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Types of computer modeling of technical devices and processes. Computer simulation

It is customary to distinguish between two types of modeling using computer technology:

  • 1) mathematical (logical-mathematical), in which modeling, including model construction, is carried out by means of mathematics and logic, as well as computer technology;
  • 2) simulation (software), in which the logical-mathematical model of the object under study is an algorithm for the functioning of the object, implemented in the form of a software package for a computer.

The listed types of modeling are not mutually exclusive and can be used when studying complex objects either simultaneously or in some combination. In addition, in a sense, conceptual and, say, structural-functional modeling are indistinguishable from each other, since the same block diagrams are special signs with established operations on them.

Computer modelling

Traditionally, computer modeling meant only simulation modeling. It can be seen, however, that in other types of modeling a computer can be very useful, with the exception of physical modeling, where a computer can also be used, but rather for the purpose of managing the modeling process. For example, in mathematical modeling, performing one of the main stages - constructing mathematical models based on experimental data - is currently simply unthinkable without a computer. In recent years, thanks to the development of the graphical interface and graphic packages, computer, structural and functional modeling has become widely used; the beginning has been made of using the computer even in conceptual modeling, where it is used, for example, in the construction of artificial intelligence systems.

Thus, it is clear that the concept of “computer modeling” is much broader than the traditional concept of “computer modeling” and needs to be clarified, taking into account today's realities.

Currently under computer model most often understood:

■ a conventional image of an object or some system of objects (or processes), described using interconnected computer tables, flowcharts, diagrams, graphs, drawings, animation fragments, hypertexts and displaying the structure and relationships between the elements of the object. We will call computer models of this type structural and functional;

■ a separate program, a set of programs, a software package that allows, using a sequence of calculations and graphical display of their results, to reproduce (simulate) the processes of functioning of an object, a system of objects, subject to the influence of various, usually random, factors on the object. We will further call such models imitation.

Computer modelling is a method for solving the problem of analysis or synthesis of a complex system based on the use of its computer model. In computer modeling, the main role is played by the computer and technology (more precisely, instrumental systems for the computer, computer technologies). For example, in simulation modeling (in the absence of a strict and formally written algorithm), the main role is played by technology and modeling tools that implement the same events and their sequences that are characteristic of the object, and in the conditions of running changes in controlled and uncontrolled influences.

The essence of computer modeling is to obtain quantitative and qualitative results from the existing model. Qualitative conclusions obtained from the results of the analysis make it possible to discover previously unknown properties of a complex system: its structure, dynamics of development, stability, integrity, etc. Quantitative conclusions are mainly in the nature of a forecast of some future or explanation of past values ​​of variables characterizing the system. Computer modeling for the generation of new information uses any information that can be updated using a computer.

When modeling, the computer plays a role:

■ an auxiliary tool for solving problems solved by conventional computing tools, algorithms, technologies;

■ means of setting and solving new problems that cannot be solved by traditional means, algorithms, and technologies;

■ means for constructing computer teaching and modeling environments;

■ modeling tools to obtain new knowledge;

■ “training” new models (self-learning models).

A type of computer modeling is computational experiment.

Computer modeling and computational experiment are becoming a new tool, a method of scientific knowledge, a new technology also due to the growing need to study not only linear mathematical models of systems.

The subject of computer modeling can be: the economic activity of a company or bank, an industrial enterprise, an information and computer network, a technological process, any real object or process, for example, the inflation process, and in general any complex system. The goals of computer modeling can be different, but most often modeling is, as noted earlier, the central procedure of system analysis, and by system analysis we will further understand a set of methodological tools used to prepare and make decisions of an economic, organizational, social or technical nature.

A computer model of a complex system should, if possible, reflect all the main factors and relationships that characterize real situations, criteria and limitations. The model should be universal enough to describe objects that are similar in purpose, if possible, and at the same time simple enough to allow the necessary research to be carried out at a reasonable cost.

