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Designing Ultra Large Scale Systems- The LIST* Approach

Navneet Bhushan & Karthikeyan Iyer

Crafitti Consulting

Oct 17, 2008

* Lean Inventive Systems Thinking

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More is Different – Scale is the New Frontier - I

Google’s Custom Built Server FarmsCurrent estimates put Google's server farm at around 450,000 machines - and they're still custom built, commodity-class x86 PCs, just like they were in 1999

Oct 17, 2008

We Are Building Bigger and Bigger Systems

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Oct 17, 2008

The Internet Capillary networkInter-disciplinary collaborations

High School Friendships

Complex system design diagram

More is Different – Scale is the New Frontier - II

Systems are Evolving into Bigger Systems

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More is Different – Scale is the New Frontier - III

“The ability to reduce everything to simple fundamental laws does not imply the ability to start from those laws and reconstruct the universe” Anderson, P.W., More is Different,

Science, Vol. 177, No. 4047, Aug. 4, 1972, pp. 393-396.

Oct 17, 2008

Scale Changes Everything!

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More is Different – Scale is the New Frontier - IV

Oct 17, 2008

“The older is not always a reliable model for the newer, the smaller for the larger, or the simpler for the more complex…Making something greater than any existing thing necessarily involves going beyond experience.”Henry Petroski, Pushing the Limits: New Adventures in Engineering

Scale is not a linear extrapolation!

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SEI ULS Study – 2006!

Oct 17, 2008

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Why we don’t know how to Design ULSS?

Oct 17, 2008

System Design - Present ApproachesAll conflicts must be resolved centrally and uniformly

Requirements can be known in advance and change slowly.

Tradeoff decisions will be stable.

Discrete Time System improvements

Effect of a change can be predicted sufficiently well.

Configuration information

Components and users are fairly homogeneous.

People are just users of the system.

Collective behavior of people is not of interest.

Social interactions are not relevant.

Failures will occur infrequently. Defects can be removed.

A prime contractor is responsible for system development,

operation, and evolution.

ULS CharacteristicsDecentralized Control

Inherently conflicting, unknowable,

and diverse requirements

Continuous evolution and

deployment

Heterogeneous, inconsistent, and

changing elements

Erosion of the people/system

boundary

Normal Failures

New paradigms for acquisition and

policy

?

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ULSS Research Areas

Oct 17, 2008

ULS Systems

Research Area

Specific Sub-Areas

Human Interaction

• Context-Aware Assistive computing

• Understanding Users and Their Contexts

• Modeling Users and User Communities

• Fostering Non-Competitive Social

Collaboration

• Longevity

Computational

Emergence

• Algorithmic Mechanism Design

• Metaheuristics in Software Engineering

• Digital Evolution

Design

• Design of All Levels

• Design Spaces and Design rules

• Harnessing Economics to Promote Good

Design

• Design Representation and Analysis

• Assimilation

• Determining and Managing

Requirements

Computational

Engineering

• Expressive Representation Languages

• Scaled-Up Specification, Verification, and

Certification

• Computational Engineering for Analysis

and Design

Adaptive

System

Infrastructure

• Decentralized Production Management

• View-Based Evolution

• Evolutionary Configuration and

Deployment

• In Situ Control and Adaptation

Adaptable and

Predictable

System Quality

• Robustness, Adaptation, and Quality

Attributes

• Scale and Composition of Quality

Attributes

• Understanding People-Centric Quality

Attributes

• Enforcing Quality Requirements

• Security, Trust, and Resiliency

• Engineering Management at Ultra-

Large Scales

Policy,

Acquisition,

and

Management

• Policy Definition for ULS Systems

• Fast Acquisition for ULS Systems

• Management of ULS Systems

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LEAN INVENTIVE SYSTEMS THINKING (LIST)

Oct 17, 2008

CLASSICAL REDUCTIONISM

Analysis, Determinism,

Dualism, Correspondence

theory of knowledge,

Rationality, Artificial

THE LIST

Learning, Discovery, Design,

Evolutionary, Experimental,

Integrative, Holistic, Non-

linear, Natural

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Elements of System Design

Oct 17, 2008

Designing ULS Systems

Needs

Function

Structure

Behavior

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Designing for Complex Needs

Oct 17, 2008

01234Sight

Sound

Smell

Taste

Touch

Linguistic

Musical

Logical

Spatial

Kinesthetic

Intra-…

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Powerful Functional Design – TRIZ approach

• Eliminate System Contradictions

• Move to a higher level along proven lines of system evolution

• Ideal Final Result

Multiple design alternatives and

paths (Which one to choose?)

