Information Technology and Infrastructure:Information Technology and Infrastructure: Benefits, Costs, and Dependencies Benefits, Costs, and Dependencies
MIRIAM HELLER, Ph.D.
NATO SCIENCE PROGRAMMEin conjunction with the
Carnegie Bosch Institute
ADVANCED RESEARCH WORKSHOP Life Cycle Analysis for Assessing Energy and
Environmental Implications of Information TechnologyBudapest, HungarySeptember 2, 2003
Sept. 2, 2003 - M. Heller ©
MessagesMessages
ICT Confers Benefits To Infrastructure Systems; (Avoided) Costs May Be Easier to Quantify
Infrastructure Systems Differ from Other Manufacturing and Service Systems
Infrastructure Dependencies May Give Way to Indirect Environmental and Energy Consequences, Which Could Figure Into Life Cycle Cost/Benefit Analysis of ICT and Infrastructure System Planning and Management
Sept. 2, 2003 - M. Heller ©
TOPICSTOPICS
Infrastructure Systems
Infrastructure Interdependencies
Benefits and Costs of IT and Infrastructure Systems
Related IT and Infrastructure Research
– Cyber* Futures at NSF
Challenges for Research
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A Definition of Infrastructure SystemsA Definition of Infrastructure Systems
Networks of facilities and institutions
Essential to life, economic well-being, and national security.
Support the flow of people, energy, other resources, goods, information, and basic services
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Critical Infrastructures Critical Infrastructures (PDD 63)(PDD 63)
Potable & Potable & Waste WaterWaste Water
Potable & Potable & Waste WaterWaste Water
Banking & Banking & InsuranceInsurance
Banking & Banking & InsuranceInsurance
GovernmentGovernmentGovernmentGovernment
Emergency Emergency ResponseResponse
Emergency Emergency ResponseResponse
TransportationTransportationTransportationTransportation
Oil & GasOil & GasOil & GasOil & Gas
ElectricityElectricityElectricityElectricity
Telecom-Telecom-municationsmunications
Telecom-Telecom-municationsmunications
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Integrated Information SystemsIntegrated Information Systems
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ICT Benefits for Infrastructure SystemsICT Benefits for Infrastructure Systems
Time
Performanceand
Efficiency
Baseline from Core UtilityProcesses Automated Monitoring, Sensing, Data Acquisition
ProcessProcessControl /Supervision
(Adapted from Heller et al.,1999)
SharedObjectives
Enterprise Architecture
EnterpriseEnterpriseIntegration/ Optimization
Shared Data
Communications Architecture
ProductProductIntegration/Interoperability
IndustrialEcology
CommunityCommunityEco-efficiency/Sustainability
SharedResources /Environment
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Infrastructure Systems: Some ReflectionsInfrastructure Systems: Some Reflections
Differ from Manufacturing Systems– Provide critical services / lifelines– Geographically distributed– One-offs with many degrees of freedom– Highly interconnected – Subject to uncertain and uncontrollable ambient
conditions Life-Cycle Modeling Differences
– Uncertainty• High consequence / low probability events vs. slow
consequence / high probability events• Life-span definition (whole-life)
– Complexity
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TransportationTransportation
Oil & Natural Gas
EELLEECCTTRRIICCIITTYY
Potable & Waste WaterPotable & Waste Water
Emergency ResponseEmergency Response
Government
IITT &&
TTEELLEECCOOMM
Banking & FinanceBanking & Finance
Infrastructure InterdependenciesInfrastructure Interdependencies
Switches, control systems
Storage, pumps, control systems, compressors
e-commerce, IT
Pumps, lifts, control systems
Signalization, switches,control systems
e-government,IT
Medical equipment
Water for cooling, emissions control
Water for production, cooling, emissions control
Fire suppression
Cooling
Fuel transport, shipping
Fuel transport, shipping
Chemicalstransport
Transport of emergency personnel, injured, evacuation
Co
mm
un
i ca
t ion
s
SCADA
SCADA
Trading, transfers
SCADA
Co
mm
un
ica
t ion
s
Location, EM contact
Generator fuels, lubricants
Heat
Fuels, lubricants
Fuels, Heat
Currency (US Treasury; Currency (US Treasury; Federal Reserve )Federal Reserve )
DOE;DOE;DOTDOT
Regulations & enforcement Regulations & enforcement FERC; DOEFERC; DOE
Personnel/Equipment Personnel/Equipment (Military)(Military)
Fin
an
cin
g, re
gu
latio
ns
, & e
nfo
rce
me
nt
Fin
an
cin
g, re
gu
latio
ns
, & e
nfo
rce
me
nt
SEC; IRSSEC; IRS
FEMA; DOTFEMA; DOT
DOTDOT
EPAEPA
Detection, 1st responders, repair
Fin
an
cin
g &
po
licie
sF
ina
nc
ing
& p
olic
ies
Financing & policiesFinancing & policies
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Köningsberg on the Pregel River with 7 bridges.