All this suggests that modeling, considered as a whole, is not only an established science with an independent set of means for displaying phenomena and processes of the real world, but also to some extent an art.

Currently, the concept of “system” in science is not fully defined. Scientists have begun to study complex systems (CS).
In numerous literature on systems analysis and systems engineering, the following basic properties of complex systems are noted:

Property 1. Integrity and articulation.

A complex system is considered as an integral set of elements, characterized by the presence of a large number of interconnected and interacting elements.
The researcher has the subjective possibility of dividing the system into subsystems, the functioning goals of which are subordinated to the general goal of the functioning of the entire system (system focus). Purposefulness is interpreted as the ability of a system to carry out behavior (choice of behavior) in pursuit of achieving a specific goal under conditions of uncertainty and the influence of random factors.

Property 2. Connections.

The presence of significant stable connections (relationships) between elements and/or their properties, exceeding in power (strength) the connections (relationships) of these elements with elements not included in the given system (external environment).
By “connections” we mean a certain virtual channel through which matter, energy, and information are exchanged between elements and the external environment.

Property 3. Organization.

The property is characterized by the presence of a certain organization - the formation of significant connections of elements, the ordered distribution of connections and elements in time and space. When connections are formed, a certain structure of the system is formed, and the properties of the elements are transformed into functions (actions, behavior).

When studying complex systems, it is usually noted:

  • the complexity of the function performed by the system and aimed at achieving a given operating goal;
  • the presence of management, an extensive information network and intensive information flows;
  • the presence of interaction with the external environment and functioning under conditions of uncertainty and the influence of random factors of various natures.

Property 4. Integrative qualities.

The existence of integrative qualities (properties), i.e. such qualities that are inherent in the system as a whole, but not characteristic of any of its elements separately. The presence of integrative qualities shows that the properties of the system, although they depend on the properties of the elements, are not completely determined by them.
Examples of SS in the economic sphere are numerous: organizational - production system, enterprise; socio-economic system, for example region; and etc.
The methodology for SS research is system analysis. One of the most important tools for applied systems analysis is computer modelling.
Simulation modeling is the most effective and universal version of computer modeling in the field of research and control of complex systems.

Model is an abstract description of a system (object, process, problem, concept) in some form that is different from the form of their real existence.

Modeling is one of the main methods of cognition, is a form of reflection of reality and consists in clarifying or reproducing certain properties of real objects, objects and phenomena with the help of other objects, processes, phenomena, or with the help of an abstract description in the form of an image, plan, map, a set of equations, algorithms and programs.

During the modeling process there is always original(object) and model, which reproduces (models, describes, imitates) some features of an object.

Modeling is based on the presence of a variety of natural and artificial systems, differing both in purpose and physical embodiment, of similarity or similarity of certain properties: geometric, structural, functional, behavioral. This resemblance may be complete (isomorphism) and partial (homomorphism).

The study of modern SS suggests various model classes. The development of information technology can be interpreted as the possibility of implementing models of various types within information systems for various purposes, for example, information systems, image recognition systems, artificial intelligence systems, decision support systems. These systems are based on models of various types: semantic, logical, mathematical, etc.

Let's give a general classification of main types of modeling:

  • conceptual modeling– representation of the system using special signs, symbols, operations on them, or using natural or artificial languages;
  • physical modeling– the modeled object or process is reproduced based on the similarity ratio resulting from the similarity of physical processes and phenomena;
  • structural-functional modeling– models are diagrams (graphs, block diagrams), graphs, diagrams, tables, drawings with special rules for their combination and transformation;
  • mathematical (logical-mathematical) modeling– the construction of the model is carried out using mathematics and logic;
  • simulation (software) modeling– in this case, the logical-mathematical model of the system under study is an algorithm for the functioning of the system, implemented in software on a computer.

