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Ageing of complex networks.

Zdzislaw Burda1, Michalina Kotwica1, Krzysztof Malarz1

  • 1AGH University of Science and Technology, Faculty of Physics and Applied Computer Science, al. Mickiewicza 30, 30-059 Kraków, Poland.

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Summary
This summary is machine-generated.

This study models complex network evolution, showing how initial growth followed by rewiring shapes network topology. Branch reshuffling accelerates network aging more than leaf reshuffling.

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Area of Science:

  • Network Science
  • Complex Systems
  • Computational Modeling

Background:

  • Real-world complex networks often evolve through a balance of growth and rewiring processes.
  • Initial network growth establishes size, while subsequent rewiring optimizes function and topology.
  • Understanding these evolutionary dynamics is crucial for network analysis.

Purpose of the Study:

  • To model and analyze the evolution of tree networks under competing growth and rewiring dynamics.
  • To investigate the impact of different aging mechanisms on network topology and evolution speed.
  • To quantify topological differences between initial and aged network states.

Main Methods:

  • Utilized a stochastic growth process (node attachment) to initiate tree network formation.
  • Implemented a Markov process for network aging, preserving node-degree distribution.
  • Compared two aging dynamics: leaf reshuffling and branch reshuffling.

Main Results:

  • Observed that network aging, particularly through branch reshuffling, significantly alters topology.
  • Branch reshuffling demonstrated a much faster aging process compared to leaf reshuffling.
  • Quantified topological changes and analyzed the dynamics of network evolution.

Conclusions:

  • The interplay between growth and rewiring is fundamental to complex network formation.
  • Network aging mechanisms, especially nonlocal ones like branch reshuffling, can rapidly modify network structure.
  • The chosen aging dynamics significantly influence the speed and nature of network evolution.