la modellazione delle reti complesse: il grand canyon tra ricerca e realtà sandro bologna enea –...
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La Modellazione delle Reti Complesse: il Grand Canyon tra Ricerca e Realtà
La Modellazione delle Reti Complesse: il Grand Canyon tra Ricerca e Realtà
Sandro Bologna
ENEA – CAMO
CR Casaccia, 00060 Roma
Sandro Bologna
ENEA – CAMO
CR Casaccia, 00060 Roma
I Giovedi della CulturaENEA-Casaccia, Aprile 29, 2004
Examples of Large Complex Critical Infrastructures
– Energy (oil & gas production and storage, electric power, …)
– Finance & Banking
– Information & Communication
– Transportation (road, airlines, boat, train, …)
– Vital Human Services (water, food, health)
– Government
the italian high-voltage transmission line (380 kv) with 127 nodes and 342 edges
The UCTE System:
2100 Twh delivered to 400 ML people
UNION FOR THE CO-ORDINATION OF TRANSMISSION OF ELECTRICITY
Fonte: Corriere della Sera 30.09.03
ELECTRICAL SYSTEM NETWORK
WaterWaterBanking andBanking and
FinanceFinance
TransportationTransportationInternetInternetCoreCore
InternetInternetCoreCore
TelecommunicationsTelecommunications
GovernmentGovernmentServicesServices
Emergency Emergency ServicesServices
ElectricElectric
Any Geographical Area, Any Network, Any Functional Area Is a Place of Vulnerability
7
Oil and GasOil and Gas
The World is a Network of Networks…The World is a Network of Networks…
REPRESENTATION OF THE DIFFERENT LAYERS THAT MAKE A COMPLEX INTERACTIVE NETWORK
- human organization node (Social Network)
- physical network node (Technological Network)
- control & information flows network node (Information Network)
Physical LayerPhysical Layer(Material Network)(Material Network)
Cyber-LayerCyber-Layer(Information Network)(Information Network)
Organisational Layer Organisational Layer (Human Network)(Human Network)
Intra-dependency
Inter-dependency
LCCI three layer ModelLCCI three layer Model
Electrical Components:Electrical Components:generators, transformers, breakers,generators, transformers, breakers,connecting cables etcconnecting cables etc
Control and supervisory hardware/software components
(Scada/EMS systems)
Electrical Power OperatorsIndependent System Operator
for electricity planning and transmission
Intra-dependency
Inter-dependency
Electrical Infrastructure Interdependencies
Electrical Infrastructure Interdependencies
Electrical Power Transmission Infrastructure
Telecomunication Infrastructure
Oil/Gas Transport System Infrastructure
CyberCyber
LayerLayer
Organisational Organisational LayerLayer
Intra-dependency
Inter-dependency
WHY SO DIFFICULT TO MODEL
Physical Physical
LayerLayer
Structural Complexity
Network Evolution
Node Diversity
Connection Diversity
Dynamical complexity
US CANADA BLACK-OUTPower System Outage Task Force Interim Report
Oil
Electric
Power
Transpor-tation
NaturalGas
Telecom
Fuels, Lubricants
Fuel TransportShipping
Power for pumpingStations, StorageControl Systems
Fuel for Generators,,Lubricants
Fuels, Lubricants
Fuel for Generators,
Water
Water forProduction
CoolingEmission reduction
Power for Pump& Lift Stations
Control Systems
Water for Cooling,Emission reduction
Water for Cooling,
SCADACommunications
SCADACommunications
Power for Switchers
Fuel TransportShipping
Power for compressorsStorage, Control Systems
SCADACommunications
Power for Signalling, Switchers
Fuel for Generators,
Transportation
SCADACommunications
Transpor-tation
Heat
Source:“Critic. Infrastruct Dependencies”
Rinaldi, Peerenboom,Kelly2002
Example of Networked Infrastructures Interdependencies
ENEA FaMoS – Multilayer Modelling Activities ENEA FaMoS – Multilayer Modelling Activities
Topology Model and Topology Model and AnalysisAnalysis
nodes and arcs in the netnodes and arcs in the net
State Machine Model and Analysis
processes and links in the netprocesses and links in the net
Electricity Network
Telecomunication Network
Transportation Network
Oil/Gas Network
Interdependency Model Interdependency Model and Simulationand Simulation
all the links with the other netsall the links with the other nets
Physical Model and Simulation
generators, transformers, breakers,generators, transformers, breakers,connecting cables etcconnecting cables etc
Dynamic Model and Analysisprocesses and links in the netprocesses and links in the net
ENEA FaMoS – Multilayer Modelling Activities ENEA FaMoS – Multilayer Modelling Activities
Topology Model and Topology Model and AnalysisAnalysis
nodes and arcs in the netnodes and arcs in the net
State Machine Model and Analysis
processes and links in the netprocesses and links in the net
ElectricityNetwork
TelecomunicationNetwork
Transportation Network
Oil/Gas Network
Interdependency Model Interdependency Model and Simulationand Simulation
all the links with the other netsall the links with the other nets
Physical Model and Simulation
generators, transformers, breakers,generators, transformers, breakers,connecting cables etcconnecting cables etc
Dynamic Model and Analysisprocesses and links in the netprocesses and links in the net
will make use of the latest results on complex systems theory to analyse the network’s property and to understand the emergent
behaviors that can take place in the network
COMPLEX SYSTEMS APPROACHRecent researches on large-scale networks make evident of some global
properties which are not pre-specified by network design and are difficult or impossible to predict from knowledge of its constituent parts.