These types of modeling can be used independently or simultaneously, in some combination (for example, almost all of the listed types of modeling or individual techniques are used in simulation modeling). For example, simulation modeling includes conceptual (in the early stages of the formation of a simulation model) and logical-mathematical (including artificial intelligence methods) modeling to describe individual subsystems of the model, as well as in procedures for processing and analyzing the results of a computational experiment and decision making. The technology for conducting and planning a computational experiment with appropriate mathematical methods was introduced into simulation from physical (experimental field or laboratory) modeling. Finally, structural-functional modeling is used both to create a stratified description of multi-model complexes and to form various diagrammatic representations when creating simulation models.

The concept of computer modeling is interpreted more broadly than the traditional concept of “computer modeling”. Let's bring him.

Computer modelling is a method for solving problems of analysis or synthesis of a complex system based on the use of its computer model.

Computer simulation can be thought of as:

  • math modeling;
  • simulation modeling;
  • stochastic modeling.

Under the term “computer model” understand a conventional image of an object or some system of objects (or processes), described using equations, inequalities, logical relationships, interconnected computer tables, graphs, charts, graphs, drawings, animation fragments, hypertexts, etc. and displaying the structure and relationships between the elements of the object. Computer models described using equations, inequalities, logical relationships, interconnected computer tables, graphs, charts, graphs will be called mathematical. Computer models described using interconnected computer tables, graphs, diagrams, graphs, drawings, animation fragments, hypertexts, etc. and displaying the structure and relationships between the elements of the object, we will call structural and functional;

Computer models (a separate program, a set of programs, a software package), allowing, using a sequence of calculations and graphical display of the results of its work, to reproduce (simulate) the processes of functioning of an object (system of objects) subject to the influence of various, usually random, factors on the object, we'll call imitation.

The essence of computer modeling consists in obtaining quantitative and qualitative results on the existing model. Qualitative results analysis reveals previously unknown properties of a complex system: its structure, dynamics of development, stability, integrity, etc. Quantitative findings mainly have the nature of an analysis of an existing system or a forecast of future values ​​of some variables. The ability to obtain not only qualitative, but also quantitative results is a significant difference between simulation modeling and structural-functional modeling. Simulation modeling has a number of specific features.

The methodology of computer modeling is system analysis(direction of cybernetics, general systems theory), in which the dominant role is given to systems analysts. In contrast to mathematical modeling on a computer, where the methodological basis is: operations research, the theory of mathematical models, decision theory, game theory, etc.

The central procedure of system analysis is the construction of a generalized model that reflects all the factors and relationships of the real system. The subject of computer modeling can be any complex system, any object or process. The categories of goals can be very different. The computer model must reflect all the properties, main factors and relationships of a real complex system, criteria, and limitations.

Computer modelling offers a set of methodological approaches and technological tools used to prepare and make decisions in various areas of research.

Choosing a modeling method to solve a given problem or study a system is an urgent task that a systems analyst must be able to cope with.

For this purpose, we will clarify the place of simulation models and their specificity among models of other classes. In addition, let us clarify some concepts and definitions that a systems analyst deals with during the modeling process. To this end, consider procedural and technological scheme for constructing and researching models of complex systems. This diagram (shown on page 6) includes the following determination steps, characteristic of any modeling method:

  1. Systems (subject, problem area);
  2. Modeling object;
  3. Purpose of models;
  4. Requirements for models;
  5. Forms of presentation;
  6. Type of model description;
  7. The nature of the model implementation;
  8. Model research method.

The first three stages characterize the object and purpose of the study and practically determine the next stages of modeling. In this case, the correct description of the object and the formulation of the purpose of modeling from the subject area of ​​research become of great importance.

Subject (problem) area. Study of various systems: mathematical, economic, production, social, queuing systems, computing, information and many others.

The model must be built purposefully. A goal-oriented model is a substitute for reality with the degree of abstraction necessary for the goal. That is, the model, first of all, must reflect those essential properties and those aspects of the modeled object that are determined by the task. At the same time, it is important to correctly identify and formulate the problem, to clearly define the purpose of the research carried out using modeling.