Cross each bridge exactly once and return to starting position.
In 1736, LeonhardEuler the SwissMathematician idealized this as a system of nodes and arcs.
Euler proved that it cannot be done unless every node is connected to every other with even degree.
Science of Engineered NetworksScience of Engineered Networks
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Random networks, generated by randomly connecting a new node with an existing node, have on average, the same number of connections per node, e.g., National Highway System (Barabási, 2002). Distribution of nodes connections is normal.
Scale-free networks (WWW, air traffic
routes, social networks) arise when new nodes connect preferentially to already well-connected nodes. Most nodes have few connections: a few nodes are heavily connected hubs. Distribution of nodes connections follows a power law.
Science of Engineered Networks:Science of Engineered Networks:DependenciesDependencies
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Power Grid Outages Follow Power LawPower Grid Outages Follow Power Law
104 105 106 10710
-2
10-1
100
101
N= # of customers affected by outage
US Power outages1984-1997
August 10, 1996
Fre
quen
cy (
per
year
) of
out
ages
> N
Data from NERC
(Amin, 9/10/01)
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ICT Impacts Infrastructure SystemsICT Impacts Infrastructure SystemsExample: 2001 California Power CrisisExample: 2001 California Power Crisis
Disrupted fuel production, refining, and distribution, sometimes cut off fuel supplies to the very plants that should have been generating their electricity
Interrupted water distribution affected the state's agribusiness
Soaring wholesale power prices impacts rippled through the region, leading to relaxation of salmon-protection and air-quality regulations and shutdown of aluminum mills in Washington state. Idaho farmers curtailed potato production to exploit Idaho Power Company's electricity buy-back program
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Coupled Systems Frameworks : Coupled Systems Frameworks : Rinaldi et al., 2001Rinaldi et al., 2001
Type of Type of FailureFailure
Infrastructure Infrastructure CharacteristicsCharacteristics
State of State of OperationOperation
Types of Types of InterdependenciesInterdependenciesEnvironmentEnvironment
Coupling/Coupling/ResponseResponseBehaviorBehavior
Loo
se/T
ight
Lin
ear/
Com
plex
Esc
alat
ing
C
asca
ding
Com
mon
Cau
se
Spatial
Temporal
Operational
Organizational
Economic
Legal/
Regulatory
Technical
Social/
Political
Physical
Cyber
Logical
Geographic
Ada
ptiv
e
Infle
xibl
e
Stressed/
Disrupted
Repair/
Restoration
Norm
al
Business Public Policy
Security Health/ Safety
NaturalNaturalEnvironment ?Environment ?
