5 Basic Models



 5.1 Devs Model

A devs class has basic methods for handling time information (last time, next time), output message, and port information such as input ports and output ports.
 

Since this class provides many services needed in devs environment, numerous methods are defined to provide polymorphism for the children classes. The inject method is useful to send input to specific models. The make_content method creates the content for message.
   

5.2 Atomicbase and Atomic Models

An atomicbase model has a simulation engine for atomic models, and also has the sigma variable. An atomic model which inherits from class atomicbase includes the phase variable. In million cell models, when we don't need a phase variable, we can use atomicbase model. The following methods handle sigma and phase variables.  

5.3 Cellbase and Cell Models
Cellbase and cell classes have an address data structure as an attribute. They are used to represent large numbers of similar models called cells which communicate with each other in the same, uniform manner, such as in cellular spaces. Coupling information is applied all the cells in the same way. For example, the coupling "out" port to "in" port applies any time one cell sends to another. These models use methods handling the address to recognize source and destination.

5.4 Coupled Models

Coupled models is the major class which embodies the hierarchical model composition constructs of the DEVS formalism. Digraph models, block models, and digcell models are specializations which enable specification of coupled models in specific ways. A coupled model is defined by specifying its component models, called its components, and the coupling relations which establish the desired communication links.

A coupled model tells how to couple several component models together to form a new model. It can itself be employed as a component in a larger coupled model, thus giving rise to hierarchical construction. A coupled model contains the following information:

5.4.1 Instance Variables

Instance variables in coupled models are defined as follows and are initialized by the constructor:
  • Components

  •  
    Figure 14 Components data structure

     

    The components variable keeps component information. In Figure 14, the coupled model (ef-m) has 3 components: genr, proc, and transd. To add compoments we use "add_component";

  • Coupling

  • As the Coupling variable holds an instance of relation (derived class, couprel), each pair has a set of source and destination pairs to keep the coupling relationships among a coupled model and its components. Figure 15 represents the data structure for the Coupling variable. The source part, the first two columns, keeps the source (ef-m) followed by port ("start" or "stop") of the source object. The destination part, remaining two columns, consists of the destination (genr) and port ("in" or "end") of the destination object.


     
    Figure 15 coupling data structure

     
    External input coupling couples the input ports of a coupled model to the input ports of its components. Likewise, external output coupling couples the output ports of the components to output ports of the coupled model. Internal coupling couples output ports of components to input ports of other components. We use "add_coupling" to provide coupling information;

  •  Comp_map

  • Comp_map, shown in Figure 16, is a function having (component, unique_id) pairs. Unique_id is assigned to each component in the coupled model so that its mailbox has unique integer id.
     
  • Imminents

  • The imminents variable keeps the information of the components in which next output events should occur. To get the imminent information, the coupled model asks which of the components have the next global event time (Figure 13).
     

    Figure 16 comp_map structure
     

    5.4.2 Convert_input()

    When messages come into the system from outside, the destination of the messages must be changed every time they descend down the hierarchical instances in the model. Convert_input() uses the external input coupling (in which the external input of the coupled model goes to external input of the components). An input port of a coupled model can be connected to one or more input ports of the components. Using the information in the coupling relation, convert_input() translates the destination object and port name to those of each related component (Figure 17).

     
    Figure 17 Convert Input Function of Coupled model