Model requirements. Modeling is associated with solving real problems and it is necessary to be sure that the modeling results reflect the true state of affairs with a sufficient degree of accuracy, i.e. the model is adequate to reality.

A good model must satisfy some generally accepted requirements. This model should be:

  • adequate;
  • reliable;
  • simple and user-friendly;
  • purposeful;
  • convenient to manage and handle;
  • functionally complete in terms of the ability to solve main problems;
  • adaptive, allowing you to easily move to other modifications or update data;
  • allowing for change (during operation it may become more complex).

Depending on the target orientation of the model, special requirements are specified for it. The most characteristic are: integrity, reflection of information properties, multi-level, multiplicity (multi-model), extensibility, universality, feasibility (the real possibility of constructing the model itself and its research), realizability (for example, on a computer, the possibility of materializing the model in the form of a real system in design tasks ), efficiency (the costs of time, labor, material and other types of resources for building models and conducting experiments are within acceptable limits or justified). The significance or priority of the requirements for the model directly follows from the purpose of the model. For example, in research problems, management problems, planning and description, an important requirement is the adequacy of the model of objective reality. In problems of design and synthesis of unique systems, an important requirement is the feasibility of the model, for example, in a CAD system or a decision support system (DSS).

The purpose of modeling and setting the requirements for the model determine model presentation form.

Any model (before becoming an objectively existing object) must exist in mental form, be constructively developed, translated into symbolic form and materialized. Thus, three forms of model presentation can be distinguished:

  • mental(images);
  • iconic(structural diagrams, descriptions in the form of oral and written presentation, logical, mathematical, logical-mathematical constructions);
  • material(laboratory and operational mock-ups, prototypes).

A special place in modeling is occupied by iconic, in particular logical, mathematical, logical-mathematical models, as well as models recreated based on descriptions compiled by experts. Sign models are used to model a variety of systems. This direction is associated with the development of computing systems. We will limit ourselves to them in further consideration.

The next stage of the procedural scheme is choosing the type of description and
building a model. For iconic forms, such descriptions can be:

  • relation and predicate calculus, semantic networks, frames, artificial intelligence methods, etc. - for logical forms.
  • algebraic, differential, integral, integral-differential equations, etc. - for mathematical forms.

Nature of implementationthere are iconic models:

  • A analytical(for example, a system of differential equations can be solved by a mathematician on a piece of paper);
  • machine(analog or digital);
  • physical(automatic).

In each of them, depending on the complexity of the model, the purpose of the modeling, the degree of uncertainty in the characteristics of the model, there may be different methods of conducting research (experiments), i.e., research methods. For example, in analytical research various mathematical methods are used. In physical or full-scale modeling, an experimental research method is used.

Analysis of current and promising methods of machine experimentation allows us to highlight computational, statistical, simulation and self-organizing research methods.

Computational (mathematical) modeling used in research mathematical models and comes down to their machine implementation with different numerical input data. The results of these implementations (calculations) are presented in graphical or tabular forms. For example, a classic scheme is a machine implementation of a mathematical model, presented in the form of a system of differential equations, based on the use of numerical methods, with the help of which the mathematical model is reduced to an algorithmic form, implemented programmatically on a computer, and calculations are carried out to obtain the results.

Imitation modeling is characterized by a high degree of generality, creates the prerequisites for the creation of a unified model, easily adaptable to a wide class of problems, and acts as a means for integrating models of different classes.

Computer modeling is a method for solving problems of analysis or synthesis of a complex system based on the use of its computer model.

Computer simulation can be thought of as:

math modeling;

simulation modeling;

stochastic modeling.

