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Universal laws, architectures, and behaviors of robust, evolvable networks

This talk will review recent progress on developing a “unified” theory for complex networks involving several elements: hard limits on achievable robust performance (misnamed “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). A separate morning talk will focus on the results in a recent paper on glycolytic oscillations [7], whereas this will focus on a framework for network architecture as described briefly in[4], [5],[8], with some discussion of representative case studies [1]- [9].

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 apparent [1][7][8]. 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[2][5]. 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 parts[4]. We have the beginnings of the underlying mathematical framework and also a series of case studies in classical problems in complexity from statistical mechanics[6], turbulence[9], cell biology[1][7], human physiology and medicine, neuroscience[8], wildfire ecology[3], earthquakes, economics, the Internet[2][4][5], and smartgrid. The talk will briefly review some aspects of these case studies.

Selected references:
[1] H. El-Samad, H. Kurata, J.C. Doyle , C.A. Gross, and M. Khammash, (2005), Surviving Heat Shock: Control Strategies for Robustness and Performance, P Natl Acad Sci USA 102(8): FEB 22, 2005 [2] Doyle et al, (2005), The “Robust Yet Fragile” Nature of the Internet, P Natl Acad Sci USA 102 (41), October 11, 2005 [3] MA Moritz, ME Morais, LA Summerell, JM Carlson, J Doyle (2005) Wildfires, complexity, and highly optimized tolerance, P Natl Acad Sci USA, 102 (50) December 13, 2005; , [4] M Chiang, SH Low, AR Calderbank, JC. Doyle (2006) Layering As Optimization Decomposition, PROCEEDINGS OF THE IEEE, Volume: 95 Issue: 1 Jan 2007 [5] 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. [6] 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 [7] Chandra F, Buzi G, Doyle JC (2011) Glycolytic oscillations and limits on robust efficiency. Science, Vol 333, pp 187-192. [8] JC Doyle, ME Csete (2011) Architecture, Constraints, and Behavior, P Natl Acad Sci USA, in press, available online [9] 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)
Type of Seminar:
Lecture Series on Directions in Systems and Control
Prof. John Doyle
Division of Engineering and Applied Science, California Institute of Technology, Pasadena, USA
Sep 05, 2011   17:15

HG D 7.1, ETH main building, Rämistrasse 101
Contact Person:

John Lygeros
No downloadable files available.
Biographical Sketch:
John Doyle is the John G Braun Professor of Control and Dynamical Systems, Electrical Engineer, and BioEngineering at Caltech. He has a BS and MS in EE, MIT (1977), and a PhD, Math, UC Berkeley (1984). Current research interests are in theoretical foundations for complex networks in engineering and biology, focusing on architecture, and for multiscale physics. Early work was in the mathematics of robust control, including LQG robustness, (structured) singular value analysis, H-infinity plus recent extensions to nonlinear and networked systems. His research group has collaborated in many software projects, including the Robust Control Toolbox (muTools), SOSTOOLS, SBML (Systems Biology Markup Language), and FAST (Fast AQM, Scalable TCP). Prize paper awards include the IEEE Baker, the IEEE Automatic Control Transactions Axelby (twice), and best conference papers in ACM Sigcomm and AACC American Control Conference. Individual awards include the AACC Eckman, and the IEEE Control Systems Field and Centennial Outstanding Young Engineer Awards. He has held national and world records and championships in various sports. He is best known for having excellent co-authors, students, friends, and colleagues.