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:

Tipo de documento:
Conference Object
Estado:
Acceso restringido
Áreas de conocimiento:
- Modelo matemático
- Ingeniería de sistemas
Áreas temáticas de Dewey:
- Ciencias de la computación

Objetivos de Desarrollo Sostenible:
- ODS 9: Industria, innovación e infraestructura
- ODS 17: Alianzas para lograr los objetivos
- ODS 8: Trabajo decente y crecimiento económico