The term “computer model” is understood as a conventional image of an object or some system of objects (or processes), described using equations, inequalities, logical relationships, interconnected computer tables, graphs, diagrams, graphs, drawings, animation fragments, hypertexts, etc. and displaying the structure and relationships between the elements of the object. Computer models described using equations, inequalities, logical relationships, interconnected computer tables, graphs, charts, graphs will be called mathematical. Computer models described using interconnected computer tables, graphs, diagrams, graphs, drawings, animation fragments, hypertexts, etc. and displaying the structure and relationships between the elements of the object, we will call it structural-functional;

Computer models (a separate program, a set of programs, a software package), allowing, using a sequence of calculations and graphical display of the results of its work, to reproduce (simulate) the processes of functioning of an object (system of objects) subject to the influence of various, usually random, factors on the object, we will call them imitative.

The essence of computer modeling is to obtain quantitative and qualitative results using the existing model. Qualitative results of the analysis reveal previously unknown properties of a complex system: its structure, dynamics of development, stability, integrity, etc. Quantitative conclusions are mainly in the nature of an analysis of an existing system or a forecast of future values ​​of some variables. The ability to obtain not only qualitative, but also quantitative results is a significant difference between simulation modeling and structural-functional modeling. Simulation modeling has a number of specific features. In each of them, depending on the complexity of the model, the goals

modeling, the degree of uncertainty of the model characteristics, can

there are different ways of conducting research

(experiments), i.e., research methods. For example, with analytical

Various mathematical methods are used in the study. In physical or full-scale modeling, an experimental research method is used.

Analysis of current and promising methods of machine experimentation allows us to distinguish between computational, statistical, simulation and self-organizing research methods.

Computational (mathematical) modeling is used in the study of mathematical models and comes down to their computer implementation with various numerical input data. The results of these implementations (calculations) are presented in graphical or tabular forms. For example, a classic scheme is a machine implementation of a mathematical model, presented in the form of a system of differential equations, based on the use of numerical methods, with the help of which the mathematical model is reduced to an algorithmic form, the software is implemented on a computer, and calculations are carried out to obtain the results.

Simulation modeling is characterized by a high degree of generality, creates the prerequisites for the creation of a unified model, easily adaptable to a wide class of problems, and acts as a means for integrating models of different classes.

computer modeling as the main method of analysis, forecasting and planning of economic systems.

A computer model, or a numerical model, is a computer program running on a separate computer, supercomputer or many interacting computers (computing nodes), implementing an abstract model of a system. Computer models have become a common tool for mathematical modeling and are used in physics, astrophysics, mechanics, chemistry, biology, economics, sociology, meteorology, other sciences and applied problems in various fields of radio electronics, mechanical engineering, automotive industry, etc. Computer models are used to obtain new knowledge about the modeled object or to approximate the behavior of systems that are too complex for analytical study.

Computer modeling is one of the effective methods for studying complex systems. Computer models are easier and more convenient to study due to their ability to carry out the so-called. computational experiments, in cases where real experiments are difficult due to financial or physical obstacles or may give unpredictable results. The logic and formalization of computer models makes it possible to identify the main factors that determine the properties of the original object under study (or an entire class of objects), in particular, to study the response of the simulated physical system to changes in its parameters and initial conditions.

The construction of a computer model is based on abstraction from the specific nature of the phenomena or the original object being studied and consists of two stages - first the creation of a qualitative and then a quantitative model. Computer modeling consists of conducting a series of computational experiments on a computer, the purpose of which is to analyze, interpret and compare the modeling results with the real behavior of the object under study and, if necessary, subsequent refinement of the model, etc.

Comparative computer animation of two building models

The main stages of computer modeling include:

statement of the problem, definition of the modeling object;

development of a conceptual model, identification of the main elements of the system and elementary acts of interaction;

formalization, that is, the transition to a mathematical model; creating an algorithm and writing a program;

planning and conducting computer experiments;

analysis and interpretation of results.

