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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 bologna@casaccia.enea .it. I Giovedi della Cultura ENEA-Casaccia, Aprile 29, 2004. Examples of Large Complex Critical Infrastructures.

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La Modellazione delle Reti Complesse: il Grand Canyon tra Ricerca e Realtà

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  1. La Modellazione delle Reti Complesse: il Grand Canyon tra Ricerca e Realtà Sandro Bologna ENEA – CAMO CR Casaccia, 00060 Roma bologna@casaccia.enea.it I Giovedi della Cultura ENEA-Casaccia, Aprile 29, 2004

  2. 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

  3. the italian high-voltage transmission line (380 kv) with 127 nodes and 342 edges

  4. UNION FOR THE CO-ORDINATION OF TRANSMISSION OF ELECTRICITY The UCTE System: 2100 Twh deliveredto400 ML people

  5. ELECTRICAL SYSTEM NETWORK Fonte: Corriere della Sera 30.09.03

  6. The World is a Network of Networks… Any Geographical Area, Any Network, Any Functional Area Is a Place of Vulnerability Oil and Gas Electric Banking and Finance Water Internet Core Transportation Government Services Emergency Services Telecommunications 7

  7.        - human organization node (Social Network) - physical network node (Technological Network) - control & information flows network node (Information Network) REPRESENTATION OF THE DIFFERENT LAYERS THAT MAKE A COMPLEX INTERACTIVE NETWORK

  8. Organisational Layer (Human Network) Intra-dependency Cyber-Layer (Information Network) Inter-dependency Physical Layer (Material Network) LCCI three layer Model

  9. Electrical Infrastructure Interdependencies Intra-dependency Inter-dependency Telecomunication Infrastructure Electrical Power Operators Independent System Operator for electricity planning and transmission Control and supervisory hardware/software components (Scada/EMS systems) Electrical Components: generators, transformers, breakers, connecting cables etc Electrical Power Transmission Infrastructure Oil/Gas Transport System Infrastructure

  10. Organisational Layer Intra-dependency Cyber Layer Inter-dependency Physical Layer WHY SO DIFFICULT TO MODEL Structural Complexity Network Evolution Node Diversity Connection Diversity Dynamical complexity

  11. US CANADA BLACK-OUT Power System Outage Task Force Interim Report

  12. Oil Example of Networked Infrastructures Interdependencies Fuels, Lubricants Fuel Transport Shipping Power for Signalling, Switchers Transpor- tation Transportation Fuel for Generators, ,Lubricants SCADA Communications Transpor- tation Fuel Transport Shipping SCADA Communications Power for pumping Stations, Storage Control Systems Fuels, Lubricants Water for Production Cooling Emission reduction Electric Power Fuel for Generators, Water for Cooling, Emission reduction Power for Switchers Natural Gas Heat Power for Pump & Lift Stations Control Systems SCADA Communications Power for compressors Storage, Control Systems Fuel for Generators, Water Water for Cooling, Source: “Critic. Infrastruct Dependencies” Rinaldi, Peerenboom,Kelly 2002 Telecom SCADA Communications

  13. ENEA FaMoS – Multilayer Modelling Activities Interdependency Model and Simulation all the links with the other nets Physical Model and Simulation generators, transformers, breakers, connecting cables etc Oil/Gas Network Dynamic Model and Analysis processes and links in the net State Machine Model and Analysis processes and links in the net Telecomunication Network Topology Model and Analysis nodes and arcs in the net Transportation Network Electricity Network

  14. ENEA FaMoS – Multilayer Modelling Activities Interdependency Model and Simulation all the links with the other nets Physical Model and Simulation generators, transformers, breakers, connecting cables etc Oil/Gas Network 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 Dynamic Model and Analysis processes and links in the net State Machine Model and Analysis processes and links in the net TelecomunicationNetwork Topology Model and Analysis nodes and arcs in the net Transportation Network ElectricityNetwork

  15. Power-law distribution Poisson distribution Random Network Scale-free Network COMPLEX SYSTEMS APPROACH Recent 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,…)

  16. 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

  17. 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)

  18. 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)

  19. 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)

  20. Present limitations of Complex Systems approach Network as a static graph 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 networks OBJECTIVE: capture the network dynamics • identify the processes that contribute to the network topology • develop dynamical models that capture these processes METHOD :

  21. ENEA FaMoS – Multilayer Modelling Activities Interdependency Model and Simulation all the links with the other nets Physical Model and Simulation generators, transformers, breakers, connecting cables etc will make use of complementary risk assessment methods to estimate the probability of unwanted incident that may lead to undesired states Foreign Electrical Transmission Infrastructure Dynamic Model and Analysis processes and links in the net State Machine Model and Analysis processes and links in the net Telecomunication Network Topology Model and Analysis nodes and arcs in the net Transportation Network Electricity Network

  22. Model checking Fault Tree Bayesian networks Extended Petri Nets Modelling tools for dependability analysis

  23. 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 can reach BAD during its evolution (dynamic properties)

