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Published July 2010 | Published
Journal Article Open

Contrasting Views of Complexity and Their Implications For Network-Centric Infrastructures

Abstract

There exists a widely recognized need to better understand and manage complex "systems of systems," ranging from biology, ecology, and medicine to network-centric technologies. This is motivating the search for universal laws of highly evolved systems and driving demand for new mathematics and methods that are consistent, integrative, and predictive. However, the theoretical frameworks available today are not merely fragmented but sometimes contradictory and incompatible. We argue that complexity arises in highly evolved biological and technological systems primarily to provide mechanisms to create robustness. However, this complexity itself can be a source of new fragility, leading to "robust yet fragile" tradeoffs in system design. We focus on the role of robustness and architecture in networked infrastructures, and we highlight recent advances in the theory of distributed control driven by network technologies. This view of complexity in highly organized technological and biological systems is fundamentally different from the dominant perspective in the mainstream sciences, which downplays function, constraints, and tradeoffs, and tends to minimize the role of organization and design.

Additional Information

© 2010 IEEE. Manuscript received July 1, 2008; revised March 10, 2009. Date of publication June 3, 2010; date of current version June 16, 2010. This paper was presented in part at the 2007 IEEE International Conference on Systems, Man and Cybernetics, Montreal, QC, Canada, October 7–10, 2007. This work was supported by the Office of Naval Research under MURI Awards 0001408WR20242 and N000140810747. This paper was recommended by Associate Editor M. Ulieru. The authors would like to thank the two anonymous referees for their considerable help in organizing this paper and for their direct contributions to the articulation of ideas on systems engineering and design for robustness.

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