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Distributed rewiring model for complex networking: The effect of local rewiring rules on final structural properties.

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  • 1Department of Electrical Engineering, Universidad Autónoma Metropolitana, Iztapalapa, Mexico City, Mexico.

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This study introduces a distributed rewiring model for complex networks. The model enhances network properties like reduced diameter and increased clustering by allowing nodes to discover and create shortcuts.

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Area of Science:

  • Complex Networks
  • Network Science
  • Graph Theory

Background:

  • Complex networks exhibit critical structural properties such as diameter and average path length.
  • These properties influence system functionalities including fault tolerance, attack resilience, and routing efficiency.
  • Understanding the evolutionary forces shaping network structure is crucial for various applications.

Purpose of the Study:

  • To investigate the evolutionary forces that lead to the settlement of structural properties in complex networks.
  • To propose and evaluate a distributed rewiring model for network topology modification.
  • To explore the applicability of the model to Information and Communication Technologies (ICT) systems and other complex network scenarios.

Main Methods:

  • Utilized a discrete event simulator to model network evolution.
  • Implemented a distributed rewiring mechanism where nodes discover and create shortcuts to distant regions.
  • Nodes locally optimize packet trajectories, leading to global topological changes.

Main Results:

  • The distributed rewiring model successfully generated networks with characteristics similar to known complex networks.
  • Observed a significant decrease in network diameter and an increase in the clustering coefficient compared to the initial graph.
  • Demonstrated that subtle changes in local rewiring rules can lead to diverse final network structures.

Conclusions:

  • A distributed, locally driven rewiring approach can effectively modify global network topology.
  • The proposed model fosters the emergence of desirable complex network properties.
  • The findings have implications for designing robust and efficient networks, particularly in ICT.