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Analysis of an evolving email network.

Chaopin Zhu1, Anthony Kuh, Juan Wang

  • 1Department of Electrical Engineering, University of Hawaii at Manoa, Holmes 483, Honolulu, Hawaii 96822, USA.

Physical Review. E, Statistical, Nonlinear, and Soft Matter Physics
|December 13, 2006
PubMed
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This study analyzes an evolving email network model, revealing steady-state properties of email traffic and network behavior. The findings confirm prior empirical results and offer insights applicable to sensor and social networks.

Area of Science:

  • Network Science
  • Computer Science
  • Data Analysis

Background:

  • Email networks exhibit complex evolving dynamics.
  • Understanding network topology and traffic is crucial for performance.
  • Previous models by Wang and De Wilde laid foundational work.

Purpose of the Study:

  • To analyze an evolving email network model.
  • To investigate steady-state properties of email traffic and network behavior.
  • To validate analytical findings with simulations and confirm empirical results.

Main Methods:

  • Formulating network topology as a random process.
  • Analyzing the dynamics of the network evolution process.
  • Conducting extensive simulations for link and network level analysis.

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Main Results:

  • Identified steady-state properties for email traffic and aggregate network behavior.
  • Confirmed empirical results from previous studies.
  • Observed phase transition phenomena and behavior in hierarchical networks.

Conclusions:

  • The analytical model accurately captures email network dynamics.
  • The methods are applicable to diverse networks like sensor and social networks.
  • The study provides a robust framework for network analysis.