Abstract: This talk will review recent
progress on developing a unified theory for complex networks of hard limits on
achievable robust performance (laws) and the organizing principles that succeed
or fail in achieving them (architectures and protocols). A collection of new unified hard limit
theorems will be compared with case studies drawn from cell biology,
development, human physiology and medicine, Internet, wildfire ecology, and more
whimsically with Lego, clothing and fashion, and market economics. Of
particular interest are the origins and mechanisms of high variability and
volatility observed throughout these systems that point to systemic
fragilities. The biggest new insights
that I think will most interest people who have heard previous versions of this
talk are in comparing the layered architectures of the cell and Internet, what
is “broken” about the latter and misleading but fixable about many popular
theories of the former.
Biological systems are robust and
evolvable in the face of even large changes in environment and system
components, yet can simultaneously be extremely fragile to other small
perturbations. Such universally robust yet fragile (RYF) complexity is found
wherever we look. The amazing evolution of microbes into humans (robustness of
lineages on long timescales) is punctuated by mass extinctions (extreme
fragility). Diabetes, obesity, cancer, and autoimmune diseases are side-effects
of biological control and compensatory mechanisms so robust as to normally go
unnoticed. RYF complexity is not confined to biology. The complexity of modern
institutions and technologies is exploding, but in ways that remain largely
hidden. They facilitate robustness and
accelerate evolution, but enable catastrophes on a scale unimaginable without
them (from network and market crashes to war, epidemics, and global warming). Understanding
RYF means understanding architecture — the most universal, high-level, persistent
elements of organization — and protocols. Protocols define how diverse modules
interact, and architecture defines how sets of protocols are organized.
Insights into the laws,
architecture, and organizational principles of networked systems can be drawn
from three converging research themes. 1)
With molecular biology’s description of components and growing attention to
systems biology, the organizational principles of biological networks are
becoming increasingly apparent. Biologists
are articulating richly detailed explanations of biological complexity,
robustness, and evolvability that point to universal principles and
architectures. This talk will connect these insights with the role of layering,
protocols, and feedback control in structuring complex multiscale modularity,
and contrast strikingly with many popular mainstream “theories” that ignore
biological functionality and evolution. 2)
Advanced technology’s complexity is now approaching biology’s. While the
components differ, there is striking convergence at the network level. New
theories of the Internet and related networking technologies have led to test
and deployment of new protocols, and suggest a fundamental rethinking of
network architecture, including those involved in finance and economics. 3) A
new mathematical framework 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 the universal system requirements
to be efficient, adaptive, evolvable, and robust to perturbations in their environment
and component parts. The universal hard
limits on systems and their components have until recently been studied
separately in fragmented domains of control, communication, computation, physics,
and chemistry, but a unified theory is needed and appears feasible.
Selected
references:
[1] Csete M.E. and
J.C. Doyle, (2004), Bow ties, metabolism, and disease, Trends in Biotechnology, Vol 22, Issue 9, pg. 446-450
[2] H. El-Samad, H. Kurata, J.C. Doyle, C.A. Gross, and M.
Khammash, (2005), Surviving Heat Shock: Control Strategies for Robustness and
Performance, PNAS 102(8): FEB 22,
2005
[3] Jin C, Wei D, Low SH, Bunn J, Choe HD, Doyle JC,et al (2005),
FAST TCP: From theory to experiments IEEE NETWORK 19 (1): 4-11
JAN-FEB 2005
[4] J. Doyle and M. Csete (2005). Motifs, stability,
and control. PLOS Biology, 3, 2005.
[5] Doyle et al,
(2005), The “Robust Yet Fragile” Nature of the Internet, PNAS 102 (41), October 11, 2005
[6] MA Moritz, ME
Morais, LA Summerell, JM Carlson, J Doyle (2005)
Wildfires, complexity, and highly optimized tolerance, PNAS, 102 (50) December 13, 2005
[7] L Li, D Alderson, JC Doyle, W Willinger (2006) Towards
a Theory of Scale-Free Graphs: Definition, Properties, and Implications, Internet Math, Vol. 2, No. 4, 2006
[8] H El-Samad, A Papachristodoulou, S
Prajna, J Doyle, and M Khammash (2006), Advanced Methods and Algorithms for
Biological Networks Analysis, PROCEEDINGS
OF THE IEEE, 94 (4): 832-853
APR 2006
[9] Kurata, H El-Samad, R Iwasaki, H Ohtake, JC Doyle, et al. (2006) Module-based analysis of robustness tradeoffs in
the heat shock response system. PLoS
Comput Biol 2(7): July 2006
[10] M Chiang, SH Low, AR Calderbank, JC. Doyle (2006)
Layering As Optimization Decomposition, PROCEEDINGS
OF THE IEEE, Volume: 95 Issue: 1 Jan 2007
[11] Martins NC, Dahleh MA, Doyle JC (2007) Fundamental
Limitations of Disturbance Attenuation in the Presence of Side Information, IEEE
Trans Auto Control, Feb 2007
[12] Doyle
J, and Csete M, Rules of engagement. NATURE 446 (7138): 860-860 APR 19 2007
(PMID: 17443168)
[13] http://www.istar.upenn.edu/osw/white%20paper/John%20Doyle%20White%20Paper.pdf, preprint, Contrasting Views of Complexity and Their Implications
For Network-Centric Infrastructures, by David L. Alderson, John C. Doyle