Abstract
Purpose. At present, the computer networks of the information and telecommunication system (ITS) of railway transport use the OSPF protocol, which does not allow taking into account several metrics when determining the optimal route. Therefore, there is a need to study the possibility of organizing routing in computer networks of rail transport ITS using a two-colonial ant algorithm. Methodology. According to the Two-ACO software model, created in the Python language based on the two-colonial ant algorithm, the optimal route in a computer network was determined. Two-ACO model inputs: computer network parameters (network adjacency matrix, number of routers); parameters of the ant algorithm (number of iterations; number of ants in the colony; number of elite ants; initial pheromone level; evaporation rate; parameter for adjusting the amount of pheromone deposition). Findings. The results of the Two-ACO model are presented in the form of graphs depicting the optimal paths: the criterion of the total delay on the routers (for the first colony of ants) and the number of hops (for the second colony of ants). Originality. According to the created Two-ACO software model for a computer network of 7 routers and 17 channels, a study of the time for determining the optimal path in a computer network by the number of ordinary and elite ants, evaporation rate and deposited pheromone was conducted. It is determined that it is enough to use the number of ants equal to the number of routers and have 2 elite ants in the colony, with 1000 iterations, evaporation rate from 0.2 to 0.7, and pheromone deposition by ants close to one. Practical value. Created Two-ACO software model using two colonies of ants on the following criteria: the total delay on the routers (for the first colony of ants) and the number of hops that make up the route (for the second colony of ants) allows you to parallel determine the optimal routes in a computer network of railway transport. It is estimated that for a computer network of 15 routers and 17 channels, it is sufficient to have 30 agents (two ants on top), the value of the pheromone deposited by the agents is close to one, and the evaporation rate is 0.4.
Highlights
У цій роботі ми передбачаємо визначити оптимальний маршрут у комп’ютерній мережі залізничного транспорту за двоколоніальним мурашиним алгоритмом, для програмної реалізації якого обрано мову Phyton, а також з’ясувати параметри мурашиного алгоритму на основі створеної моделі
According to the Two-ACO software model, created in the Python language based on the two-colonial ant algorithm, the optimal route in a computer network was determined
Summary
У цій роботі ми передбачаємо визначити оптимальний маршрут у комп’ютерній мережі залізничного транспорту за двоколоніальним мурашиним алгоритмом, для програмної реалізації якого обрано мову Phyton, а також з’ясувати параметри мурашиного алгоритму на основі створеної моделі. Вхідні параметри моделі: n – кількість маршрутизаторів; graph – матриця суміжності мережі; iteration – кількість ітерацій; ants – кількість мурах у колонії; elite_ants – кількість елітних мурах; phero_lvl – початковий рівень феромону; ro – коефіцієнт випаровування; q – параметр для регулювання величини відкладення феромону. За програмною моделлю «Two–ACO» проведені дослідження кількості ітерацій, необхідних для пошуку оптимального шляху, за параметрами алгоритму.
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