There are analytical and simulation modeling. In analytical modeling, mathematical (abstract) models of a real object are studied in the form of algebraic, differential and other equations, as well as those involving the implementation of an unambiguous computational procedure leading to their exact solution. In simulation modeling, mathematical models are studied in the form of an algorithm(s) that reproduces the functioning of the system under study by sequentially performing a large number of elementary operations.


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FEDERAL STATE AUTONOMOUS EDUCATIONAL INSTITUTION OF HIGHER PROFESSIONAL EDUCATION

"Immanuel Kant Baltic Federal University"

INSTITUTE OF TRANSPORT AND TECHNICAL SERVICE

KALININGRAD TECHNICAL COLLEGE

COURSE WORK

BY COMPUTER SIMULATION

"MODELINGcomputer»

CompletedA:

Baturina Evgenia

Group: 2KS-1

Checked:

Ampilogov D.V.

KALININGRAD 2014

Introduction

1. Formalization of the conceptual model

1.1 Definition of model parameters and variables

1.2 Definition of the model time unit

1.3 Definition of the law of system functioning

2. Task

2.1 Determination of computing requirements

2.2 Selecting simulation software

2.3 Functional structure of the GPSS language

2.4 Program code

Conclusion

List of used literature

Introduction

Modern times dictate a new rhythm of life, modifying all areas of human activity. Today it is impossible to imagine almost any production process or scientific research process without the use of computer modeling. Like any other modeling, computer modeling is aimed at creating prototypes of various kinds of objects, processes or systems, in particular complex systems that depend on a set of interrelated and random factors. Computer modeling can significantly reduce the cost of conducting experiments, reduce the time required to create and analyze models, and also obtain the necessary results in a convenient form. An important feature of modern modeling is the use of various kinds of application packages aimed at modeling certain phenomena. Such software products, to some extent, are themselves the results of computer modeling and serve to optimize and visualize the processes of modeling specific objects, systems and processes. There are various computer modeling environments that are characteristic for modeling and analyzing specific problems in specific areas of science and technology. In my work, I used the GPSS environment, which I consider the most convenient, easy to use and understand, as well as the easily accessible syntax of the language I chose. The course work will present the solution to the problem, as well as the main aspects related to the modeling of modern computers. It is also necessary to remember that the main goal that stood before completing the course work was to consolidate the material received from lecture classes. A special feature of this work is the implementation of the task on a personal computer in the GPSS software environment.

1. Forconceptual model malization

computer simulation model abstract

Before you start looking at a model, you need to determine the type of model. Therefore, determine the type of modeling. This course work will examine the model from the point of view of a systems approach.

A model is not an absolute copy of the original; it already presupposes a certain degree of abstraction.

Currently, the concept of a model has expanded; it includes both real and so-called ideal ones. models, for example mathematical models. The properties of a model are possessed by such forms of scientific ideas about the world as laws, hypotheses, theories.

Any model - ideal or material, used for scientific purposes, in production or in everyday life - carries information about the properties and characteristics of the original object (the original object), which are essential for the problem being solved by the subject. A model is a physical or abstract object that reflects, to one degree or another, the processes in the system under study.

A program written on a computer is a formalized representation of the data processing process. A formalized model is also a set of signs, because the machine understands only this representation of information. A computer program is a model for processing various types of information.

Building a model is one of the main tasks that requires analysis and basic information about the purpose of the study. A model is built to evaluate its properties, response to the environment, etc. Most models are based on hypotheses and assumptions, from which the idea of ​​building a model then follows.

In different areas of science and human activity, processes are studied from different points of view and, accordingly, different models are used.

Modeling languages ​​can be divided into artificial and natural. Artificial languages ​​are created by humans when there is a need to create special purposes or to divide people into groups. Natural languages ​​develop unexpectedly and over a period of time.

Simulation starts:

First stage

1) Statement of the problem (what do you want to get as a result of modeling. what is your goal when starting work)

2) Description of the task (specify or put the task within a certain framework)

3) Study of the characteristics of the object (it is necessary to monitor the consequences that the model can have on the environment and humans)

4) What impact must be made on the object being studied so that its parameters satisfy the given condition.

