Network models, growth, dynamics, and failure


Abstract:

This paper reports on preliminary explorations, both empirical and analytical, of probabilistic models of large-scale networks. We first examine the structure of networks that grow by the addition of nodes and lines, using a class of connection rules motivated by considerations of distance and prior connectivity. Second, we examine the dynamic behavior of the binary influence model - a particular form of a more general model of networks in which each node has a status (for instance: normal, or failed) that behaves as a Markov chain, but with transitions that are influenced by the present status of each neighboring node. Some interesting influence model examples are analyzed, including one displaying a power-law relation between the frequency of a failure event and its extensiveness.

Año de publicación:

2001

Keywords:

    Fuente:

    scopusscopus

    Tipo de documento:

    Conference Object

    Estado:

    Acceso restringido

    Áreas de conocimiento:

    • Modelo matemático
    • Ingeniería de sistemas

    Áreas temáticas de Dewey:

    • Ciencias de la computación
    Procesado con IAProcesado con IA

    Objetivos de Desarrollo Sostenible:

    • ODS 9: Industria, innovación e infraestructura
    • ODS 17: Alianzas para lograr los objetivos
    • ODS 8: Trabajo decente y crecimiento económico
    Procesado con IAProcesado con IA