On power-law relationships of the Internet topology
Proceedings of the conference on Applications, technologies, architectures, and protocols for computer communication
Approximation algorithms
Computers and Intractability; A Guide to the Theory of NP-Completeness
Computers and Intractability; A Guide to the Theory of NP-Completeness
Network topology generators: degree-based vs. structural
Proceedings of the 2002 conference on Applications, technologies, architectures, and protocols for computer communications
Scale-free geometry in OO programs
Communications of the ACM - Adaptive complex enterprises
A structural approach to the temporal modeling of networks
Winter Simulation Conference
| Hi-index | 0.00 |
Recent research has shown that while many complex networks follow a power-law distribution for their node degrees, it is not sufficient to model these networks based only on their degree distribution. In order to better distinguish between these networks, the metric s was introduced to measure how interconnected the hub nodes are in a network. We examine the effectiveness of creating network models based on this metric. Through a series of computational experiments, we compare how well a set of common structural network metrics are preserved between instances of the autonomous system Internet topology and a series of random models with identical degree sequences and similar s values. We demonstrate that creating models based on the s metric can produce moderate improvement in structural characteristics over strictly using degree distribution. Our results also indicate that some interesting relationships exist between the s metric and the various structural metrics.