Abstract
We consider two types of random configuration graphs: with the power-law and with the Poisson vertex degree distributions. The parameters of these distributions are fixed. By simulations we estimate the probabilities of graph connectivity (when all graph vertices are joined into one connected component) in different graph types and their dependence on the graph size and the vertex degree distribution parameter.
Highlights
We consider two types of random configuration graphs: with the power-law and with the Poisson vertex degree distributions
By simulations we estimate the probabilities of graph connectivity in different graph types and their dependence on the graph size and the vertex degree distribution parameter
On the power-law random graph model of massive data networks // Performance Evaluation
Summary
We consider two types of random configuration graphs: with the power-law and with the Poisson vertex degree distributions. Соответственно, также имеют некоторое разнообразие, как в определении степеней вершин случайного графа, так и в установлении связей между этими вершинами. С увеличением размеров сетей и с ростом их разнообразия стало понятно, что для адекватного отражения топологии и функционирования таких сетей при построении их математических моделей недостаточно учитывать только распределение степеней вершин в соответствующей модели случайного графа, но необходимо также принимать в рассмотрение и другие не менее важные характеристики сети.
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