INNOVATIVE METHODS AND TECHNIQUES FOR HIGH-PERFORMANCE AND - RELIABILITY MODELING AND SIMULATION (M&S)

Transcription

1 INNOVATIVE METHODS AND TECHNIQUES FOR HIGH-PERFORMANCE AND - RELIABILITY MODELING AND SIMULATION (M&S) Prof. Dr. Axel Lehmann titut für Technik Intelligenter Systeme (ITIS) at the Universität der Bundeswehr München Germany Institut für Technische Informatik Universität der Bundeswehr München Germany lehmann@informatik.unibw-muenchen.de URL:

2 OUTLINE 1. Modeling & Simulation (M&S): State of the Art and Demands 2. M&S: A Multiple-Phase Development & Application Process 3. Component-Based M&S 4. M&S - Verification, Validation & Accreditation (VV&A) 5. Parallel and Distributed M&S 6. Conclusions

3 &S - State of the Art and Demands Trends / Requirements of (Technical) Systems Developments Rapid technological innovations new information and communication technologies efficient, powerful, computer-assisted tools (e.g. CAD, CAM,... ) Increasing systems complexity & lifetime embedded systems distributed systems networks of components / systems Increasing productivity & cost-benefit Decreasing cycle times for system s innovations

4 Major Challenges Mastering of system(s) complexity over lifetime w.r.t. multiple aspects /goals? (safety, reliability, performance,...) Approach: Goal-oriented, efficient, effective and dependable models!

5 Mastering of model(s) complexity!? STRATEGIC approach: Devide and Conquer!! MODEL-ENGINEERING approach!!

6 Current Importance of M&S (as a discipline / methodological approach / tool set): Receives increasing acceptance by decision makers Becomes more and more a standard method / tool set Seen as a major enabling technology for innovations Research relevancy is well-documented, e.g. by :

7 95, US-DARPA:... M&S is one of the top-10-key enabling technologies... 98, DoD (Dr. Gansler):... by the year Systems development in 25 % less time... 99, US-government: IT 2 Research Initiative 99, PITAC report: Fund research in... global-scale networks and its associated information infrastructure... including... Modeling and simulating network behaviour (Recommendation 3.3.2) 03, EU 6th Research Framework Program

8 Major Challenges for M&S applications: Increasing systems / M&S complexity Decreasing cycle times for systems / M&S innovations Increasing lifetimes of systems, models, and simulations Increasing variety of M&S-aspects / purposes Safety, reliability,... cost-benefit constraints (for systems / M&S) Hardware-/Software-/User-in-the loop simulation User acceptance; ease of use & credibility Application of Virtual / Augmented Reality ( VR, AR ) etc.

9 General Approaches, Methods to cope these M&S-Challenges: Hierarchical modeling Hybrid models (OR-, analytic, simulation solutions) Interoperability of models Reuseability of models (model components) Collaborative M&S Parallel & distributed M&S Improved model credibility by application of VV&A Model engineering

10 M&S - Design, Implementation and Application Process Example: Effectiveness and efficiency of a Booking System (Customers who access their bank accounts to transfer or to deposit money; client-server architecture) Goal parameters to be analysed might be, e.g.: processing time per transaction client/server utilization queueing time, queue length How to approach this (complex) problem? Divide and Conquer : A Multiple-Phase M&S Process

11 Phases & Products in the M&S - Development Process Hauptobjekt mit Modellattributen Systemgrenze Objekt Objekt Objekt Intera kt i on Objekt Model Documentation Umweltobjekt Examination Aim Problem Definition Structured Problem, Description Project Objectives System Observations Conceptual req.&constr. System Analysis Communicative Conceptual Model Modeling Method Formal req.&constr. Model Formalization Formal Model Solution Techniques Technical req.&constr. Implementation Executable Model Model Input Data Experimental req.&constr. Experimentation Model Results

12 M&S-Sources of Knowledge and Expertise User Knowledge Problem Definition System Analysis Domain Knowledge Model Formalization Modeling Expertise Implementation Experimentation (HW-)SW- Expertise Experimental Design and Analysis

13 M&S-Development Team (Skills) User Problem Definition User Knowledge ustomer System Analysis Domain Knowledge Domain Expert Model Formalization Modeling Expertise Modeller Implementation Experimental Design and Analysis ct Manager ntractor) Programmer Experimentation (HW-)SW- Expertise

14 . Component-Based M&S Divide and Conquer -approach: decomposition of (complex) models/problems components Component : not a well-defined term!! Example: Booking System

15 Example: Booking System Conceptual Model : T 1 I/O device 1 CPU T n I/O device n Server

16 Example: Booking System Formal Model (Version 1): queueing net

17 Example: Booking System Formal Model (Version 2): Remote Jobs

18 Performance measures: Little s law: k λ t Q = = or λ w With: response time t, queueing time w, service rate µ t = w + µ 1 ; k = Σ k p (k) 6 State probability p(k) 6 Utilization ρ ( m service stations) ρ = arrival rate service rate = λ < 1 m µ

19 Conclusions model component (e.g. regarding the example Booking System ) Problem Description: pragmatism / goal specification Conceptual Model: structural & functional description of components different levels of abstraction Formal Model: formal specification of components ( selected modeling paradigm(s)) different levels of abstraction hierarchical modeling approach ( decomposition into submodels / components Executable Model(s): e.g. analytic solution reusable SW- components simulation

20 Phases & Products in the M&S - Development Process Hauptobjekt mit Modellattributen Systemgrenze Objekt Objekt Objekt Intera kt i o n Objekt Model Documentation Umweltobjekt Examination Aim Problem Definition Structured Problem, Description Project Objectives System Observations onceptual req.&constr. System Analysis Communicative Conceptual Model Modeling Method Formal req.&constr. Model Formalization Formal Model Solution Techniques Technical req.&constr. Implementation Executable Model Model Input Data erimental req.&constr. Experimentation Model Results

21 M&S- componen X X X X

22 Model ( Component ) Specification Levels 6 Model Federation Level Black Boxes 6 Model Level Autonomous, interoperable models 6 Submodel / Object Level Submodels / Object structures of different modeling paradigms 6 Function Level Coded basic functions / algorithms Model repository Library of submodels & communication infrastructure Library of objects/methods (for interaction) Program Library ls ( ti ) f si rs ( ti+ 1 ti ) + zs ( ti, ti+ 1) : wenn ls ( ti + 1) > 0 s. ls( ti+ 1) = 0 : sonst mit 0 < i n und 0 < s 6

23 Component-Based M&S : Current Approaches Hierarchical modeling via - decomposition - aggregation - hybrid solution / implementation techniques Generic modeling object templates (depending on the modeling paradigm), e.g. - class / object libraries Function / Program libraries, e.g. - statistical analyses - random number generators Coupling of monolithic models, e.g. - federation of models (DIS, HLA,... ) - agent-based simulation Conclusion: Missing comprehensive formal & methodological approaches r component-based M&S

24 . M&S-Verification, Validation & Accreditation (VV&A) Terminology Model validation: process of demonstrating that a model and its beha suitable representations of the real system and its behavior w.r.t. intended purpose of model application. Model verification: process of demonstrating that a model is correctly represented and was transformed correctly from one representation form into another, w.r.t. transformation and representation rules, requirements, and constraints.

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