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    <journal-meta />
    <article-meta>
      <title-group>
        <article-title>Automated system for modeling traffic of multiservice networks</article-title>
      </title-group>
      <contrib-group>
        <contrib contrib-type="author">
          <string-name>B.Ya. Likhttsinder</string-name>
          <xref ref-type="aff" rid="aff0">0</xref>
        </contrib>
        <contrib contrib-type="author">
          <string-name>A.V. Kharkovsky</string-name>
          <xref ref-type="aff" rid="aff0">0</xref>
        </contrib>
        <contrib contrib-type="author">
          <string-name>S.Yu. Antsinov</string-name>
          <xref ref-type="aff" rid="aff0">0</xref>
        </contrib>
        <aff id="aff0">
          <label>0</label>
          <institution>Povolzhsky State University of Telecommunications and Informatics</institution>
          ,
          <addr-line>LevTolstoy street, 23, 443010, Samara</addr-line>
          ,
          <country country="RU">Russia</country>
        </aff>
      </contrib-group>
      <pub-date>
        <year>2017</year>
      </pub-date>
      <fpage>68</fpage>
      <lpage>71</lpage>
      <abstract>
        <p>The paper deals with the system for modeling parameters of traffic of multiservice networks, developed by the authors on the basis of Visual Studio, in C#. The system is based on the principles of interval method of flow analysis general systems of mass service. The results of comparison with similar products are presented. Software structural scheme and its performance are analyzed with examples of video and Poisson traffic stream. The possibility of approximation coefficients determination is given which are coefficients of generalized KhinchinPollaczek formula. As a result, for real traffic, average size of the queues were determined by using approximation coefficients applications at different load factors, as well as a number of other characteristics of multiservice traffic, such as dispersion, correlation, probability distribution.</p>
      </abstract>
      <kwd-group>
        <kwd>modeling</kwd>
        <kwd>multi-service network</kwd>
        <kwd>generalized Khinchin-Pollaczek formula</kwd>
        <kwd>traffic analysis</kwd>
        <kwd>packets</kwd>
      </kwd-group>
    </article-meta>
  </front>
  <body>
    <sec id="sec-1">
      <title>1. Introduction</title>
    </sec>
    <sec id="sec-2">
      <title>2. Software structure</title>
      <p>The structural scheme of Fig. 1 shows the algorithm of the program.</p>
    </sec>
    <sec id="sec-3">
      <title>3. Analysis of software correctness</title>
      <p>
        The basis of this software lay down the methods of analysis and processing algorithms of traffic, given in [
        <xref ref-type="bibr" rid="ref3">3</xref>
        ], [
        <xref ref-type="bibr" rid="ref8">8</xref>
        ], [
        <xref ref-type="bibr" rid="ref9">9</xref>
        ]. To
assess the correct operation of software, a comparison was made between previously defined video streaming characteristics and
characteristics obtained from the analysis using the developed system. Below are the graphs obtained using developed system
analysis.
      </p>
      <p>
        The resulting graphs Fig. 2 and Fig. 3 are completely analogous to those examined in [
        <xref ref-type="bibr" rid="ref6">6</xref>
        ].
      </p>
      <p>The developed program was tested on Poisson traffic stream. In Fig. 4 demonstrated the graphs of dependencies of average value
and dispersion of the packets at intervals corresponding to different load factors of the system ρ. Both graphs are linear and
completely coincide, which is typical for Poisson traffic stream.</p>
    </sec>
    <sec id="sec-4">
      <title>4. Main features of the program</title>
      <p>Interface of the main program window consists of three blocks (Fig. 5):
1. Panel with flows.
2. Graph.
3. Setting bar of graph display.</p>
      <p>Data Science / B.Ya. Likhttsinder, A.V. Kharkovsky, S.Yu. Antsinov</p>
      <p>Examine each block in more details. The system provides the addition to a flow, using the "Add flow" button in the user
interface (Fig. 6).</p>
      <p>The user has the ability to specify a name of the flow and limit the number of packets of input traffic. The flow file must
contain information about the arrival times of packets or the intervals between packets.</p>
      <p>The program is not limited to the number of flows and packets therein. You can add multiple flows and compare their
characteristics, as shown in Fig. 5. After addition, the title of the flow is displayed on the panel (Fig. 7).</p>
      <p>The graphical representation of flow consists of three “buttons”:
1. Remove the flow from the panel.
2. Display setting.
3. Shading the flow from the general graph.</p>
      <p>In the display settings dialog box of the graph (Fig. 8), a user can select traffic characteristic to build, tune in the graph (color,
thickness and line type). When you click “OK”, graphical representation of the flow changes, and selected characteristic is built.</p>
      <p>The graph displayed in the Cartesian coordinate system is automatically scaled by the size of the window. The user has the
ability to scale the graph, shift the plane graphics using the mouse, and reset these values and determine the coordinates of the
point on the graph using the context menu (right mouse button). You can adjust the grid, sweep along the axes in the panel for
setting the graph display.</p>
    </sec>
    <sec id="sec-5">
      <title>5. Determination of approximation coefficients</title>
      <p>
        The main practical benefit of this software is the ability to determine the coefficients of the approximation of the numerator of
generalized Khinchin-Pollaczek formula [
        <xref ref-type="bibr" rid="ref5">5</xref>
        ], [
        <xref ref-type="bibr" rid="ref6">6</xref>
        ], [
        <xref ref-type="bibr" rid="ref8">8</xref>
        ]. It is necessary to build a characteristic of numerator dependence mE (ρ) of
Khinchin-Pollaczek formula on the load factor ρ and to approximate it by a function F( )  (   0 )2   (   0 ) .
      </p>
      <p>By changing the coefficients α, β and  0 , an approximation is made automatically, the results of which are shown in the
diagrams Fig. 9.
q( ) 
mE ( )</p>
      <p>The developed software can be used in the analysis of traffic of multiservice telecommunication networks. Further development
involves automatic collection of information about the flow and processing in real time, allowing to obtain average values of
coefficients of e generalized Khinchin-Pollaczek formula.</p>
    </sec>
  </body>
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