1. Dip. Di Informatica Sistemi e Produzione Università di Roma Tor Vergata E. Casalicchio, E.Galli, S.Tucci CRESCO SPIII.5 Project status 06-07-07 Università di Roma "Tor Vergata" - CRESCO-SPIII

2. What's an Agent 2 It's a software process able to work asynchrounsly and autonously in an particular environment An agent is identifiable, a discrete individual with a set of characteristics and rules governing its behaviors and decision- making capability. It can perceive and interact with the world (environment and other agents) Agents have protocols for interaction with other agents Every agent is identified by an own location, capabilities and memory. Can adapt its behaviours according to its experience Every agent has its own goal. Intelligent agent can evaluate different plans and choose the best one Università di Roma "Tor Vergata" - CRESCO-SPIII

3. What is ABM&S 3 ABMS has its direct historical roots in complex adaptive systems (CAS) Systems are built from the ground-up Important results can emerge in systems that are completely described by simple rules that are based on only local information Results that may develop can be extremely sensitive to the initial conditions. Simple rules can be used to understand much of the complexity observed in the real world Università di Roma "Tor Vergata" - CRESCO-SPIII

4. Why ABM&S 4 I. Allow to simulate a complex system composed by many subsystem  organize system hierarchically  decomposition of an agent in multi-agents  simplify interactions between entities when it's to hard to represent them with equations II. Customize the target system as required by the case under study III. Allow to study of unexpected pertubations on the interconnected infrastructures IV. Study the behaviour of an infrastructure for a certain input more than a equations V. Allow to give a whole picture of the system behaviour VI. Allow to use external specific simulators, wrapping them with a agent Università di Roma "Tor Vergata" - CRESCO-SPIII

5. Independent or sequential simulation E.g.: Simulation of the effect of fault in the power grid in [t1, t2]. From the output i know that Roma- Est city’s area will experiment a blackout [t1’,t2’] I use such result to build a scenario for the simulation of the communication network behavior in [t1,t2] introducing a blackout starting at t1’ and ending at t2’ 5 Università di Roma "Tor Vergata" - CRESCO-SPIII

6. Interdependent or distributed simulation E.g.: simulation of the transportation net., the power grid and the comm. net. in Roma in [t1,t2] At time t’>t1 the power grid experiment a failure. Such failure propagates and have a direct effect at time t’+dt on a node of the comm. net. The failure of a comm. net. node has an impact on a not well known simulated system that directly or indirectly use the CommNet, e.g. the transp. net. 6 Università di Roma "Tor Vergata" - CRESCO-SPIII

7. Advantages & Disadvantages Università di Roma "Tor Vergata" - CRESCO-SPIII 7 Sequential: -/+ macroscopic int. analysis - Do not emerge unknown interdependencies + Does not require simulators re-engineering Distributed: + microscopic int. analysis + could emerge unknown interdependency - Requires simulators re- engineering or adaptation

8. Introduction to a custom approach with Repast and Omnet Università di Roma "Tor Vergata" - CRESCO-SPIII 8 We have used Repast as Toolkit for ABM&S We have modeled both some Infrastructure and simple users which use them We have used OMNeT++ as framework DES (discrete event simulation) to simulate Communication Network We have developed a distributed approach with Repast and OMNeT to study an our defined simple scenario

9. Introduction to a custom approach with Repast and Omnet (cont.) ‏ Università di Roma "Tor Vergata" - CRESCO- SPIII 9 In Repast has been simulated interaction between different infrastructures. Every Infrastructure is an agent with its behaviour, memory and so on. The communication network is modelled using a specialized simulator: Omnet The agents which communicate using the Communication networks use specific calls of the: CommunicationNetworkAgent V.Cardellini, E. Casalicchio, E. Galli. Agent-based Modelling of Interdependencies in Critical Infrastructures through UML. In Proc. of Spring Simulation Multiconference 2007 (SpringSim07) REPASTOMNET Internet R1 R2 R3 R4R5 IS4CEM Wounded CMN HCC1 Soccurer Wounded Soccurer IS4CEM HCC1

10. Implementation of model: Network Università di Roma "Tor Vergata" - CRESCO-SPIII 10 Based on two level: Interactions between infrastructures are controlled by agents of Repast Simulation of communication network developped with OMNet++ Developped an interface between Repast and OMNet++ The communication network is built in OMNet++ Setting of capacity of lynks between agents Simulation of workload The CommunicationNetwork Class of Repast control failure and can set new capacity for a link Agents use CommunicationsNetwork’s method to send message to other agents on network

11. Implementation of model: Network (cont) ‏ Università di Roma "Tor Vergata" - CRESCO-SPIII 11 Example of sending of a message: Every agent that wants to send a message on network comunicates its necessity to Communication Network Class Communication Network prepares messages to send and uses the interface with OMNet++. Simulation is paused. OMNet++ calculates routing and time for every new message and informs Communication Network, if any message is arrived at destination. The Communication Network Class determine if there is a failure in the communication (e.g. with a timeout). Communication Network schedules reception of messages for every receiver-agents and the simulation restarts

12. Some screenshots: Repast & Omnet Università di Roma "Tor Vergata" - CRESCO-SPIII 12

13. Some screenshots: Graphs with Omnet Università di Roma "Tor Vergata" - CRESCO-SPIII 13

14. Some screenshots: GUI of Omnet Università di Roma "Tor Vergata" - CRESCO-SPIII 14

15. Conclusions Università di Roma "Tor Vergata" - CRESCO-SPIII 15 Study of the common scenario Create an interface for every Infrastructure Simulator Study of interdependency between different infrastructures Mapping every infrastructure to a geographic location Use of GIS or Google's API Introduce a more complex fuzzy-set rules for every actors that we want to model