1. Simulation concepts and architectures

2. Simulation Basics System: a collecting of entities that act and interact together toward the accomplishment of some logical end. State: the collection of variables necessary to describe a system at a particular time, relative to the objectives of a study Model: a description about how a system behaves, that consist of a collection of assumptions.

3. System Experiment with the actual system Experiment with a model of the system Physical model Mathematical model Analytical solution Simulation Figure 1. Ways to study a system

4. Experiment with the actual system vs. Experiment with a Model of the system –Costly, disruptively. –“System” could be only a conceptual matter. –Validity : the accuracy of the model. Physical model vs. Mathematical model –Cockpits, miniatures, etc. are iconic. Sometimes useful in operations research like scale models. Analytical solution vs. Simulation –v = d/t –Large nonsparse matrix inversion, manufacturing system, the Matrix

5. Static vs. Dynamic simulation models –Whether time plays an role in the model Deterministic vs. stochastic simulation models –Whether random elements are taken into account –One of the main disadvantage of simulation Continuous vs. discrete simulation models –Whether state changes happen instantaneously in countable time points. Simulation models

6. Time advance mechanisms for discrete-event models Next-event time advance ….while ( !done) { System->next_Event(); Simulation_clock->update(); }….. Fixed-increment time advance ….while (time <= end_time) { System->update_states(); time++; }….

7. Distributed simulation Why distributed simulation? –Ever-complex system and simulation models require more computing power –Advance in hardware and software technologies –Lower cost of hardware –Network computing capabilities

8. Distributed systems: the middle tier contains computers without shared memories. Acts as one single machine to users. Dialogue between computers is make possible by a unique inter-process communication mechanism Users don’t know where the resources are located Resources can be moved without changing their names Users don’t know the number of existing instances of the object Many users can share the resources automatically Some processes may execute in parallel on the network.

9. Distributed simulation architecture Basic elements: –An object interface language : describe interface. Distributed applications require more abstract level of communications than ordinary ones. Provide interoperability between distributed objects –An object manager : Passing references to requesting clients Instantiating objects and marshalling(coordinating) object requests between different machines. Objects therefore become indifferent to invokers. –A naming service The mechanism by which a server informs clients about objects available for access. Making the communications between objects can be delayed until runtime.

10. High level architecture

11. Common Object Request Broker Architecture

12. J2EE’s RMI Remote Method Invocation/Internet Inter-ORB Protocol (RMI/IIOP)— Protocol that enables Remote Method Invocation (RMI) Programmers to combine the benefits of using the RMI APIs and robust CORBA IIOP communications protocol to communicate with CORBA-compliant clients that have been developed using any language compliant with CORBA.

13. Comparison Both CORBA and HLA are concerned with legacy applications, possibly in different languages. C++, Ada, Java, etc. RMI keeps to single language, now has common interface with CORBA HLA is more simulation specific, whereas CORBA and RMI are designed for general applications. HLA’ s notion of transfer of object ownership is unique. RMI uses TCP/IP, CORBA uses IIOP, HLA leaves the choice to RTI developers/vendors (which is considered a disadvantage to interoperability). RMI has unique security Manager.