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Network Synthesis: Using Genetic Algorithms for Network Synthesis


  • Lipetsk State Pedagogical P. Semenov-Tyan-Shansky University, Lipetsk, Russian Federation


Objectives: The article deals with problem of creating the new systems of the Ethernet network optimal structure, considering a possibility to adjust such system in compliance with system administrator specification. Method: The main tasks of the research have been solved using as follows: graphs theory, queuing theory; large control systems theory; simulation modeling theory; genetic algorithms theory, structural and object-oriented programming methodology. Findings: In the present article an important scientific and technical problem associated with synthesis of the Ethernet network optimal structure is being solved. The following new research findings have been obtained: the modification of a genetic algorithm for topology synthesis of the Ethernet local network has been offered, in which compared to the analogues known, a simulation system is used as a utility function which enables to consider the user traffic effect on the Ethernet network characteristics at the evaluation of this structure variant. The methods of a parametric and structural optimization of the Ethernet local network have been developed. The unique methods of optimization of a structured cabling system of the Ethernet corporate network have been developed. Improvements: The results obtained are rather universal which enables to use them in different fields of the Ethernet network application: For quality improvement, reduction of value and time required for preparation of design solutions based on the Ethernet networks; in MetroEthernet; in Industrial Ethernet; in the networks different from the Ethernet standards for example, in virtual private networks or in the networks based on multi-protocol label switching MPLS.


Genetic Algorithm, Local Network Synthesis, Models.

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  • Blagodarov AV, Pylkin AN, Skudnev DM, Shibanov AP. Modeling and synthesis of the optimal Ethernet network structure. Moscow: Hot Line Telecom; 2014.
  • Pilinsky M, Rutkovskaya D, Rutkovsky L. Neural networks, genetic algorithms and fuzzy systems: translated from Polish by Rudinsky I.D. Moscow: Hot Line Telecom; 2013.


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