On the Periodicity of Random Walks in Dynamic Networks

Research output: Contribution to journalArticle

Abstract

We investigate random walks in graphs whose edges change over time as a function of the current probability distribution of the walk. We show that such systems can be chaotic and can exhibit 'hyper-torpid' mixing. Our main result is that, if each graph is strongly connected, then the dynamics is asymptotically periodic almost surely.

Original languageEnglish (US)
Article number8747524
Pages (from-to)1337-1343
Number of pages7
JournalIEEE Transactions on Network Science and Engineering
Volume7
Issue number3
DOIs
StatePublished - Jul 1 2020

All Science Journal Classification (ASJC) codes

  • Control and Systems Engineering
  • Computer Science Applications
  • Computer Networks and Communications

Keywords

  • chaos
  • hyper-torpid mixing
  • Markov influence systems
  • Random walks
  • temporal networks

Fingerprint Dive into the research topics of 'On the Periodicity of Random Walks in Dynamic Networks'. Together they form a unique fingerprint.

  • Cite this