  24. Modelling Public Mobile Network (PMN)

  25. ENEA FaMoS – Multilayer Modelling Activities Interdependency Model and Simulation all the links with the other nets will make use of logical and qualitative approaches to optimize the network in the presence of different type of constraints Physical Model and Simulation generators, transformers, breakers, connecting cables etc Oil(Gas Network Dynamic Model and Analysis processes and links in the net State Machine Model and Analysis processes and links in the net TelecomunicationNetwork Topology Model and Analysis nodes and arcs in the net Transportation Network Electricity Network

  26. ABSTRACT LOGIC VIEW OF A NETWORK

  27. ENEA FaMoS – Multilayer Modelling Activities will model the grid dynamics over a range of different geographic and time domains Interdependency Model and Simulation all the links with the other nets Physical Model and Simulation generators, transformers, breakers, connecting cables etc Oil/Gas Network Dynamic Model and Analysis processes and links in the net State Machine Model and Analysis processes and links in the net TelecomunicationNetwork Topology Model and Analysis nodes and arcs in the net Transportation Network ElectricityNetwork

  28. will establish probable correlation among different networks to understand cascading failures or unknown and emergent behaviours ENEA FaMoS – Multilayer Modelling Activities Interdependency Model and Simulation all the links with the other nets Physical Model and Simulation generators, transformers, breakers, connecting cables etc Oil/Gas Network Dynamic Model and Analysis processes and links in the net State Machine Model and Analysis processes and links in the net Telecomunication Network Topology Model and Analysis nodes and arcs in the net Transportation Network Electricity Network

  29. Fuels, Lubricants Fuel Transport Shipping Power for Signalling, Switchers Transportation Fuel for Generators, ,Lubricants SCADA Communications Transpor- tation Fuel Transport Shipping SCADA Communications Power for pumping Stations, Storage Control Systems Oil Fuels, Lubricants Water for Production Cooling Emission reduction Fuel for Generators, Water for Cooling, Emission reduction Power for Switchers Heat Power for Pump & Lift Stations Control Systems SCADA Communications Power for compressors Storage, Control Systems Fuel for Generators, Water for Cooling, SCADA Communications Modelling Networked Infrastructures Interdependencies Transpor- tation Electric Power Natural Gas Water Source: “Critic. Infrastruct Dependencies” Rinaldi, Peerenboom,Kelly 2002 Telecom

  30. Higher abstraction level formalisms and conceptual models Social Network Model Transportation Network Model Electrical Network Model Internet AS Model ?? Common Simulation Platform to run Cooperating Models of Interacting Networks A possible Framework for Interdependencies Modeling and Simulation

  31. Supervisory System Electrical System Agent Transport System Agent Messages Broker Users System Agent Health Services System Agent FaMoS Agent Based Simulation Implementation for Interdependencies Analysis

  32. Large Complex Critical Infrastructure (LCCI) Human component Cybercomponent Human Errors Physical component Organisation Technological Grid Copy rights: High-Intelligence & Decision Research Group, CAMO, ENEA, http://erg4146.casaccia.enea.itAuthor: Adam Maria Gadomski, 8/10/2003 SOCIO-COGNITIVE ENGINEERING APPROACH: Human Errors

  33. Copy rights: High-Intelligence & Decision Research Group, CAMO,ENEA, http://erg4146.casaccia.enea.itAdam M. Gadomski, 7/10/2003 SOCIO-COGNITIVE ENGINEERING contributes to the Vulnerability Analysis and to the Improvement of Robustness of Large Complex Critical Systems • Key Intervention Domains • Users Modelling and Simulation • Organization Structures and Decision-Making Modelling and Simulation • Assessment of Social Risk and Impacts • Intrusions and Mismanagement

  34. (From UCTE Interim Report) ITALY BLACK-OUT NETWORK STATE OVERVIEW & ROOT CAUSES Pre-incident network in n-1 secure state Island operations fails due to unit tripping Event tree from UTCE report

  35. National InfrastructureSimulation and Analysis Center

  36. NISAC A Suite of Models • Energy Sector • Telecommunications Sector • Transportation Sector • Public Health Sector • Financial Sector • …….. • ……..

  37. IST FP5 Roadmap Project: ACIP ACIP Analysis & Assessment for Critical Infrastructure Protection www.eu-acip.de

  38. Telecommunication Transportation (Ship) Government Banking & Finance Transportation (Rail) Energy EISAC Transportation (Air) Vital Human Services European Infrastructures Simulation and Analysis Center - EISAC

  39. Presidenza del Consiglio dei Ministri GRUPPO DI LAVORO SULLA PROTEZIONE DELLE INFRASTRUTTURE CRITICHE PROTEZIONE DELLE INFRASTRUTTURE CRITICHE INFORMATIZZATE La realtà Italiana

  40. Proposta per un Centro Nazionale di Simulazione delle Interdipendenze Il Centro, non necessariamente localizzato in un solo sito geografico, sull’esempio del 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.

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