Research on the possibility of the bee colony algorithm for determining the topology of the wireless network at the marshalling yard

Nazarova, D.

Research on the possibility of the bee colony algorithm for determining the topology of the wireless network at the marshalling yard

Файли

Black_Sea_Science_Proc_2020_Nazarova.pdf(4.67 MB)

Дата

2020

Автори

Nazarova, D.

Анотація

For railway marshalling yards of different power (low, medium, high), an optimal number of wireless base stations and their location were determined on a Python program based on a bee colony algorithm. Program input: marshalling yard parameters (area, number of clients); wireless network parameters (coverage radius and number of base station clients); parameters of the algorithm (number of bees, number of attempts). For example, to connect 300 clients at the medium-power marshalling yard, 93 base stations with a coverage radius of 50 m are required. The quality of solutions depends heavily on the choice of parameters of the bee colony algorithm. It is determined that increasing the number of bees (from 10 to 50) and the number of attempts to find the optimal bee solution (from 10 to 50) leads to an improvement in the quality of the optimal solution (reducing the number of base stations by an average of 6.5% and 9.3%, respectively). In addition, increasing the number of bees by 5 times leads to a decrease in the search time of the bee optimal solution by an average of 1.8 times, while increasing the number of attempts to find the optimal bee solution by 5 times will increase the search time of the solution by an average of 2.14 times. In particular, for the high-power marshalling yard, when the base stations coverage radius is doubled (from 50 to 100 m), their number decreases approximately twice (from 136 to 64), while the search time for the bee optimal solution is increased by 2.5 times (from 8.4 to 20.6 s).

Опис

Nazarova D. Research on the possibility of the bee colony algorithm for determining the topology of the wireless network at the marshalling yard / D. Nazarova ; supervisor V. Pakhomova // Black Sea Science 2020: proc. of the Intern. Competition of Student Scientific Works / Odessa National Academy of Food Technologies; eds. B. Yegorov, M. Mardar [et al.]. – Odessa: ONAFT, 2020. – P. 325–339 : tabl., fig. – Ref.: 19 tit.