(Barabasi, Strogatz, Watts,…)
Poisson distribution
Random Network
Power-law distribution
Scale-free Network
A case study: the italian high-voltage transmission line (380 kv) with 127 nodes and 342 edges
The complex systems view of these networks might reveal interesting features useful for: a) predicting outage events b) reduce vulnerabilities c) increase self-healing control strategies
Pure 2-dimensional networks are less “theoretically interesting” as geometrical constraints inhibit the occurrence of nodes with large degrees. They show single-scale structure with even gaussian-type decay (PNAS 97 (2000) 11149).
Cumulative degree distribution P(k>K)
The analisys of the node’s centrality allows to identify sites where there is a maximum flow. This informations could be used into network’s design toolsets, with the aim of increasing network’s homogeneity in the node’s workflow.
Betweenneess centrality distribution
(bc is the # of shortest paths passing through a node)
Min-cut decomposition of networks (provided by Laplacian spectral analysis) is a useful tool for locating possible sites of vulnerabilities and/or overload. (Rosato et al., Europhys.Lett. to appear)
Present limitations of Complex Systems approach
Given a network with N nodes and L links
Create a graph with statistically identical topology
RESULT: model the static network topology
PROBLEM: Real networks are dynamical systems!
Evolving networksOBJECTIVE: capture the network dynamics
METHOD :• identify the processes that contribute to the network topology
•develop dynamical models that capture these processes
Network as a static graph
ENEA FaMoS – Multilayer Modelling Activities ENEA FaMoS – Multilayer Modelling Activities
Topology Model and Topology Model and AnalysisAnalysis
nodes and arcs in the netnodes and arcs in the net
State Machine Model and Analysis
processes and links in the netprocesses and links in the net
Electricity Network
Telecomunication Network
Transportation Network
Foreign Electrical Transmission Infrastructure
Interdependency Model Interdependency Model and Simulationand Simulation
all the links with the other netsall the links with the other nets
Physical Model and Simulation
generators, transformers, breakers,generators, transformers, breakers,connecting cables etcconnecting cables etc
Dynamic Model and Analysisprocesses and links in the netprocesses and links in the net
will make use of complementary risk assessment methods to estimate the probability of unwanted
incident that may lead to undesired states
Modelling tools for dependability analysis
Model checking
Extended Petri Nets
Fault Tree
Bayesian networks
Model Checking
Given: a System S with initial state <s1,s2,..sn> and an undesired state BAD
We want to know:under which conditions, if any, our system S canreach BAD during its evolution (dynamic properties)
Modelling Public Mobile Network (PMN)Modelling Public Mobile Network (PMN)
ENEA FaMoS – Multilayer Modelling Activities ENEA FaMoS – Multilayer Modelling Activities
Topology Model and Topology Model and AnalysisAnalysis
nodes and arcs in the netnodes and arcs in the net
State Machine Model and Analysis
processes and links in the netprocesses and links in the net
Electricity Network
TelecomunicationNetwork
Transportation Network
Oil(Gas Network
Interdependency Model Interdependency Model and Simulationand Simulation
all the links with the other netsall the links with the other nets
Physical Model and Simulation
generators, transformers, breakers,generators, transformers, breakers,connecting cables etcconnecting cables etc
Dynamic Model and Analysisprocesses and links in the netprocesses and links in the net
will make use of logical and qualitative approaches to optimize the network in the presence of different type of constraints
ABSTRACT LOGIC VIEW OF A NETWORK
ENEA FaMoS – Multilayer Modelling Activities ENEA FaMoS – Multilayer Modelling Activities
Topology Model and Topology Model and AnalysisAnalysis
nodes and arcs in the netnodes and arcs in the net
State Machine Model and Analysis
processes and links in the netprocesses and links in the net
ElectricityNetwork
TelecomunicationNetwork
Transportation Network
Oil/Gas Network
Interdependency Model Interdependency Model and Simulationand Simulation
all the links with the other netsall the links with the other nets
Physical Model and Simulation
generators, transformers, breakers,generators, transformers, breakers,connecting cables etcconnecting cables etc
Dynamic Model and Analysisprocesses and links in the netprocesses and links in the net
