Noise enhances information transfer in hierarchical networks

Agnieszka Czaplicka , Janusz Hołyst , Peter M.A Sloot


We study the influence of noise on information transmission in the form of packages shipped between nodes of hierarchical networks. Numerical simulations are performed for artificial tree networks, scale-free Ravasz-Barabási networks as well for a real network formed by email addresses of former Enron employees. Two types of noise are considered. One is related to packet dynamics and is responsible for a random part of packets paths. The second one originates from random changes in initial network topology. We find that the information transfer can be enhanced by the noise. The system possesses optimal performance when both kinds of noise are tuned to specific values, this corresponds to the Stochastic Resonance phenomenon. There is a non-trivial synergy present for both noisy components. We found also that hierarchical networks built of nodes of various degrees are more efficient in information transfer than trees with a fixed branching factor.
Author Agnieszka Czaplicka (FP / LPESS)
Agnieszka Czaplicka,,
- Center of Physics in Economics and Social Sciences
, Janusz Hołyst (FP / LPESS)
Janusz Hołyst,,
- Center of Physics in Economics and Social Sciences
, Peter M.A Sloot - [University of Amsterdam (UVA)]
Peter M.A Sloot,,
- Universiteit van Amsterdam
Journal seriesScientific Reports, ISSN 2045-2322
Issue year2013
Publication size in sheets0.5
Keywords in EnglishHierarchical networks, stochastic resonance, information flow
ASJC Classification1000 Multidisciplinary
ProjectComputing Real-World Phenomena with Dynamically Changing Complex Networks . Project leader: Hołyst Janusz, , Phone: 22 234 7133, start date 01-06-2009, end date 30-11-2012, FP7-ICT-2009-5, Completed
WF 7 Framework Programme (7 FP) [7 Program Ramowy (7 PR)]
Score (nominal)40
Score sourcejournalList
ScoreMinisterial score = 40.0, 18-05-2020, ArticleFromJournal
Ministerial score (2013-2016) = 40.0, 18-05-2020, ArticleFromJournal
Publication indicators WoS Citations = 25; GS Citations = 48.0; Scopus Citations = 27; Scopus SNIP (Source Normalised Impact per Paper): 2014 = 1.544; WoS Impact Factor: 2013 = 5.078 (2) - 2013=5.078 (5)
Citation count*48 (2020-09-01)
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* presented citation count is obtained through Internet information analysis and it is close to the number calculated by the Publish or Perish system.
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