Universal laws and architecture: Challenges for Sustainable Infrastructure John Doyle John G Braun Professor Control and Dynamical Systems, EE, BioE Caltech

“Universal laws and architectures?” Universal “conservation laws” (constraints) Universal architectures (constraints that deconstrain) Mention recent papers* Focus on broader context not in papers Lots of theorems Case studies: evolution, physiology, bacterial biosphere,, glycolytic oscillations, Internet/IT, neuroscience, smartgrid, aerospace, wildfire ecology, turbulence, stat mech, earthquakes, heart rate variability *try to get you to read them?

Collaborators and contributors (partial list, out of date,…) Theory: Parrilo, Carlson, Murray, Vinnicombe, Paganini, Papachristodoulou, Prajna, Goncalves, Fazel, Liu, Lall, D’Andrea, Jadbabaie, Dahleh, Martins, Recht, many more current and former students, … Biology: Chandra, Buzi, Csete,Yi, El-Samad, Khammash, Tanaka, Arkin, Savageau, Simon, Gross, Kitano, Hucka, Gillespie, Petzold, F Doyle, Stelling, Caporale,… Web/Internet: Chen, Low, Lavaei, Sojoudi, Li, Alderson, Willinger, Kelly, Zhu,Yu, Wang, Chandy, Trossen, Griffin,… Turbulence: Gayme, McKeon, Bamieh, Bobba, Gharib, Marsden, … Physics: Sandberg, Delvenne, Barahona, Carlson, Asimakopoulos, Matni,… Disturbance ecology: Moritz, Carlson,… Neuroscience: Lamperski, Grafton, Gazzaniga, Mitra,… Current CaltechFormer CaltechOtherLongterm Visitor

Thanks to NSF ARO ONR Braun family Lee Center for Advanced Networking (Caltech) Philips NIH/NIGMS? AFOSR? DARPA? Special thanks to Hiroaki Kitano (ERATO)

Happy families are all alike; every unhappy family is unhappy in its own way. Leo Tolstoy, Anna Karenina, Chapter 1, first line What does this even mean? Given incredible diversity of people and environments? It has to be a statement about organization. Happy family = empathy + cooperation + simple rules? Constraints on components and architecture

wasteful fragile efficient robust Happy families are all alike; every unhappy family is unhappy in its own way. Want robust and efficient systems and architectures Are robust, efficient systems/architectures “all alike”?

accessible accountable accurate adaptable administrable affordable auditable autonomy available credible process capable compatible composable configurable correctness customizable debugable degradable determinable demonstrable dependable deployable discoverable distributable durable effective efficient evolvable extensible failure transparent fault-tolerant fidelity flexible inspectable installable Integrity interchangeable interoperable learnable maintainable manageable mobile modifiable modular nomadic operable orthogonality portable precision predictable producible provable recoverable relevant reliable repeatable reproducible resilient responsive reusable robust safety scalable seamless self-sustainable serviceable supportable securable simplicity stable standards compliant survivable sustainable tailorable testable timely traceable ubiquitous understandable upgradable usable Requirements on systems and architectures happy?

accessible accountable accurate adaptable administrable affordable auditable autonomy available credible process capable compatible composable configurable correctness customizable debugable degradable determinable demonstrable dependable deployable discoverable distributable durable effective efficient evolvable extensible failure transparent fault-tolerant fidelity flexible inspectable installable Integrity interchangeable interoperable learnable maintainable manageable mobile modifiable modular nomadic operable orthogonality portable precision predictable producible provable recoverable relevant reliable repeatable reproducible resilient responsive reusable robust safety scalable seamless self-sustainable serviceable supportable securable simplicity stable standards compliant survivable sustainable tailorable testable timely traceable ubiquitous understandable upgradable usable Requirements on systems and architectures happy?

