1. DEVS and SES as a Framework for Modeling and Simulation Tool Development Bernard P. Zeigler Arizona Center for Integrative Modeling and Simulation University of Arizona Presented at SIMUTools 2008 March 3–7 2008 Marseille, France

2. M&S Framework Source System Simulator Model Experimental Frame Simulation Relation Modeling Relation Based on mathematical formalism using system theoretic principles Separation of Model, Simulator and Experimental Frame Atomic and Coupled types Hierarchical construction

3. x 0 x 1 X S Y y0y0 e t0t0 t1t1 t2t2 Discrete Event Time Segments

4. M&S Framework formulated within UML classes construction mechanisms relationships constraints create classes to satisfy use cases M&S Framework classes interpretation as software code (e.g. Java) Use Cases UML models simulators Source systems Experimental & Pragmatic Frames ontologies collect data store model run model construc t model store data simulate model sensor retri eve data retrieve model validate model memory control- simulator predictive -simulator model evaluator model generator real world model generated goal- generator action planning motor objectives M&S apply pragmatic frame apply experimen tal frame

5. DEVS – Formal Specification of a System A discrete event system specification (DEVS) is a structure M= where X is the set of input values, S is a set of states, Y is the set of output values,  int :S->S is the internal transition function,  ext, :Q  X->S is the external transition function,  con, :Q  X->S is the confluent transition function, ta: S->R + 0,∞ Where Q={(s,e)|s  S, 0  e  ta(s) } is the total state set, e is the time elapsed since last transition, :S->Y is the output function and R + 0,∞ is the set of positive reals with 0 and 

6. DEVS Hierarchical Modular Models DEVS Model Output port Input port DEVS Model message coupling SES Hierarchical Composition, Coupling and Variants are Represented in System Entity Structure System Entity Structure

7. Atomic Models Ordinary Differential Equation Models Spiking Neuron Models Coupled Models Petri Net Models Cellular Automata n-Dim Cell Space Partial Differential Equations Self Organized Criticality Models Processing/ Queuing/ Coordinating Processing Networks Networks, Collaborations Physical Space Some Types of Models Represented in DEVS can be components in a coupled model Multi Agent Systems Discrete Time/ StateChart Models Quantized Integrator Models Spiking Neuron Networks Stochastic Models Reactive Agent Models Fuzzy Logic Models

8. Concept of DEVS Standard DEVS Simulator Interface Single processor Distributed Simulator Real-Time Simulator C++ Non DEVS Model Interface Java Other Representation DEVS Simulation Protocol Virtual-Time Simulator DEVSML

9. DEVS Simulation Protocol Coordinator Atoimc1 Non-DEVS Simulator Atoimc2 simulators.tellAll("initialize“) simulators.AskAll(“nextTN”) simulators.tellAll("computeInputOutput“) simulators.tellAll("sendMessages") simulators.tellAll(" Coordinator DEVS Model 1 simulators.tellAll("initialize“) simulators.AskAll(“nextTN”) simulators.tellAll("computeInputOutput“) simulators.tellAll("sendMessages") simulators.tellAll(" ApplyDeltFunc”) putContentOnSimulator DEVS Simulator DEVS Model 2 ?

10. Finite Deterministic DEVS : FD-DEVS FDDEVS = where incomingMessageSet, outgoingMessageSet, StateSet are finite sets TimeAdvanceTable: StateSet → R 0, ∞ + (the positive reals with zero and infinity) InternalTransitionTable: StateSet → StateSet ExternalTransitionTable: StateSet × incomingMessageSet → StateSet, OutputTable: StateSet → the set of subsets of outgoingMsgSet Natural Language For FDDEVS to start hold in PHASE for time SIGMA when in PHASE and receive MSG go to PHASE’ hold in PHASE for time SIGMA after PHASE then output MSG from PHASE go to PHASE’ Semantics defined by mapping into DEVS

