ORGANIZING WIRELESS NETWORK AT MARSHALLING YARDS USING THE BEE METHOD

Authors

DOI:

https://doi.org/10.15802/stp2020/204005

Keywords:

marshalling yard, wireless network, base station (BS), coverage radius, bee method, bees, attempts, search time

Abstract

Purpose. In general, today wireless networks are widely used as an alternative to wired, allowing you to connect multiple devices, both among themselves in the local and global Internet. However, at the present stage in Ukraine there is no widespread use of a wireless network at rail transport, therefore it is advisable to conduct research on the deployment of such a network, in particular, at a marshalling yard. Methodology. Using LocBS‑BeeCol program model written in Python according to the bee colony algorithm the optimal number of base stations (BS) of the wireless network and their location at the marshalling yards was determined, as well as research on the bee algorithm parameters was conducted. Input data of the LocBS‑BeeCol model are as follows: marshalling yard parameters (area, number of clients that need to be connected to base stations); wireless network parameters (base station coverage radius, maximum number of clients for one base station); parameters of the bee colony algorithm (number of scout bees, number of attempts to find the optimal solution using one bee). Findings. For marshalling yards of various capacities (small, medium and high), the optimal number of base stations of the wireless network was obtained with restrictions on the coverage radius of the base station and the number of clients connected to it. Thus, for example, to connect 300 clients at medium-sized marshalling yards with an area of 2500x500 m2, 93 base stations with a coverage radius of 50 m are needed. Originality. The quality of the obtained solutions significantly depends on the choice of the bee colony algorithm parameters. A study of the base stations number of the wireless network and search time for finding the optimal solution for different number of bees and the number of attempts to find the optimal solution using the bee for marshalling yards of various capacities was carried out. It was determined that an increase in the number of bees (from 10 to 50) and the number of attempts to find the optimal solution by a bee (from 10 to 50) improves the quality of the optimal solution (decrease in the number of base stations by an average of 6.5% and 9.3%), respectively. In addition, increase in the bee number (from 10 to 50) reduces the search time for the optimal solution by bees by an average of 1.8 times, while increase in the number of attempts to find the optimal solution by a bee (from 10 to 50) will increase search time for the optimal solution on average 2.14 times. Practical value. An algorithm and its software implementation have been developed, which make it possible to determine the required number of base stations and their location when deploying a wireless network at a marshalling yards. For marshalling yards with high capacity, when the coverage radius of the base station is doubled (from 50 to100 m), their number decreases by about half (from 136 to 64), while the time for finding the optimal solution by bees increases by 2.5 times (from 8.4 to 20.6 s).

Author Biographies

V. M. Pakhomova, Dnipro National University of Railway Transport named after Academician V. Lazaryan

Dep. «Electronic Computing Machines», Dnipro National University of Railway Transport named after Academician V. Lazaryan, Lazaryana St., 2, Dnipro, Ukraine, 49010, tel. +38 (056) 373 15 89, e-mail viknikpakh@gmail.com

D. I. Nazarova, Dnipro National University of Railway Transport named after Academician V. Lazaryan

Dep. «Electronic Computing Machines», Dnipro National University of Railway Transport named after Academician V. Lazaryan, Lazaryana St., 2, Dnipro, Ukraine, 49010, tel.  +38 (056) 373 15 89, e-mail olkdi@outlook.com

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Published

2020-05-25

How to Cite

Pakhomova, V. M., & Nazarova, D. I. (2020). ORGANIZING WIRELESS NETWORK AT MARSHALLING YARDS USING THE BEE METHOD. Science and Transport Progress, (2(86), 60–73. https://doi.org/10.15802/stp2020/204005

Issue

Section

INFORMATION AND COMMUNICATION TECHNOLOGIES AND MATHEMATICAL MODELING