accessible accountable accurate adaptable administrable affordable auditable autonomy available credible process capable compatible composable configurable correctness customizable debugable degradable determinable demonstrable dependable deployable discoverable distributable durable effective efficient evolvable extensible failure transparent fault-tolerant fidelity flexible inspectable installable Integrity interchangeable interoperable learnable maintainable manageable mobile modifiable modular nomadic operable orthogonality portable precision predictable producible provable recoverable relevant reliable repeatable reproducible resilient responsive reusable robust safety scalable seamless self-sustainable serviceable supportable securable simplicity stable standards compliant survivable sustainable tailorable testable timely traceable ubiquitous understandable upgradable usable Requirements on systems and architectures wasteful fragile efficient robust

wasteful fragile efficient robust Happy families are all alike; every unhappy family is unhappy in its own way. Want robust and efficient systems and architectures In what sense are robust, efficient systems/architectures all alike?

inefficient wasteful weak fragile efficient (slow) strong robust Biology Human evolution Apes feet skeleton muscle skin gut hands

inefficient wasteful weak fragile efficient (slow) strong robust Biology Hard tradeoffs? Apes Architecture?

inefficient wasteful weak fragile efficient (slow) strong robust Biology sticks stones fire +Technology

inefficient wasteful weak fragile efficient (slow) strong robust Biology +Technology ++Technology

wasteful fragile efficient robust Hard tradeoffs? Architecture? Constraints (that deconstrain)

wasteful fragile efficient robust Next 3 speakers

Biology sticks stones fire +Technology feet skeleton muscle skin gut hands Human complexity? wasteful fragile efficient robust

RobustFragile Human complexity Metabolism Regeneration & repair Healing wound /infect  Obesity, diabetes  Cancer  AutoImmune/Inflame Start with physiology Lots of triage

RobustFragile Mechanism? Metabolism Regeneration & repair Healing wound /infect  Fat accumulation  Insulin resistance  Proliferation  Inflammation  Obesity, diabetes  Cancer  AutoImmune/Inflame  Fat accumulation  Insulin resistance  Proliferation  Inflammation

RobustFragile What’s the difference? Metabolism Regeneration & repair Healing wound /infect  Obesity, diabetes  Cancer  AutoImmune/Inflame  Fat accumulation  Insulin resistance  Proliferation  Inflammation Controlled Dynamic Uncontrolled Chronic

Controlled Dynamic Uncontrolled Chronic Low mean High variability High mean Low variability  Fat accumulation  Insulin resistance  Proliferation  Inflammation Death

RobustFragile Restoring robustness? Metabolism Regeneration & repair Healing wound /infect  Obesity, diabetes  Cancer  AutoImmune/Inflame  Fat accumulation  Insulin resistance  Proliferation  Inflammation Controlled Dynamic Uncontrolled Chronic Low mean High variability High mean Low variability  Fat accumulation  Insulin resistance  Proliferation  Inflammation

RobustFragile Metabolism Regeneration & repair Healing wound /infect  Obesity, diabetes  Cancer  AutoImmune/Inflame  Fat accumulation  Insulin resistance  Proliferation  Inflammation Fragility  Hijacking, side effects, unintended… Of mechanisms evolved for robustness Complexity  control, robust/fragile tradeoffs Math: robust/fragile constraints (“conservation laws”) Accident or necessity? Both

Human complexity? wasteful fragile efficient robust

RobustYet Fragile Human complexity Metabolism Regeneration & repair Immune/inflammation Microbe symbionts Neuro-endocrine  Complex societies  Advanced technologies  Risk “management”  Obesity, diabetes  Cancer  AutoImmune/Inflame  Parasites, infection  Addiction, psychosis,…  Epidemics, war,…  Disasters, global &!%$#  Obfuscate, amplify,… Accident or necessity?

In the real (vs virtual) world What matters: Action What doesn’t: Data Information Computation Learning Decision …

Don’t worry... “Like, dude, like, chill…” “There’s an app for that.” “The ‘new sciences’ of …” “There’s a gene… “The market will...” “Order for free…” “The rapture is near.”

