030/D1, December 2017Google Scholar
  16. 16.
    Kossiakoff, A., Sweet, W.N., Seymour, S.J., Biemer, S.M.: Systems Engineering Principles and Practice, vol. 83. Wiley, London (2011)CrossRefGoogle Scholar
  17. 17.
    Buede, D.M., Miller, W.D.: The Engineering Design of Systems: Models and Methods. Wiley, London (2016)Google Scholar
  18. 18.
    Bullock, S., Barnett, L., Di Paolo, E.A.: Spatial embedding and the structure of complex networks. Complexity 16(2), 20–28 (2010)CrossRefGoogle Scholar
  19. 19.
    Sinha, K., de Weck, O.L.: Structural complexity metric for engineered complex systems and its application. In: Gain Competitive Advantage by Managing Complexity: Proceedings of the 14th International DSM Conference Kyoto, Japan, pp. 181–194 (2012)Google Scholar
  20. 20.
    Lloyd, S.: Measures of complexity: a nonexhaustive list. IEEE Control Syst. Mag. 21(4), 7–8 (2001)CrossRefGoogle Scholar
  21. 21.
    Sheard, S.A.: 5.2. 1 systems engineering complexity in context. In: INCOSE International Symposium, vol. 1, pp. 1145–1158. Wiley Online Library (2013)Google Scholar
  22. 22.
    Fischi, J., Nilchiani, R., Wade, J.: Dynamic complexity measures for use in complexity-based system design. IEEE Syst. J. 11(4), 2018–2027 (2015)CrossRefGoogle Scholar
  23. 23.
    MacCormack, A.: The architecture of complex systems: do “core-periphery” structures dominate? In: Academy of Management Proceedings, vol 1, pp. 1–6. Academy of Management (2010)CrossRefGoogle Scholar
  24. 24.
    Rechtin, E.: Systems architecting: Creating and building complex systems, vol. 1. Prentice Hall, Englewood Cliffs (1991)Google Scholar
  25. 25.
    Sillitto, H.: Architecting Systems: Concepts, Principles and Practice. College Publications, London (2014)Google Scholar
  26. 26.
    Newman, M.E.: Mixing patterns in networks. Phys. Rev. E 67(2), 026126 (2003)MathSciNetCrossRefGoogle Scholar
  27. 27.
    ISO/IEC/IEEE International standard - systems and software engineering – system life cycle processes, pp. 1–118 (2015). ISO/IEC/IEEE 15288 First edition 2015-05-15.  https://doi.org/10.1109/ieeestd.2015.7106435
  28. 28.
    Freeman, L.: The Development of Social Network Analysis. A Study in the Sociology of Science 1. Empirical Press, Vancouver (2004)Google Scholar
  29. 29.
    Gilbert, N., Bullock, S.: Complexity at the social science interface. Complexity 19(6), 1–4 (2014)CrossRefGoogle Scholar
  30. 30.
    Crawley, E., De Weck, O., Magee, C., Moses, J., Seeringk, W., Schindall, J., Wallace, D., Whitney, D.: The influence of architecture in engineering systems (monograph) (2004)Google Scholar
  31. 31.
    De Weck, O.L., Roos, D., Magee, C.L.: Engineering Systems: Meeting Human Needs in a Complex Technological World. Mit Press, Cambridge (2011)CrossRefGoogle Scholar
  32. 32.
    De Weck, O.L., Ross, A.M., Rhodes, D.H.: Investigating relationships and semantic sets amongst system lifecycle properties (Ilities) (2012)Google Scholar
  33. 33.
    De Neufville, R., Scholtes, S.: Flexibility in Engineering Design. MIT Press, Cambridge (2011)CrossRefGoogle Scholar
  34. 34.
    Newman, M.E.: Complex systems: a survey (2011). arXiv preprint arXiv:11121440
  35. 35.
    Newman, M.E.: The structure and function of complex networks. SIAM Rev. 45(2), 167–256 (2003)MathSciNetCrossRefGoogle Scholar
  36. 36.
    Albert, R., Jeong, H., Barabási, A.-L.: Error and attack tolerance of complex networks (2000). arXiv preprint cond-mat/0008064Google Scholar
  37. 37.
    Khoury, M., Bullock, S.: Multi-level resilience: reconciling robustness, recovery and adaptability from a network science perspective. Int. J. Adapt. Resil. Auton. Syst. (IJARAS) 5(4), 34–45 (2014)CrossRefGoogle Scholar
  38. 38.
    Khoury, M., Bullock, S., Fu, G., Dawson, R.: Improving measures of topological robustness in networks of networks and suggestion of a novel way to counter both failure propagation and isolation. Infrastruct. Complex. 2(1), 1 (2015)CrossRefGoogle Scholar
  39. 39.
    Boardman, J., Sauser, B.: System of systems-the meaning of of. In: Proceedings of the 2006 IEEE/SMC International Conference on System of Systems Engineering Los Angeles, CA, USA, pp. 118–126, April 2006Google Scholar
  40. 40.
    Maier, M.W.: Architecting principles for systems‐of‐systems. In: INCOSE International Symposium, vol 1. Wiley Online Library, pp. 565–573 (1996)Google Scholar
  41. 41.
    ISO/IEC/IEEE Draft international standard - systems and software engineering - systems of systems considerations in engineering of systems, pp. 1–43 (2017). ISO/IEC/IEEE P21839, April 2017Google Scholar
  42. 42.
    Fu, G., Dawson, R., Khoury, M., Bullock, S.: Interdependent networks: vulnerability analysis and strategies to limit cascading failure. Eur. Phys. J. B 87(7), 148 (2014)CrossRefGoogle Scholar
  43. 43.
    Marvin, J.W., Garrett Jr., R.K.: Quantitative SoS architecture modeling. Procedia Comput. Sci. 36, 41–48 (2014)CrossRefGoogle Scholar
  44. 44.
    ISO/IEC/IEEE DIS 42020 Enterprise, systems and software - architecture processes (2017)Google Scholar
  45. 45.
    Barnett, L., Buckley, C.L., Bullock, S.: Neural complexity: a graph theoretic interpretation. Phys. Rev. E 83(4), 041906 (2011)CrossRefGoogle Scholar
  46. 46.
    Brughmans, T.: Connecting the dots: towards archaeological network analysis. Oxf. J. Archaeol. 29(3), 277–303 (2010)CrossRefGoogle Scholar

Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  • Matthew Potts
    • 1
    Email author
  • Pia Sartor
    • 1
  • Angus Johnson
    • 2
  • Seth Bullock
    • 1
  1. 1.University of Bristol, Faculty of EngineeringBristolUK
  2. 2.Thales Research and Technology UKReadingUK

Personalised recommendations