Tuning clustering in random networks with arbitrary degree distributions

¹School of Informatics, Indiana University, Eigenmann Hall, 1900 East Tenth Street, Bloomington, Indiana 47406, USA.

Physical Review. E, Statistical, Nonlinear, and Soft Matter Physics

|October 26, 2005

Summary

We developed a random network generator with tunable clustering and degree distributions. This method reveals a universal relationship between network assortativity and clustering, setting structural bounds for real-world networks.

Area of Science:

Network science
Statistical physics
Computer science

Background:

Understanding complex network structure is crucial.
Existing models often lack control over specific topological features like clustering and degree distribution.
Tunable network generators are needed to explore structure-property relationships.

Purpose of the Study:

To introduce a novel random network generator.
To enable simultaneous tuning of degree distribution and degree-dependent clustering coefficients.
To investigate the universal relationship between network assortativity and clustering.

Main Methods:

A configuration model-inspired approach.
Fixing degree distribution and degree-dependent clustering coefficients a priori.
Employing a two-step generation process: triangle closure followed by stub closure.

Main Results:

The generator successfully produces random networks with specified properties.
An emergent universal relationship between clustering and degree-degree correlations was identified.
Assortativity was shown to impose an upper bound on the level of clustering.

Conclusions:

The proposed method provides a powerful tool for generating complex networks with controlled topology.
The discovered universal relation offers insights into the structural constraints of real-world networks.
Network assortativity acts as a fundamental determinant of achievable clustering levels.

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Related Experiment Videos

Tuning clustering in random networks with arbitrary degree distributions

Area of Science:

Background:

Purpose of the Study:

Main Methods:

Main Results:

Conclusions:

Related Concept Videos

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