Don’t worry... “Like, dude, like, chill…” “There’s an app for that.” “The ‘new sciences’ of …” “There’s a gene… “The market will...” “Order for free…” “The rapture is near.” Come back to this later

IEEE TRANS ON SYSTEMS, MAN, AND CYBERNETICS, JULY 2010, Alderson and Doyle

Csete and Doyle

Feathers and flapping? Or lift, drag, propulsion, and control? The dangers of naïve biomemetics

Getting it (W)right, 1901 “We know how to construct airplanes...” (lift and drag) “… also know how to build engines.” (propulsion) “Inability to balance and steer still confronts students of the flying problem.” (control) “When this one feature has been worked out, the age of flying will have arrived, for all other difficulties are of minor importance.” Wilbur Wright on Control, 1901

Getting it right, 2011 “...know how to construct sustainable infrastructures...” “… also know how to build their components.” “Inability to control and manage fragilities....” “When this one feature has been worked out, the age of sustainability will have arrived, for all other difficulties are of minor importance.” Fragilities? Unintended crashes, hijacking, parasitism, evolution Need robust, efficient, evolvable architectures Policy trumps technology (next talks) Aligning incentives (next talks)

wasteful fragile efficient robust Hard tradeoffs?

Chandra, Buzi, and Doyle

simple enzyme Fragility Metabolic Overhead complex enzyme Theorem!

Glycolytic “circuit” and oscillations Perfect circuit case study – Every cell (10 30 ), heavily studied – Experiments, models, simulation, …, all “well-known” Oscillations? – Remain persistent mystery (decades,…?) – Frozen accident? Edge of chaos? Emergulence? New insight: constraints and tradeoffs – “Universal” robustness/efficiency tradeoff – Evolution + physiology + “CDS” theory – Issues & theory: broadly relevant and “universal” Extreme responses typical ubiquitous

Glycolytic “circuit” and oscillations End of an old story (why oscillations) – no purpose per se – side effect of hard robustness/efficiency tradeoffs – just needed a theorem Beginning of a new one – robustness/efficiency tradeoffs – complexity and architecture – need more theorems and applications

robust efficientwasteful fragile Tradeoffs? Hard limit Robust=maintain energy level w/fluctuating demand Efficient=minimize metabolic overhead Want robust and efficient

Control, ORComms Compute Physics Shannon Bode Turing Godel Einstein Heisenberg Carnot Boltzmann Theory? Deep, but fragmented, incoherent, incomplete Nash Von Neumann Kalman Pontryagin

ControlComms Compute Physics Shannon Bode Turing Godel Einstein Heisenberg Carnot Boltzmann wasteful? fragile? slow? ? Each theory  one dimension Tradeoffs across dimensions Assume architectures a priori Progress is encouraging, but…

.1% 1% 10% 100% When will steam engines be 200% efficient? Exponential improvement Note: this is real data!

.1% 1% 10% 50% When will steam engines be 200% efficient? Oops… never.

wasteful fragile robust efficient At best we get one Technology?

wasteful fragile robust efficient Often neither  ??? 

Bad theory?  ???  ? ? Bad architectures? wasteful fragile gap? robust efficient

Case studies wasteful fragile Sharpen hard bounds Hard limit Conservation “laws”?

simple enzyme Fragility Overhead complex enzyme Theorem! z and p functions of enzyme complexity and amount

What reviewers say “The approach to establish universality for all biological and physiological systems is simply wrong. It cannot be done…” “…does not seem to have an understanding or appreciation of the vast diversity of biological and physiological systems…” “… a mathematical scheme without any real connections to biological or medical problems…” “…desire to develop rigorous framework is understandable, but usually this can be done only by imposing a high degree of abstraction, which would then make the model useless …” “While the notion of universality is well justified in physics, it is perhaps not so useful in biological sciences and medicine. To develop a set of universal principles for biological and physiological systems is mostly likely a dream that will never be realized, due to the vast diversity in such systems.”

Glycolytic “circuit” and oscillations End of an old story (why oscillations) – no purpose per se – side effect of hard robustness/efficiency tradeoffs – just needed a theorem Beginning of a new one – robustness/efficiency tradeoffs – complexity and architecture – need more theorems and applications

wasteful fragile efficient robust Hard tradeoffs? Architecture?