will model the grid dynamics over a range of different geographic and time domains
ENEA FaMoS – Multilayer Modelling Activities ENEA FaMoS – Multilayer Modelling Activities
Topology Model and Topology Model and AnalysisAnalysis
nodes and arcs in the netnodes and arcs in the net
State Machine Model and Analysis
processes and links in the netprocesses and links in the net
Electricity Network
Telecomunication Network
Transportation Network
Oil/Gas Network
Interdependency Model Interdependency Model and Simulationand Simulation
all the links with the other netsall the links with the other nets
Physical Model and Simulation
generators, transformers, breakers,generators, transformers, breakers,connecting cables etcconnecting cables etc
Dynamic Model and Analysisprocesses and links in the netprocesses and links in the net
will establish probable correlation among different networks to understand cascading
failures or unknown and emergent behaviours
Oil
Electric
Power
Transpor-tation
NaturalGas
Telecom
Water
Water forProduction
CoolingEmission reduction
Water for Cooling,Emission reduction
Water for Cooling,
Power for pumpingStations, StorageControl Systems
Power for Pump& Lift Stations
Control Systems
Power for Switchers
Power for compressorsStorage, Control Systems
Power for Signalling, Switchers
SCADACommunications
SCADACommunications
SCADACommunications
SCADACommunications
Fuel for Generators,
Heat
Source:“Critic. Infrastruct Dependencies”
Rinaldi, Peerenboom,Kelly2002
Fuel for Generators,,Lubricants
Fuels, Lubricants
Fuels, Lubricants
Fuel for Generators,
Fuel TransportShipping
Fuel TransportShipping
Transportation
Transpor-tation
Modelling Networked Infrastructures Interdependencies
Higher abstraction level formalisms and conceptual models
Social
Network
Model
TransportationNetworkModel
ElectricalNetwork Model
InternetASModel
??
Common Simulation Platform to run Cooperating Models of Interacting Networks
A possible Framework for Interdependencies Modeling and Simulation
Electrical System Agent
Transport System Agent
Users System AgentHealth Services System Agent
Messages Broker
Supervisory System
FaMoS Agent Based Simulation Implementation for Interdependencies Analysis
SOCIO-COGNITIVE ENGINEERING APPROACH: Human Errors
Copy rights: High-Intelligence & Decision Research Group, CAMO, ENEA, http://erg4146.casaccia.enea.it Author: Adam Maria Gadomski, 8/10/2003
Large Complex Critical Infrastructure (LCCI)
Technological Grid
Human Errors
Organisation
Human component
Physical component
Cyber component
contributes to the Vulnerability Analysis and to the Improvement of Robustness of Large Complex Critical Systems
SOCIO-COGNITIVE ENGINEERING
Key Intervention Domains
• Users Modelling and Simulation
• Organization Structures and Decision-Making Modelling and Simulation
• Assessment of Social Risk and Impacts
• Intrusions and Mismanagement
Copy rights: High-Intelligence & Decision Research Group, CAMO,ENEA, http://erg4146.casaccia.enea.it Adam M. Gadomski, 7/10/2003
Pre-incident network in n-1 secure state
Island operations fails due to unit tripping
NETWORK STATE OVERVIEW & ROOT CAUSES
Event tree from UTCE report
ITALY BLACK-OUT(From UCTE Interim Report)
National InfrastructureSimulation and Analysis Center
NISAC A Suite of Models
• Energy Sector• Telecommunications Sector• Transportation Sector• Public Health Sector• Financial Sector• ……..• ……..
IST FP5 Roadmap Project: ACIP
Analysis & Assessment for Critical Infrastructure Protection
Analysis & Assessment for Critical Infrastructure Protection
www.eu-acip.de
Transportation(Air)
Vital Human Services
EISAC
Government
Transportation(Ship)
Transportation(Rail)
Banking & Finance
Energy
Telecommunication
European Infrastructures Simulation and Analysis Center - EISAC
Presidenza del Consiglio dei MinistriGRUPPO DI LAVORO SULLA PROTEZIONE DELLE
INFRASTRUTTURE CRITICHE
PROTEZIONE DELLE INFRASTRUTTURE CRITICHE
INFORMATIZZATELa realtà Italiana
Proposta per un Centro Nazionale di Simulazione delle Interdipendenze
Il Centro, non necessariamente localizzato in un solo sito geografico, sull’esempiodel National Infrastructure Simulation and Analysis Center (NISAC) americano dovrebbe avere l’obiettivo di:
1. Sviluppare Modelli e Metodi di Simulazione per l’Analisi delle Interdipendenze
2. Sviluppare una adeguata Piattaforma HW/SW di Simulazione. 3. Integrare Modelli e Metodi per studiare le Interdipendenze a fronte di diversi
Scenari e fornire indicazioni ai Decisori responsabili della Gestione delle Crisi.