Применение алгоритмов кластеризации для нахождения узлов спроса в сетях подвижной связи

In this article, the main algorithms of fuzziness clusterization for determination nodes of demand in mobile radio networks are compared. Identification of the most suitable algorithm for dynamic finding of nodes of demand in the conditions of abnormal zones of spatial-time changes of traffic transmitting (change of loading) is necessary for fast redistribution of a final radio-frequency resource of base stations, communication channels and computing powers of the provider. Each algorithm of an accurate and fuzzy clustering is the unique mathematical tool capable to analyze traffic on the modern telecommunication. At the same time, all algorithms have applicability boundaries in real implementation - the calculation speed, feature of a choice of boundaries of fuzziness, a choice of a metrics of belonging to some cluster and the whole range of heuristic criteria for the solution of real physical tasks. Comparing of two algorithms of a fuzziness clustering revealed that Fuzzy C-Means works quicker in the conditions of the increasing traffic, than Gustafsson-Kessel's algorithm. Simulation was made for two cases: increase of number of subscribers and increase of quantity of clusters in case of invariable number of subscribers.