TCP IP Physical MAC Switch MAC Pt to Pt Diverse applications Layered architectures

Proceedings of the IEEE, Jan 2007 Chang, Low, Calderbank, and Doyle

TCP IP Physical Diverse applications Too good? Diverse

TCP IP Deconstrained (Hardware) Deconstrained (Applications) Layered architectures Constrained Networks “constraints that deconstrain” (Gerhart and Kirschner)

OS Deconstrained (Hardware) Deconstrained (Applications) Layered architectures Constrained PCs “constraints that deconstrain” (Gerhart and Kirschner)

OS Deconstrained (Hardware) Deconstrained (Applications) Layered architectures Constrained Control, share, virtualize, and manage resources Processing Memory I/O Few global variables Don’t cross layers

TCP/ IP Deconstrained (Hardware) Deconstrained (Applications) Layered architectures Constrained Control, share, virtualize, and manage resources Processing? Memory? I/O Comms Latency? Few global variables? Don’t cross layers?

Catabolism AA Ribosome RNA RNAp transl. Proteins xRNA transc. Precursors Nucl. AA DNA DNAp Repl. Gene ATP Enzymes Building Blocks Shared protocols Deconstrained (diverse) Environments Deconstrained (diverse) Genomes Bacterial biosphere Architecture = Constraints that Deconstrain Layered architectures

Catabolism AA Ribosome RNA RNAp transl. Proteins xRNA transc. Precursors Nucl. AA DNA DNAp Repl. Gene ATP Enzymes Building Blocks Crosslayer autocatalysis Macro-layers Inside every cell almost

Catabolism AA Ribosome RNA RNAp transl. Proteins xRNA transc. Precursors Nucl. AA DNA DNAp Repl. Gene ATP Enzymes Building Blocks Core conserved constraints facilitate tradeoffs Deconstrained phenotype Deconstrained genome What makes the bacterial biosphere so adaptable? Active control of the genome (facilitated variation) Environment Action Layered architecture

This paper aims to bridge progress in neuroscience involving sophisticated quantitative analysis of behavior, including the use of robust control, with other relevant conceptual and theoretical frameworks from systems engineering, systems biology, and mathematics. Doyle and Csete, Proc Nat Acad Sci USA, online JULY

Meta-layers Physiology Organs Prediction Goals Actions errors Actions Cortex Fast, Limited scope Slow, Broad scope Which blue line is longer ? “Seeing is dreaming?” “Seeing is believing?”

sense move Spine delay=death

sense move Spine Reflex Reflect

sense move Spine Reflex Reflect

sense move Spine Reflect Reflex Layered

sense move Spine Reflect Reflex Layered

Physiology Organs Neurons Cortex Cells Cortex Layered architectures Cells

Physiology Organs Meta-layers Prediction Goals Actions errors Actions Cortex

Simulation Seeing is dreaming Conscious perception Conscious perception

Which blue line is longer?

Simulation Seeing is dreaming Conscious perception Conscious perception

Physiology Organs Prediction Goals Actions errors Actions Seeing is believing Conscious perception Prediction Goals Conscious perception Seeing is dreaming

sourcereceiver signaling gene expression metabolism lineage Biological pathways

sourcereceiver control energy materials signaling gene expression metabolism lineage More complex feedback

sourcereceiver control energy materials Physiology Organs Prediction Goals Actions errors Actions Prediction Goals Conscious perception fast

Meta-layers Physiology Organs Prediction Goals Actions errors Actions Cortex Fast, Limited scope Slow, Broad scope Unfortunately, we’re not sure how this all works.

Meta-layers Physiology Organs Prediction Goals Actions errors Actions Cortex Fast, Limited scope Slow, Broad scope Which blue line is longer ? “Seeing is dreaming?” “Seeing is believing?”

