This talk will focus on progress towards a more “unified” theory for complex networks involving several elements: hard limits on achievable robust performance ( “laws”), the organizing principles that succeed or fail in achieving them (architectures and protocols), the resulting high variability data and “robust yet fragile” behavior observed in real systems and case studies (behavior, data), and the processes by which systems evolve (variation, selection, design). Insights into what the potential universal laws, architecture, and organizational principles are can be drawn from three converging research themes. First, detailed description of components and a growing attention to systems in biology and neuroscience, the organizational principles of organisms and evolution are becoming increasingly. Biologists are articulating richly detailed explanations of biological complexity, robustness, and evolvability that point to universal principles and architectures. Second, while the components differ and the system processes are far less integrated, advanced technology’s complexity is now approaching biology’s and there are striking convergences at the level of organization and architecture, and the role of layering, protocols, and feedback control in structuring complex multiscale modularity. Third, new mathematical frameworks for the study of complex networks suggests that this apparent network-level evolutionary convergence within/between biology/technology is not accidental, but follows necessarily from their universal system requirements to be fast, efficient, adaptive, evolvable, and most importantly, robust to perturbations in their environment and component part. We have the beginnings of the underlying mathematical framework and also a series of case studies in classical problems in complexity from statistical mechanics, turbulence, cell biology, human physiology and medicine, neuroscience, wildfire, earthquakes, economics, the Internet, and smartgrid. A workshop preceding CDC will explore this in more detail (with Pablo Parrilo).
 M Chiang, SH Low, AR Calderbank, JC. Doyle (2006) Layering As Optimization Decomposition, PROCEEDINGS OF THE IEEE, Volume: 95 Issue: 1 Jan 2007
Alderson DL, Doyle JC (2010) Contrasting views of complexity and their implications for network-centric infrastructures. IEEE Trans Systems Man Cybernetics—Part A: Syst Humans 40:839-852.
H. Sandberg, J. C. Delvenne, J. C. Doyle. On Lossless Approximations, the Fluctuation-Dissipation Theorem, and Limitations of Measurements, IEEE Trans Auto Control, Feb 2011
Chandra F, Buzi G, Doyle JC (2011) Glycolytic oscillations and limits on robust efficiency. Science, Vol 333, pp 187-192.
JC Doyle, ME Csete (2011) Architecture, Constraints, and Behavior, P Natl Acad Sci USA, in press, available online
Gayme DF, McKeon BJ, Bamieh B, Papachristodoulou P, Doyle JC (2011) Amplification and Nonlinear Mechanisms in Plane Couette Flow, Physics of Fluids, in press (published online 17 June 2011)