A Simple Model of Scale-free Networks Driven by both Randomness and Adaptability
arXiv:physics/0409061
Abstract
In this paper, we present a simple model of scale-free networks that incorporates both preferential & random attachment and anti-preferential & random deletion at each time step. We derive the degree distribution analytically and show that it follows a power law with the degree exponent in the range of (2,infinity). We also find a way to derive an expression of the clustering coefficient for growing networks and compute the average path length through simulation.
15 pages, 4 figures
References in corpus (15)
- Emergence of scaling in random networks
- Statistical mechanics of complex networks
- The diameter of the world wide web
- Mean-field theory for scale-free random networks
- Hierarchical Organization in Complex Networks
- Structure of Growing Networks: Exact Solution of the Barabasi--Albert's Model
- Topology of evolving networks: local events and universality
- Connectivity of Growing Random Networks
- Growing Scale-Free Networks with Tunable Clustering
- Organization of Growing Random Networks
- Pseudofractal Scale-free Web
- Evolution of reference networks with aging
- Growing Scale-Free Networks with Small World Behavior
- Degree Distributions of Growing Networks
- Scaling Behaviour of Developing and Decaying Networks