Meta-layers Physiology Organs Prediction Goals Actions errors Actions Cortex Fast, Limited scope Slow, Broad scope

Meta-layers Physiology Organs Prediction Goals Actions errors Actions Cortex Fast, Limited scope Slow, Broad scope UAV

Comms Meta-layers Physiology Organs Prediction Goals Actions errors Actions Cortex Fast, Limite d scope Slow, Broad scope Disturbance Plant Remote Sensor Actuator Interface Control Layered architectures

Comms Disturbance Plant Remote Sensor Actuator Interface Control Layered architectures

Comms Disturbance Plant Remote Sensor Actuator Interface Control ? Deconstrained (Hardware) Deconstrained (Applications) Next layered architectures Constrained Control, share, virtualize, and manage resources

Other examples Clothing Lego Money Cell biology

Base Insulation Shell Outfit BodyEnvironment Shirt Slacks Jacket Tie T-Shirt Socks ShoesCoat Shorts

Base Insulation Shell Outfit BodyEnvironment

Garment Outfit BodyEnvironment Complexity  Robustness Layers must be hidden to be robust Choice (management and control) is more complex than assembly Mgmt/ctrl Assembly

Garment Outfit BodyEnvironment

Garment Outfit

Garment Outfit Cloth Thread Fiber Garment Cloth Thread Fiber Garment Cloth Thread Fiber Garment Layering within garments (textiles)

Cloth Thread Fiber Garments

Cloth Thread Fiber Garments Weave Sew Spin Universal strategies? Prevents unraveling of lower layers

Cloth Thread Fiber Garments Xform Universal strategies? Garments have limited access to threads and fibers constraints on cross-layer interactions quantization for robustness Even though garments seem analog/continuous Prevents unraveling of lower layers

Cloth Thread Fiber Garments XformCtrlMgmt Networked, universal, layered XformCtrlMgmt XformCtrlMgmt XformCtrlMgmt Control Supply Complexity?

Fiber Geographically diverse sources Diverse fabric Functionally diverse garments General purpose machines Diverse Thread sew knit, weave spin

OS Deconstrained (Hardware) Deconstrained (Applications) Layered architectures Constrained Control, share, virtualize, and manage resources Processing Memory I/O Few global variables Don’t cross layers Direct access to physical memory?

Catabolism AA Ribosome RNA RNAp transl. Proteins xRNA transc. Precursors Nucl. AA DNA DNAp Repl. Gene ATP Enzymes Building Blocks Shared protocols Deconstrained (diverse) Environments Deconstrained (diverse) Genomes Bacterial biosphere Architecture = Constraints that Deconstrain Few global variables Don’t cross layers

Meta-layers Physiology Organs Prediction Goals Actions errors Actions Cortex Fast, Limited scope Slow, Broad scope Which blue line is longer ? “Seeing is dreaming?” “Seeing is believing?” Few global variables Don’t cross layers

Comms Meta-layers Physiology Organs Prediction Goals Actions errors Actions Cortex Fast, Limite d scope Slow, Broad scope Disturbance Plant Remote Sensor Actuator Interface Control Layered architectures Few global variables Don’t cross layers

Problems with leaky layering Modularity benefits are lost Global variables? Poor portability of applications Insecurity of physical address space Fragile to application crashes No scalability of virtual/real addressing Limits optimization/control by duality?

Fragilities of layering/virtualization Hijacking, parasitism, predation –Universals are vulnerable –Universals are valuable Breakdowns/failures/unintended/… not transparent Hyper-evolvable but with frozen core

TCP/ IP Deconstrained (Hardware) Deconstrained (Applications) Original design challenge? Constrained Trusted end systems Unreliable hardware Facilitated wild evolution Created whole new ecosystem complete opposite

TCP/ IP Deconstrained (Hardware) Deconstrained (Applications) Layered architectures Constrained Control, share, virtualize, and manage resources Processing? Memory? I/O Comms Latency? Few global variables? Don’t cross layers?

App IPC Global and direct access to physical address! Robust? Secure Scalable Verifiable Evolvable Maintainable Designable … DNS IP addresses interfaces (not nodes)

Naming and addressing need to be resolved within layer translated between layers not exposed outside of layer Related “issues” VPNs NATS Firewalls Multihoming Mobility Routing table size Overlays …

? Deconstrained (Hardware) Deconstrained (Applications) Next layered architectures Constrained Control, share, virtualize, and manage resources Comms Memory, storage Latency Processing Cyber-physical Few global variables Don’t cross layers

Every layer has different diverse graphs. Architecture is least graph topology. Architecture facilitates arbitrary graphs. Persistent errors and confusion (“network science”) Physical IP TCP Application

Notices of the AMS, 2009

wasteful fragile slow Good case studies Hard limit  bad  worse Fix bugs “New sciences” of “complexity” and “networks”?