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State of the Water/Wastewater SystemState of the Water/Wastewater System
Size– 15,000 Publicly-Owned Wastewater Treatment Plants– 100,000 Pumping Stations– 160,000 Public Potable Water Systems
Operations– Accounts for 3-7% Total US Electricity Consumption– ASCE Estimates $12 Billion Needed for Maintenance
2012
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ICT Benefits for Water/Wastewater SystemsICT Benefits for Water/Wastewater Systems
Time
Performanceand
Efficiency
Baseline from Core UtilityProcesses
(Adapted from Heller et al.,1999)
SharedObjectives
Utility Business Architecture
UtilityUtilityIntegration/ Optimization
Shared Data
Utility Communications Architecture
PlantPlantIntegration/Interoperability
Automated Monitoring, Sensing, Data Acquisition
ProcessProcessControl /Supervision
Process Level IT (SCADA, GIS, EMS, CIS, MMS, LIMS, hydraulic, water quality, and distribution network models Reduced Chemical and Energy Consumption, Lower Operating Costs, Improved Regulatory Compliance, Higher Reliability, and Improved Customer Service, Inventory Control, and Maintenance Management
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Harnassing Complexity through Shared ResourcesHarnassing Complexity through Shared ResourcesEnergy and Water Quality Management Systems (Jentgen, 2001)Energy and Water Quality Management Systems (Jentgen, 2001)
Energy Cost Energy Cost SchedulerScheduler
(Electric Utility)(Electric Utility)
Energy Cost Energy Cost SchedulerScheduler
(Electric Utility)(Electric Utility)
OperationsOperationsOperationsOperations
Water Water Quality Quality
AnalyzerAnalyzer
Water Water Quality Quality
AnalyzerAnalyzer
Water Water Source Source
AnalyzerAnalyzer
Water Water Source Source
AnalyzerAnalyzer
Raw Water Raw Water Supply/ Water Supply/ Water
Treatment PlantTreatment Plant
Raw Water Raw Water Supply/ Water Supply/ Water
Treatment PlantTreatment Plant
Pump StationsPump StationsPump StationsPump Stations
Wastewater Wastewater Treatment PlantTreatment Plant
Wastewater Wastewater Treatment PlantTreatment Plant
DistributionDistributionDistributionDistribution
CustomerCustomerCustomerCustomer
CollectionCollectionCollectionCollection
Consumption Consumption Forecast Forecast ProgramProgram
Consumption Consumption Forecast Forecast ProgramProgram
Automated Automated Maintenance Maintenance Management Management
SystemSystem
Automated Automated Maintenance Maintenance Management Management
SystemSystem
Water Consumption Forecast
Management Scheduler
Clearance Approvals
System Operating
Plan
Schedule & Control
Operating Plan
Clearance Work Orders
Water LawWater Rights
Water Priorities
Performance Criteria
HydroSchedule
EnergyCost
Schedule
InterruptionScheduler
Signal
Operations Planner & SchedulerOperations Planner & Scheduler
System Scheduler:System Scheduler:Surface Water Treatment PlantSurface Water Treatment PlantPump StationsPump StationsDistributionDistributionCustomerCustomerCollectionCollectionWastewater TreatmentWastewater Treatment
Operations Planner & SchedulerOperations Planner & Scheduler
System Scheduler:System Scheduler:Surface Water Treatment PlantSurface Water Treatment PlantPump StationsPump StationsDistributionDistributionCustomerCustomerCollectionCollectionWastewater TreatmentWastewater Treatment
Water ResourceSchedule/Constraints
Water QualityAlarms
SCADAData
Water QualityOperating
Constraints
Water QualityData
Utility’s Historical Operating DataPerformance Criteria
Lab & FieldSamples
Operating Plan
Regulations
Power SupplyContract Terms/Conditions
Power Suppliers’Price Schedule
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Potential ICT Benefits for Water/WastewaterPotential ICT Benefits for Water/Wastewater
SharedResources /Environment
Shared Data
Time
Performanceand
EfficiencyShared
Objectives
Baseline from Core UtilityProcesses Automated Monitoring, Sensing, Data Acquisition
Utility Communications Architecture
ProcessProcess PlantPlant Utility/FacilityUtility/FacilityControl / Integration/ Integration/ Supervision Interoperability Optimization
Utility Business Architecture
(Adapted from Heller et al.,1999)
Industrial Ecology
RegionalRegionalEco-efficiency/Sustainability
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Industrial Symbiosis Example:Industrial Symbiosis Example:Baytown’s Water Infrastructure Baytown’s Water Infrastructure (Nobel & Allen, 1998)(Nobel & Allen, 1998)
21 process, 5 utility streams 75 feasible reuse pathways identified
#####
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Linear Program Linear Program FormulationFormulation
I2
GC
WTP WWTP
I1
I3 Fresh
Reclaimed
