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

bologna@casaccia.enea.it

Sandro Bologna

ENEA – CAMO

CR Casaccia, 00060 Roma

bologna@casaccia.enea.it

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.