D. Alderson, NPS122

“New sciences” of “complexity” and “networks”? worse Edge of chaos Self-organized criticality Scale-free “networks” Creation “science” Intelligent design Financial engineering Risk management “Merchants of doubt” … Not today Science as Pure fashion Ideology Political Evangelical Nontech trumps tech

IEEE TRANS ON SYSTEMS, MAN, AND CYBERNETICS, JULY 2010, Alderson and Doyle Statistical physics Complex networks edge of chaos, self-organized criticality, scale-free,…

Complex systems? Fragile Scale Dynamics Nonlinearity Nonequlibrium Open Feedback Adaptation Intractability Emergence … Even small amounts can create bewildering complexity

Complex systems? Fragile Scale Dynamics Nonlinearity Nonequlibrium Open Feedback Adaptation Intractability Emergence … Scale Dynamics Nonlinearity Nonequlibrium Open Feedback Adaptation Intractability Emergence … Robust

Complex systems? Resources Controlled Organized Structured Extreme Architected … Robust complexity Scale Dynamics Nonlinearity Nonequlibrium Open Feedback Adaptation Intractability Emergence …

New words Fragile complexity Emergulent Emergulence at the edge of chaocritiplexity Scale Dynamics Nonlinearity Nonequlibrium Open Feedback Adaptation Intractability Emergence …

“New sciences” of complexity and networks Statistical physics Complex networks edge of chaos, self-organized criticality, scale-free,…

IEEE TRANS ON AUTOMATIC CONTROL, FEBRUARY, 2011 Sandberg, Delvenne, and Doyle Stat physics, fluids, QM Complex networks “orthophysics”

J. Fluid Mech (2010) Transition to Turbulence Flow Streamlined Laminar Flow Turbulent Flow Increasing Drag, Fuel/Energy Use and Cost Turbulence and drag?

Physics of Fluids (2011) z x y z x y Flow upflow high-speed region downflow low speed streak Blunted turbulent velocity profile Laminar Turbulent 3D coupling Coherent structures and turbulent drag

wasteful fragile Laminar Turbulent efficient robust Blunted turbulent velocity profile Laminar Turbulent ?

Transition to Turbulence Flow Streamlined Laminar Flow Turbulent Flow Increasing Drag, Fuel/Energy Use and Cost Turbulence and drag? z x y Flow Coherent structures z x y

z x y Blunted turbulent velocity profile Laminar Turbulent “turbulence is a highly nonlinear phenomena”

SmallLarge Robust Simple 2d, linear Organized Computer Fragile chaocritical 3d, nonlinear Irreducibile? Complexity? mildly nonlinear highly nonlinear  Model 

wasteful fragile Laminar Turbulent efficient robust Laminar Turbulent ? Control?

Supplementary materials has a demo. Doyle and Csete, Proc Nat Acad Sci USA, online JULY m M L

Fragility up + eyes Theorem up, no eyes This is a cartoon, but can be made precise. L hopeless down lower focus

u x  m M m M Linearized pendulum on a cart

Easy, even with eyes closed No matter what the length

Time Time Simulation Frequency Sensitivity Function h=3 Simple metabolism without autocatalysis

Gratuitous fragility versus fragile robustness

Time Time Simulation Frequency Sensitivity Function h=1 h=3 h=5 Robust Fragile Simple metabolism without autocatalysis

Up is hard for shorter lengths Down easy, even with eyes closed all lengths

Fragility complex This is a cartoon, but can be made precise. L L Too fragile Why oscillations? Side effects of hard tradeoffs

m M Eyes closed Want r and z large (but p small).

Fragility up + eyes Theorem up, no eyes This is a cartoon, but can be made precise. L hopeless down lower focus