Indian Journal of Science and Technology
Year: 2016, Volume: 9, Issue: 46, Pages: 1-8
Vladimir Sergeyevich Ziyautdinov, Dmitry Mikhaylovich Skudnev* and Mikhail Yuryevich Smirnov
*Author for correspondence
Dmitry Mikhaylovich Skudnev Lipetsk State Pedagogical P. Semenov-Tyan-Shansky University, Lipetsk, Russia; [email protected]
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.
Keywords: Genetic Algorithm, Local Network Synthesis, Models
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