11. FD-DEVS Example of Natural Language Spec: 1.to start passivate in waitForStart 2.when in waitForStart and receive StartAck go to sendFirst 3.hold in sendFirst for time 0.5 then output ReqForAck and go to sendSecond 4.hold in ackReceived for time Infinity 5.… waitFor Start send First send Second send Third Ack Received StartAck Ack 0.5 10 ∞ ∞ last Chance ReqForAck Ack The “right” abstraction of DEVS – retains important timing properties Amenable to analysis Supports automation Maps to DEVSJAVA Supplies a skelton that can be extended to full DEVS Simple XML expression

12. Automated Analysis: Based on State Input Pairs Enables Automated Test Model Generation listen Awaiting Adv OrderOfferProdFeasibilityFalse ProdFeasibilityTrue waitFor Confirm Confirm Dominant State-Input pair: listen,orderOffer Dominant State-Input pair: listen,orderOffer State-Input pair paths: 1= listen,OrderOffer 2 = listen, OrderOffer, awaitingAdv,ProdFeasibilityFalse 3= listen,OrderOffer awaitingAdv,ProdFeasibilityTrue 4= listen,OrderOffer awaitingAdv,ProdFeasibilityTrue waitForConfrm,Confirm Dominant State- Input pair paths: 2 4 Defined State-Input pairs: listen,orderOffer awaitingAdv,ProdFeasibilityFalse awaitingAdv, ProdFeasibilityTrue waitForConfrm,Confirm Defined State-Input pairs: listen,orderOffer awaitingAdv,ProdFeasibilityFalse awaitingAdv, ProdFeasibilityTrue waitForConfrm,Confirm Terminal State-Input Pairs: awaitingAdv, ProdFeasibilityFalse waitForConfrm, Confirm Terminal State-Input Pairs: awaitingAdv, ProdFeasibilityFalse waitForConfrm, Confirm State-Input Pairs mapped To Terminal State-Input pairs: listen,orderOffer -> awaitingAdv, ProdFeasibilityFalse awaitingAdv, ProdFeasibilityTrue -> waitForConfrm, Confirm

13. Generated Test Models in DEVSJAVA SimView AckCheck Send inputs Observe Outputs Trigger next in Sequence upon pass Observe Pass/Fail

14. System Entity Structure (SES) : SESBuilder

15. System Entity Structure/Model Base Repository: Support Automated DEVS Generation and Reuse Model construction SES Model Repository Experimental Frame prune and transform

16. Automated Generation of Test Models SES/XML Of DSR texts SES Pruned ES FDDEVS atomic model FDDEVS test models Augmented Test Models Automatedmanual

17. DEVS/SOA Infrastructure: Supports Deployment and Execution of DEVS Models on the Web WEB SERVICE CLIENT Middleware (SOAP, RMI etc) Net-centric infrastructure DEVS Simulator Services DEVS Modeling Language (DEVML) DEVSJAVA DEVS Agent ( Virtual User) DEVS Agent (Observer) WEB SERVICE CLIENT Run ExampleExample Service Oriented Architecture (SOA) consists of various W3C standards Machine-to-machine interoperable interaction over the network based on WSDL interface descriptions Client server framework Message encapsulated in SOAP wrapper which is in XML

18. Deploying Models: DEVSML and DEVS/SOA

19. Applications Natural language capture of high level information technology systems requirements Automated generation of FDDEVS kernel DEVSJAVA/C++ models for distributed real-time net- centric IT systems testing Development of web service workflows using DEVS/SOA Network Traffic data capture, focused extraction, and model generation for exercising IT systems e.g., intrusion detection

20. Conclusions DEVS and SES provide a framework based on Systems Theory for M&S tool development DEVS standard supports sharable models and repository reuse The framework provides an ontology in which tools can be organized and interoperate – missing slots can be identified; overlapping tools can be compared The framework supports development of generic tools which in turn support a wide array of domain specific specializations and applications

21. devsworld.org acims.arizona.eduRtsync.com Books and Web Links