Reused
Disposed
Exchange Feasibility Based on water quality parameters
(e.g., TOC, TSS, TDS) Creates input for cost optimization
– feasible exchange pathways, i.e., “arcs”– “type” of water– transportation costs
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Industrial Symbiosis: Optimal Water UseIndustrial Symbiosis: Optimal Water Use (Nobel & Allen, 1998) (Nobel & Allen, 1998)
MetricsScenario mgd % $/day % Base Case 8.71 - 108,554 -Minimum Cost 1.05 -88% 57,165 -47%Minimum Fresh Water 0.26 -97% 85,098 -22%
Fresh WaterUsage
Cost
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ICT Benefits for Oil and Gas Infrastructure ICT Benefits for Oil and Gas Infrastructure Example: BP’s Texas City PlantExample: BP’s Texas City Plant
“Project Future” (Bylinsky, Fortune, “Elite Factories,” 9/1/2003)
– Combined Refinery / Petrochemical Plant – $30 bbl Oil $60 of Gasoline, Diesel, Jet Fuel, p-Xylene– 2,740 Employees– 2-year, $75 Million Investment in Computerization and Automation
of 650 Key Valves
Returns On Investment– Start-up Time Reduced from 2 Weeks to 3.5 Days– Real-Time Equipment Setpoints Based on Ambient Temperature,
Weather, and Product Prices– 3% Less Electricity Used– 10% Less Natural Gas Used – 55% Increase in Productivity }$ Millions and
Tons GHG Saved
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State of Oil and Gas Infrastructure SystemsState of Oil and Gas Infrastructure Systems
Size– Ports, Refineries, Transportation– 2,000 Petroleum Terminals– Almost 1 Million Wells– 2,000,000 Miles of Oil Pipelines– 1,300,000 Miles of Gas Pipelines and Increasing
Operations– Pipeline and Distribution System
• Leak Detection• Monitoring and Control Systems• More Efficient Use of Existing Pipe• Aging
Coupled Economic Models on Natural Gas and Electric Power
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State of the Transportation SystemState of the Transportation System
Size– 125,000 Miles of National Highway System– 25,000 Miles of Public Roads– 3.76 Million Miles of Other Roads
Operations– FHWA : > $78 Billion / Year Idled Away in Congestion– 50% Total US Petroleum Consumed by Highway
Vehicles– > 1/3 GHG Due to Surface Transportation– Major Source of Photochemical Smog and Other Air
Pollution– > 40,000 Fatalities / Year Over Past Decade
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Potential ICT Benefits for TransportationPotential ICT Benefits for Transportation
Inform on-line buyers of environmental impacts of shipping options (NAE, 1994; Hawken et al., 1999; Sui & Rejeski, 2002)
– Ship or rail: 400-500 BTU/ton-mile– Truck : >2000 BTU/ton-mile– Air freight : > 14,000 BTU/ton-mile
Reduce Travel: Telework, Telecommute, Teleconference, Virtual Tradeshows
Improve Urban Planning and Policy regarding– Land use– Environmental quality– Social equity– Infrastructure operations and maintenance
Increase On-Board Traveler Productivity
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Potential ICT Benefits for TransportationPotential ICT Benefits for Transportation
Advanced Traveler Information Systems (Real-time) Influence on Traveler Behavior and Improved Traffic Models
Intelligent Computer Vision Enhanced Traffic Modeling Improved Traffic Models & Collision Avoidance
Real-time Emissions Monitoring Coupled Traffic and Air Quality Models
Wireless Communications Networks Improved Data Acquisition, Data Management, and Traffic Control
Congestion Pricing Control Demand En-route Commerce Optimize Supply Optimal and/or Dynamic Routing Intermodal Models Improved Transportation Models
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State of the Electric Power GridState of the Electric Power Grid Size
– ~200,000 Miles of Transmission Lines– 5000 Power Plants, 800,000
Megawatts
Transmission level (meshed network of extra high voltage, > 300 kV, &
high voltage, 100-300 kV, connected to large generation units and very large
customers; tie-lines to transmission networks, and to sub-transmission level)
Sub-transmission level (radial or weakly coupled network with some high
voltage, 100-300 kV, but typically only 5-15 kV, connected to large customers
and medium sized generators)
Distribution level (tree network of low voltage, 110-115 or 220-240 volts,
and medium voltage, 1-100 kV, connected to small generators, medium- sized
customers, and to local low-voltage networks for small customers)
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Urbanization load growth– 2.1+ % annual national growth over
last 25-years result in a 50% increase by 2014 - 2020
State of the Electric Power GridState of the Electric Power Grid
Nearly no new HV transmission lines in last 25 years 1988-98, 30% growth in total U.S. electricity demand is met with
