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„Component-Based“ Modeling and Simulation

„Component-Based“ Modeling and Simulation. An Exploration based on James II. A.M. Uhrmacher University of Rostock. Computer science department Modeling & Simulation group. Definitions – Model and Simulation.

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„Component-Based“ Modeling and Simulation

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  1. „Component-Based“ Modeling and Simulation An Exploration based on James II A.M. Uhrmacher University of Rostock Computer science department Modeling & Simulation group

  2. Definitions – Model and Simulation • „A model (M) for a system (S) and an experiment (E) is anything to which the experiment (E) can be applied to answer questions about the system (S). (Minsky 1965) • „A simulation is an experiment performed on a model“ (Korn/Wait 1991)

  3. Component-Based Approach • Component – A physical, replaceable part of a system that packages implementation and provides the realization of a set of interfaces. (OMG 99) • A component-based model design facilitates the development of individual models on demand • A component-based design of a simulation system supports the development of individual simulation systems on demand

  4. Based on DEVS • A modelling formalism based on DEVS • hierarchical composition, • atomic and coupled models, • closed under composition • extended • by means of reflection which supports the creation, deletion and migration of models • by peripheral ports via which external software and simulation interact • by time models to relate resource consumption and simulation time • by variable ports to support plasticity • by semantically enriched couplings • Basis of the simulation system James (Java-Based Agent Modelling Environment for Simulation)

  5. Discrete Event Systems Specification DEVS = < X, Y, S, sinit, dint, dext, ta, l > Zeigler, 1984

  6. DEVS & Dynamic Structures • DEVS models support a modular, hierarchical construction of discrete event models • Reflective models support “modularity” with respect to the temporal dimension. c s1 ta = c s31 x = b x = c s4 x = b ta = a s7 s3 x = b s5 x = b s2 ta = f s6 s51 ta = f x = c b d b

  7. regulator gene operator region genes coding for the 5 enzymes needed to synthesize tryptophan promoter region binding site for RNA polymerase RNA polymerase Application: The Tryptophan Operon A Repressible Operon in the Presence of a Corepressor RNA polymerase is unable to transcribe the genes needed to synthesize tryptophan inactive repressor protein active repressor protein corepressor (tryptophan)

  8. Structure of the Tryptophan Operon

  9. after expRandom(unbindingT) free repressing removeCouplingTo(Operon) after deacTime [deacTime < reprTime] Trp accept / / reject / removeCouplingTo(Operon) active deacTime = expRandom(deactT) reprTime = expRandom(reprT) trying to dock after reprTime [reprTime  deacTime] / addCouplingTo(Operon) Trp dock Repressor Trp Trp undock / Repressor – StateChart

  10. Model component profile – Meta Model <profile> <name>Enzyme.AAA.Trp.Ecoli.DEVS.Model_1</name> <application_domain>Enzymology;Systems Biology</application_domain> <domain_dependent_classification> GO:0004834 ; EC:4.2.1.20 </domain_dependent_classification> <text_description> Tryptophan Synthase is an enzyme classified by the E.C. number: EC 4.2.1.20. The described enzyme stems from the organism E.coli. It produces Tryptophan and Glycerole-3-phosphate and consumes Serine, Indole-glycerole-3-phosphate The model component is developed using the DEVS formalism. </text_description> <input Serine; Indole-Glycerole-3-phosphate /input> <output Tryptophan; Glycerole-3-phosphate /output> <objective> Analysing the static channeling effect; Analysing the behavior of single enzymes. </objective> ... </profile> EC:4.2.1.20 Serine; Indole-Glycerole-3-phosphate Tryptophan; Glycerole-3-phosphate

  11. Visualization

  12. Application: Simulation-based Testing of Software • Test cases not predefined but evolve dynamically • Well-suited for testing the interaction of agents (correctness / timeliness) with a virtual environment • Rather Black Box than White Box testing tsim 7:01 tsim 7:04 tsim 7:05 tsim 7:00 Simulation apartment elderly care giver robot zo zo zi zo zo zi 8:00 take medicine ... Autominder

  13. SQL Transparencies 1 - 2 - 4 Summary of 2PC Exercise SQL Exercise: UML Solution SQL-Exercise Description Diane More about SQL? Anna Project: Services in Adhoc Networks, Prof. Koenig Ries, University of Jena & University of Karlsruhe

  14. Requirements Service propagation Focus: • Modular design of the test environment • Specification of protocols as state charts • Easy plug and play • User models at different levels of detail and realism (HBR) Questions: • How much does the dynamic of the network influence the performance of lanes in comparison to flooding? • What criteria decide which length of lanes is optimal? • What is the effect of users moving in groups ? 1 5 9 2 6 10 any cast any cast 3 7 11 4 8 12 Service search

  15. Diane Test environment Node Environment User movement transport protocol Lanes

  16. Need for different types of simulators • Tryptophan synthase / operon • A sequential processor, unpaced • Parallel conservative, unpaced • Parallel optimistic, unpaced • Autominder • sequential processor, paced with an EPI • Diane • All of them • …. How can we support such diverse simulation engines for one model?

  17. Component-based design of simulation layer

  18. Which implements • A sequential processor, unpaced • A sequential processor, paced • A sequential processor, paced with an external process interface for the SUT (Software under Test) • A sequential processor, unpaced with an EPI • A conservative, unpaced processor • A conservative, paced processor • A conservative, unpaced processor with an EPI • A conservative, paced processor with an EPI • A sequential processor, unpaced for integration • ….

  19. RC C RC Seq Seq S Seq Seq C … Seq C C S Seq Seq … S S S S Model and Dynamic Simulation Tree Structure cell bulk Enzyme 1 Enzyme n … alpha beta alpha beta

  20. Evaluation of Performance by Meta Simulation • Meta-Simulation can be used to select appropriate simulation algorithms, depending on model and hardware properties • Facilitates evaluation of simulation approaches Application Model Simulator Model Infrastructure Model Simulation Simulator

  21. Conclusion Applications • Cell biology, e.g. Tryptophan Synthase, just at the beginning wnt signalling pathway • Software testing, Diane (services in ad-hoc networks) Methods • Focus on Devs models and variants, • Different parallel, distributed, paced, unpaced (discrete-event) simulator components • A set of partitioning and load-balancing components • Meta simulation to help a performance-oriented exploitation of simulator components Future Work • Integration of • Additional modelling formalisms, e.g. Beta Binders • Additional simulator components, e.g. for continuous simulation • Interaction with verification tools • To support parameter selection and model composition • Exploration of models • Support for a better exploitation of model components

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