Discrete Event Modeling and Simulation of Distributed Architectures using the DSSV Methodology E. de Gentili, F. Bernardi, J.F. Santucci University Pascal Paoli of Corsica SPE Laboratory UMR CNRS 6134

2 Studied Problem Main Objectives of our Research – Modeling and simulation of the behavior of a software object – Showing up a generic methodology for the modeling of this kind of objects Selected Approach: DEVS Based Modeling and Simulation Selected Application: CORBA Architecture (and especially the Portable Object Adapter)

3 Outline of the Presentation DEVS Modeling Theory Methodology for Algorithmic functions Modeling (DSSV) The CORBA Portable Object Adapter (POA) Example: the find_poa() Function Results and Validation Conclusion and Perspectives

4 DEVS Modeling Theory The DEVS (Discrete EVent System Specification) Modeling and Simulation Approach: – Describes a system by components interconnection – Allows interactions between components using communication ports – Uses two types of components Two Main Points: – Event: Information arrival on a port – Simulation: Taking into account behavioral changings according to time or events

5 DEVS Modeling Theory Components used for Modeling considering a Given System: – Atomic Models: Basic components that provide a local description of the dynamic behavior of the system – Coupled Models: Corresponds to a set of behavioral components that describes the manner a new component is created by interconnecting some others

6 DEVS Modeling Theory An atomic model is defined by: – A set of input ports – A set of output ports – A set of state variables: define completely the states of the model – Two transition functions: allows to change the state variables – An exit function – A time advance function

7 DEVS Modeling Theory Why DEVS ? – Long experience in our laboratory with many works based upon this approach – Already defined and satisfying tools – Great adaptation to discrete event systems such as computer programs Original approach: Showing up a methodology for algorithmic functions modeling

8 Methodology for Algorithmic Functions Modeling Basic Approach (starting from the source code): – Algorithmic functions are seen as coupled models – An atomic model represents the modeling of the behavior of the function between two calls to other external functions – Internal variables of the function are binded to state variables – Variables are carried through specialized ports as long as the function need them

9 Methodology for Algorithmic Functions Modeling For a better understanding, we introduce four kinds of ports: – Call Ports: used to carry the name of the function to be called – Parameter Ports: used to carry the parameters needed by a function – Secondary Call Ports: dedicated to external functions couplings – Secondary Parameter Ports: used to carry data between coupled models

10 Example of function: Methodology for Algorithmic Functions Modeling AM1 AM2 AM3 int f(a,b) { e = g(d); return e; }

11 Methodology for Algorithmic Functions Modeling AM1 AM4 AM3AM2 CM2: g(d)  e CM1: f(a,b)  c a b c f(a,b) g(d) Exception de Parameter Ports Call Ports Secondary Call Ports Secondary Parameter Ports

12 Methodology for Algorithmic Functions Modeling Basic Control Structures Modeling The « if » statement The « do » statementThe « for » statement The « while » statement AM1 AM2 AM3 AM1 AM2AM1 AM2AM1

13 Methodology for Algorithmic Functions Modeling Algorithmic function: Coupled model composed by the interconnection of atomic models Application: Modeling of the CORBA Portable Object Adapter

14 The CORBA Portable Object Adapter (POA) CORBA: Common Object Request Broker Architecture Reference architecture for distributed systems Many implementations available Object-Oriented architecture (OMG) Based upon many concepts such as: ORB, POA, servant, client,...

15 The CORBA Portable Object Adapter (POA) Position of the POA in the CORBA Architecture ORB (Object Request Broker) Proxy ClientServant POA Requests

16 The CORBA Portable Object Adapter (POA) The POA is defined as an object presenting 25 methods For example: create_POA(), find_POA(), destroy() PortableServer::POA the_name : string … create_POA() find_POA() destroy() get_servant() …

17 Example: the find_poa() function Returns a pointer to a POA adapter name Can raise an exception (AdapterNonExistent) Accepts two parameters (adapter, activate)

18 Example: the find_poa() function C++ simplified source code POA_ptr find_poa(adapter, activate) { if (getDestroyed()) throw Exception; bool check=true; if (containsKey(adapter) && activate) { adapterActivator = getAdapterActivator(); if (adapterActivator != NULL) check = unknownAdapter(adapter); } POA poa; if (check) get(adapter, poa); if (poa == NULL) throw AdapterNonExistent; return poa; }

19 Example: the find_poa() function Definition of the Coupled Model POA: – Input ports: adapter, activate children, poa_control (ORB) find_poa (Methodology) – Output ports: Exception, POA_ptr Coupled Model find_POA() POA_ptr activate adapter children poa_control find_poa() Exception

20 Example: the find_poa() function Components: 10 atomic models Links to 5 other coupled models Minimal path (without exception): 6 atomic models Maximum path (without exception): 10 atomic models

21 Results and Validation Simulation using a software written in Java Validation by testing all possible paths Good results for every function simulated

22 Results and Validation

23 Conclusion and Perspectives Originality of our approach: Use of DEVS modeling for algorithmic functions Modeling and simulation starting from the source code Application: CORBA Architecture Already done: Portable Object Adapter Main objective: Being able to simulate the whole CORBA architecture for testing new services

24 Conclusion and Perspectives Perspectives: – To complete the whole architecture (ORB) – To add a physical network simulation tool – To simulate a complete distributed application over a network – To develop new techniques of validation