Second phase

1) Development of a diagram for this model (scheme R)

Considering a model instead of a system entails simplification.

The model is required for:

1. Understanding the principle of operation of the device, its structure, consider

how the model develops under different conditions and its behavior under these conditions, as well as see the main properties.

2. You need to learn how to control the model.

3. Predict the consequences of the model, and also consider what consequences the object that interacted with this model will have.

Basic properties of the abstract model:

1) Finiteness - the model must have a final result.

2) Simplification - the model should be simple and easily reproducible.

3) Purposeful - any model must have a goal, because the model represents part of the system.

4) Approximateness - the reality of all actions that occur with the model or their approximation.

5) Completeness - the model must take into account all the basic concepts of the system to obtain a more accurate result.

6) Information content - in the model, it is necessary to contain all the necessary information about the system and, if possible, obtain information from other sources.

8) Stability - the model must describe the behavior of the system under various conditions, even if the conditions are unstable.

9) Visualization - the main properties and applications of the system that needs to be written.

10) Integrity - the model implements an abstract system and therefore must be a single whole, indivisible.

11) Closedness - take into account the cyclical nature of the system, relationships and connections.

12) Availability.

13) Adaptability - the model needs to adapt to any outcome.

14) Manufacturability for reproducing a model describing a specific system.

15) Evolvability - opportunities for development and increasing the level of complexity.

16) Controllability - the model must have at least one change parameter.

One of the main properties of the model is its adequacy. This has various dependencies:

a) the degree of completeness and reliability of information about the system under study;

b) degree of detail of the model;

c) the correctness of model parameterization, which means establishing a correspondence between the parameters of the system and the model;

d) the level of training and experience of the researcher himself.

Formalization - displaying the results of thinking in precise concepts or statements.

A structural model of a system is also called a structural diagram. The structural diagram reflects the composition of the system and its internal connections.

A conceptual model is a model represented by a set of concepts and connections between them that determine the semantic structure of the subject area under consideration or its specific object.

Most often, a conceptual model is presented in the form of an entity-relationship diagram, which will be given below. To understand how the model works, you need to build its diagram. At this stage there is a transition from a verbal description of the modeling object to its mathematical model. One of the main goals is to simplify the description of the system, to separate the system itself S from the external environment E and the selection of the main content of the model by discarding everything that is secondary from the point of view of the stated goal of modeling.

Let's construct a formal diagram (R-scheme) of a given computer system:

Figure No. 1 (R-scheme)

S-1 - network machine

S-2 - network machine

S-3 - network machine

O - queue

E - electronic computer (computer)

Before entering the computer, the source data must be queued (a data structure with a “first in, first out” access discipline to elements). And only then the data from the queue will enter the computer.

Data for the computer is prepared in the form of a package of control and defining cards, which is compiled according to a model diagram composed of standard symbols. The created GPSS program, working in interpretation mode, generates and transmits transactions from block to block. Each transaction transition is assigned to a specific point in system time.

1.1 Definitionmodel parameters and variables

Analysis of the development of the most complex technical systems allows us to conclude that computers are increasingly penetrating their structure. Computers become an integral, and often the main part of such systems. First of all, this applies to complex radio-electronic systems. Among them are various automatic systems, including automatic switching systems (electronic telephone exchanges), radio communication systems, radio telemetry systems, radar and radio navigation systems, and various control systems.

When constructing such systems, the principles and structures of the organization of computers and computer systems (CS) are largely used. A characteristic feature is the presence in the systems of several processors, combined in various ways into a specialized computer. At the same time, a transition is made from the “hard” logic of the functioning of technical systems to the universal “software” logic. Because of this, specialized system and application software plays an increasingly significant role in such systems, along with hardware.

To carry out the experiment, you will only need one personal computer without external devices. The experiment execution time is limited only by the access time to a personal computer.