transmission network growth of 15%
– Re-regulation with privatization
– Uncertainty ROIs
– NIMBY
– Right-of-way restrictions for T&D expansion
– Tightening fuel supplies to meet increased demand
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State of the Electric Power GridState of the Electric Power Grid
Operations– 8/15/03 blackout affected > 20
millions of people, water supply, wastewater conveyance, transportation, communications, hospitals, banking, and retail sales• ICT safety equipment tripped to protect power plants and contain the outage causing
cascading failures• 9 nuclear power plants automatically powered down safely
– EPRI : $1.5 billion for July-Aug 1996 power blackouts
– CEIDS : $119 billion / year in power quality disruptions
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Potential ICT Benefits for Electric PowerPotential ICT Benefits for Electric Power EPRI/DoD Complex Interactive Networks Initiative
Goal: Develop tools that enable secure, robust and reliable operation of interdependent infrastructures with distributed intelligence and self-healing abilities
Systems’ approach to complex networks: advancing mathematical and system-theoretic foundations
– Target theoretical and applied results for increased dynamic network reliability and efficiency
– Identify, characterize, and quantify failure mechanisms
– Understand interdependencies, coupling and cascading
– Develop predictive models
– Develop prescriptive procedures and control strategies for mitigation or/and elimination of failures
– Design self-healing and adaptive architectures
– Trade-off between robustness and efficiency
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““The best minds in electricity R&D The best minds in electricity R&D have a plan: have a plan: Every node in the Every node in the power network of the future will be power network of the future will be awake, responsive, adaptive, price-awake, responsive, adaptive, price-smart, eco-sensitive, real-time, smart, eco-sensitive, real-time, flexible, humming - and flexible, humming - and interconnected with everything interconnected with everything elseelse.”.” —Wired Magazine, July 2001http://www.wired.com/wired/archive/9.07/juice.html
The Energy Web: The Energy Web: “…a network of technologies and services that provide illumination…”
From M. Amin, 2001
Sept. 2, 2003 - M. Heller ©
Enabling ICT for Electric InfrastructureEnabling ICT for Electric Infrastructure
Materials: Superconductors and wide bandgap semiconductors
Monitoring: WAMS, OASIS, SCADA, EMS
Analysis: DSA/VSA, PSA, ATC, CIM, TRACE, OTS, ROPES,
TRELSS, market/risk assessment Control: FACTS; Fault Current Limiters (FCL)
Distributed resources: Fuel cells, photovoltaics, Superconducting
Magnetic Energy Storage (SMES) Next generation: integrated sensor; 2-way communication;
"intelligent agent" functions: assessment, decision, learning; actuation, enabled by advances in semiconductor manufacturing
From M. Amin, 2001
Sept. 2, 2003 - M. Heller ©
Intelligent Adaptive IslandingIntelligent Adaptive Islanding
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From M. Amin, 2001
Sept. 2, 2003 - M. Heller ©
System Risk is a Function of System Risk is a Function of System StateSystem State
P(Ht,s) = probability of a hazard at time t (and system state s)
P(Ds|Ht,s) = probability of a particular level of vulnerability of a system in state s given a hazard at time
t (and system state s)
E(L|Ds) = expected losses conditioned on the vulnerability of system in state s
E(L) = E(L|ds) * P(ds|ht,s) * P(ht,s) ht,s ds
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Life-Cycle Infrastructure Asset ManagementLife-Cycle Infrastructure Asset Management
Life-Cycle Design
Emergency Response, Diagnosis
Multi-Objective Multi-Objective Multi-stakeholder Multi-stakeholder Decision-MakingDecision-Making
Multi-Objective Multi-Objective Multi-stakeholder Multi-stakeholder Decision-MakingDecision-Making
Life-Cycle Analysis– Internal, Direct Impacts
– External, Indirect Impacts
– Systems Evaluation
Predictive Maintenance, Sensing, Monitoring, Data (Storage, Transmission, Retrieval)
Modeling, Simulation,
Recovery, Corrective Maintenance, Deconstruction,Reuse
Detection, Preventive Maintenance, Lifetime Extension, Early Warning
Social/ Social/ Cultural Cultural ValuesValues
Social/ Social/ Cultural Cultural ValuesValues
Policy/ Policy/ LawLawPolicy/ Policy/ LawLaw
Financial/ Financial/ Insurance Insurance InstrumentsInstruments
Financial/ Financial/ Insurance Insurance InstrumentsInstruments
Organizational Organizational TheoryTheory
Organizational Organizational TheoryTheory