Oct 17, 2008

Improving parameter

Worsening parameter

Increasing dynamism (flexibility)

Transition to higher level systems

Transition to micro level systems

Completeness (reducing human involvement)

Shortening of energy flow path

Increasing controllability

Harmonization of rhythms

Non-uniform evolution of sub-systems

Ideality Quotient =Benefits

(Cost + Harmful Effects)

TRIZ: Theory of Inventive Problem Solving

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Structure – Complexity and Centrality

Oct 17, 2008

Flexibility, Adaptability, Ability to evolve, change

Stability, Rigidity, Strength, Productivity, Efficiency

Stability - They are elements where the most critical functions are performed and cannot afford to fail

Unpredictability – They are not very well understood and are unpredictable, hence they are deliberately operating within strict constraints

Dependency – Too many other system elements are dependent on this element, hence it cannot be changed very easily and without pain

Insulation – They are not very well connected and therefore do not have an incentive to change or adapt to changes

Efficiency – The elements are optimally structured to perform certain functions as efficiently as possible

Why are structures rigid?

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System Behavior

• Behavior of the “whole” as opposed to the “parts”

• Need for observation from a different plane

• Complex non-linear systems display macro behavior invisible when seen from inside the system

– Synchronization

– Chaos

– Balance

Oct 17, 2008

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System Behavior –The tendency to synchronize

• Synchronization aids stability –centralized control difficult in complex non-linear systems

• Synchronization is learnt over time; complex non-linear systems need to be designed as “learning systems”

• Systemic synchronization is a result of distributed intelligence

• Synchronization follows simple rules at the sub-system level

• Synchronization happens around system rhythms or clocks

• Synchronization happens for a reason (beneficial outcome)

Oct 17, 2008

Arrhythmia and cessation

of breath

Child rhythm

of breath

Toy rhythm

of breath

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System Behavior - Designing for Chaos

• Chaotic systems hide certain patterns of behavior called attractors.

• Complex non-linear systems display chaotic behavior and gravitate towards system attractors

• Attractors manifest across scale

• Attractors act as strong central rhythms or clocks.

• Strange Attractors

Oct 17, 2008

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Design – A Macro“Balancing” act

Air

Distribution, change

Fire

Fuel, Energy to run the system

Water

Vitality, Life, Growth - Ideas

Earth

Structure and raw material

Complex ULS System

Oct 17, 2008

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The “Typical”Design Process

Oct 17, 2008

Always Reaching Local Optima

Creates a false sense of simplification of complexity

Introduces artificial delay

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The Lean Design Approach –Set-Based Concurrent Engineering

Search for global optima

Elimination of the weakest

Slow convergence

Emergent design

Scope to incorporate systems thinking (needs, functions, structure and behavior) and inventive thinking (TRIZ)

Oct 17, 2008

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The Design Process and the LIST framework

Oct 17, 2008

Mapping the

Design Space

Describe user needs

In case of multiple needs carry out needs

interdependency analysis

Find out key functions to be performed

Understand structural complexities

Understand behavioral complexities

Function dependency analysis to find out

interdependencies

Can some high level functions specific to

strengths of different teams be identified

Let each team explore the specifications,

needs, functions independent of each

other

Each team explore design tradeoffs

through simulations and their past

observations

Each team should come up with their sets

of different solutions within the functional

and performance needs of the product

• Problem Formulation and Analysis• Value Stream• Ideal Final Result (IFR)• Why-what hierarchy• Nine windows• Dependency Structure Matrix (DSM) • Function/Attribute Analysis• System Complexity Estimator (SCE)• S curve analysis• Vedic Inventive Principles• Contradictions – Technical/Physical• Trends of evolution

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Design Process and LIST continued . . .

Oct 17, 2008

Striving for Conceptual

Robustness

(Functional Team level)

Design should remain functional

after variations in its

environment

Vulnerability of system to

changes in the environment

should be minimized

Modularized Design with

standard components

IFR

AFD/Subversion Analysis

Robust Inventive System Design (RISD)

DSM

Integration by

Intersection

(System level)

How are the parts integrated to

meet at the point that will be

regarded best solution

Find out overlap of feasible

design spaces for each sub

component

Decisions about eliminating the

weak designs

Decision Dependency Matrices (DDM)

Analytic Hierarchy Process (AHP)

Technical Contradictions / Inventive

Principles

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Design Process and LIST continued . . .

Oct 17, 2008

Establish Feasibility

before

Commitment

Multiple concepts developed using

prototyping simulation

The infeasible ones will be rejected rest all

will continue to be developed

Decision theoretic principles

AHP

Closer to IFR

Conflict Handling Cooperative Conflict handling Which solution is closer to IFR?

DDM

AHP

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Final Points

• Scale is the New Frontier – it changes everything!

• Existing approaches found insufficient for designing Ultra Large Scale Systems

• Need for designing learning, discovery, human-machine cohesiveness and failure absorption inside the ULSS

• We propose a new framework combining elements of ancient wisdom, modern complexity science, empirical theory of invention, practical experiences of striving excellence and holistic design principles

• Lean Inventive Systems Thinking (LIST) may help us to bridge the gap between current approaches and needs of ULSS

Oct 17, 2008

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THANK YOU!

Oct 17, 2008

Lean Inventive Systems Thinking

Crafitti ConsultingCrafting innovation together . . .

www.crafitti.com

Navneet Bhushan (navneet.bhushan@crafitti.com)

Karthikeyan Iyer (karthikeyan.iyer@crafitti.com)