Deterministic model - an analytical representation of a pattern, operation, etc., in which for a given totality input values ​​to output system, a single result can be obtained. To create a deterministic model of a given computing system, it is necessary to replace stochastic flows with their mathematical expectations:

The interval between user arrivals is 10 minutes

Job preparation time for 1st user 16 min

Job preparation time for the 2nd user 17 min

Job preparation time for the 3rd user 18 min

Time to complete a task on a computer 0.8 min

The probability of each user arriving is 0.33

1.2 Definition of a model time unit

Model time is a time that can be chosen at your discretion depending on the conditions of the problem.

In the original problem, the unit of model time (emd) must be taken to be the minimum real time interval. The minimum real time interval (emd) during which the system does not change its initial state. In the current problem, the model time is 0.1 min.

1.3 Determination of the law of system functioning

The operation of this computer system can be represented in the form of timing diagrams.

Figure No. 2 (dependence of model time Emd on incoming information from network machine S-1)

Figure No. 3 (dependence of model time Emd on incoming information from network machine S-2)

Figure No. 4 (dependence of model time Emd on incoming information from the network machine S-3)

Figure No. 5 (time dependence on how data enters the computer)

2. Exercise

The problem condition is shown in the figure:

Figure No. 6 (task condition)

2.1 Determining computing requirements

To solve the original problem, you will need one computer on which the GPSS program is installed. The time spent on solving the problem is limited by the time of access to the computer.

2.2 Selecting Simulation Software

To write the program, I chose the environment GPSS. The language used in this environment is called GPSS. GPSS (General Purpose

Simulation System) is a language that is used to model abstract systems and queuing systems (QS), as well as for the spatial movement of objects. Objects of the GPSS language are associated with a QS - a system that processes incoming requests. Requirements in the QS are serviced by servicing devices. These objects mentioned earlier are called transactions. Transactions can be created and deleted as needed to solve any problem. In any model, there are certain blocks, each of which is responsible for its own function. The function tells transactions where to move or move to get the final result. Data for the computer is prepared in the form of a package of control and defining cards, which is compiled according to a model diagram composed of standard symbols. The created GPSS program, working in interpretation mode, generates and transmits transactions from block to block. Each transaction transition is assigned to a specific point in system time.

2.3 Functional structure of the languageGPSS

I) The level is determined by a combination of basic functional objects such as:

Devices

Logic switch

Queue

Transactions;

II) Level - a block diagram of the model, composed of standard blocks between which transactions move.

1) Transactions are abstract moving elements that are analogues of various objects of the real world (messages, vehicles, people, parts, etc.) Transactions move according to the model, they can be created and destroyed.

By moving between model blocks in accordance with the modeling logic, transactions cause (and experience) various actions:

There may be delays at some points in the model (related to service, waiting in line),

Changing routes and directions of movement,

Creating a copy of transactions.

2) Devices model objects in which transaction processing can occur, which is time-consuming. Devices are analogues of QS channels (each device at a given time may be occupied by only one transaction). GPSS has the ability to check the status of the device.

3) Memory - intended for modeling objects with capacity. An analogy with multi-channel QS - memory can serve several transactions simultaneously. In this case, the transaction occupies a certain part of memory.

4) Logical switches - take the value on or off, allow you to change the paths of transactions in the model.

5) Queue. During the movement, transactions may be delayed at certain points in the model. If it is necessary to collect information about the length of the transaction queue and the transaction delay time, use the appropriate statistical objects.

6) Tables. The tables process statistical information and build a histogram of distributions for any variable.

2.4 Programcode

10 generate 100,500

40 release ustr1

50 transfer ,evm

100 generate 200,500

130 release ustr2

140 transfer ,evm

200 generate 300,500

230 release ustr3

300 evm seize ustr4

320 release ustr4

Table No. 1 presents the main blocks that were required as a result of writing the program:

Table No. 1

Program text