CommunicationCommunication/ Education/ EducationCommunicationCommunication/ Education/ Education
Prediction
Planning, Training and Preparedness
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Multi-Objective Multi-stakeholder Multi-Objective Multi-stakeholder Decision-MakingDecision-Making
Allocation problem over various investment options, over various stages of development (R&D, development, implementation) over time with risk/uncertainty
Multiple objectives : efficiency, reliability, security, resiliency, sustainability
1
2
3B/C ( S&M)
B/C (ER)
1 ~ 2 ~ 3 : indifferent wrt ER
1 is infeasible wrt obj. S&M
2 >> 3 : 2 dominates 3
Multiple stakeholders : different institutional boundaries, missions, resources, timetables, and agendas
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Challenges for Research in Life-Cycle Challenges for Research in Life-Cycle Analysis of IT and InfrastructureAnalysis of IT and Infrastructure
Critical Infrastructure Inventory Data– Scalable Environmental Knowledge Architecture
Models of Individual Infrastructure Systems Models of Coupled Infrastructure Systems System Response and Resiliency
– System state /vulnerability analysis– Consequence models (boundaries, data, methods)– Extreme value statistics– Substitute services / alternate pathways
Measures of Network Performance Life-Cycle Infrastructure Asset Management Modeling
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““CyberInfrastructure” VisionCyberInfrastructure” Vision “Atkins report”
– Blue-ribbon panel, chaired by Daniel E. Atkins
Calls for a national-level, integrated system of hardware, software, & data resources and services
New infrastructure to enable new paradigms of scientific/ engineering research and education
http://www.cise.nsf.gov/evnt/reports/toc.htm
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What CyberInfrastructure MeansWhat CyberInfrastructure Means Infrastructure that enables distributed, reliable, real-
time collaboration and analysis requiring large-scale, dynamic information storage and access
Examples of components to be integrated:– Major computational processing capabilities– Unique experimental facilities– High-speed networks– Tele-participation and tele-operation tools– Networks of data collection devices– Data/metadata storage and curation– Data analysis and information extraction tools– Universal access
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What Makes CyberInfrastructure UniqueWhat Makes CyberInfrastructure Unique Cyberinfrastructure : more than the sum of its component
parts – the key is integration
CyberInfrastructure isn’t just… Unless it also involves…
Individual infrastructure components (e.g., devices that collect data, data mining as a science, or big computing resources)
Playing an integrative role in a larger system
Sharing distributed data across research groups or disciplines
Transforming data into meaningful information
Data and resources that are collected, processed, and used by a community
Distributing collection, storage and access across multiple locations and communities
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Examples of Early CyberInfrastructureExamples of Early CyberInfrastructure George E. Brown, Jr. Network for Earthquake Engineering
Simulation (NEES) Extends national capacity for earthquake engineering through
unique, shared infrastructure What makes NEES CyberInfrastructure?
– Real-time video & data enable participation from remote sites– Real-time communications allow experiments to span facilities, link
physical experiments with numerical simulation– 15 experimental facilities linked by common network, data
repository, tools,
metadata
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Examples: NEES’s Distributed Users and Examples: NEES’s Distributed Users and Distributed ResourcesDistributed Resources
Unique LaboratoryFacilitiesEquipment
Site 1
EquipmentSite 2
EquipmentSite 3
EquipmentSite 15
. .
.
OtherSite A
OtherSite B
Practitioners
EmergencyCommunities
K-14Education
UserCommunities
Earth.Eng.ResearchersData Repositories &
Computational Resources
NEESConsortium
NEESgrid
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Other NSF ICT-Relevant ProgramsOther NSF ICT-Relevant Programs
CLEANER Small Planning Grants– Nick Clesceri, BES,
Sensors and Senor Networks– Shih-Chi Liu, CMS, [email protected]
Information Technology Research Cybertrust and Cybersecurity
Sept. 2, 2003 - M. Heller ©
Thank You For Your Attention !Thank You For Your Attention !
MIRIAM HELLER, Ph.D.Infrastructure & Information Systems
Program Director
National Science Foundation
Tel: +1.703.292.7025 Email: [email protected]