Revista: | Polibits |
Base de datos: | PERIÓDICA |
Número de sistema: | 000402939 |
ISSN: | 1870-9044 |
Autores: | Meghanathan, Natarajan1 |
Instituciones: | 1Jackson State University, Department of Computer Science, Jackson, Misisipi. Estados Unidos de América |
Año: | 2016 |
Periodo: | Ene-Jun |
Número: | 53 |
Paginación: | 5-21 |
País: | México |
Idioma: | Inglés |
Tipo de documento: | Artículo |
Enfoque: | Analítico |
Resumen en inglés | The focus of research in this paper is to investigate whether a random network whose degree sequence of the vertices is the same as the degree sequence of the vertices in a real-world network would exhibit values for other analysis metrics similar to those of the real-world network. We use the well-known Configuration Model to generate a random network on the basis of the degree sequence of the vertices in a real-world network wherein the degree sequence need not be Poisson-style. The extent of similarity between the vertices of the random network and real-world network with respect to a particular metric is evaluated in the form of the correlation coefficient of the values of the vertices for the metric. We involve a total of 24 real-world networks in this study, with the spectral radius ratio for node degree (measure of variation in node degree) ranging from 1.04 to 3.0 (i.e., from random networks to scale-free networks). We consider a suite of seven node-level metrics and three networklevel metrics for our analysis and identify the metrics for which the degree sequence would be just sufficient to generate random networks that have a very strong correlation (correlation coefficient of 0.8 or above) with that of the vertices in the corresponding real-world networks |
Disciplinas: | Ciencias de la computación, Matemáticas |
Palabras clave: | Redes, Matemáticas aplicadas, Probabilidad, Teoría de gráficas, Gráficas aleatorias |
Keyword: | Computer science, Mathematics, Networks, Applied mathematics, Probability, Graph theory, Random graphs |
Texto completo: | Texto completo (Ver PDF) |