2012/02/29 by Juan I. Perotti, Orlando V. Billoni · 11 citations
Biochemistry, Genetics and Molecular Biology · Engineering · Mathematics · Physics and Astronomy · #Algorithm #Complex Network Analysis Techniques #Computer network #Computer science #Degree (music) #Entropy (arrow of time) #Gene Regulatory Network Analysis #Mathematics #Molecular Communication and Nanonetworks #Network topology #Path (computing) #Physics #Random walk #Scheme (mathematics) #Statistics #Topology (electrical circuits) #cond-mat.dis-nn #cond-mat.stat-mech
paper · pdf · doi:10.1103/physreve.86.011120
published in Physical Review E 86(1), 011120 (American Physical Society) · 9 pages, 11 figures
openalex publication_date 2012/07/19 · arxiv created 2012/08/13 · arxiv updated 2012/08/15 · openalex created_date 2025/10/10 · openalex updated_date 2026/08/05
In this work we study the problem of targeting signals in networks using entropy information measurements to quantify the cost of targeting. We introduce a penalization rule that imposes a restriction on the long paths and therefore focuses the signal to the target. By this scheme we go continuously from fully random walkers to walkers biased to the target. We found that the optimal degree of penalization is mainly determined by the topology of the network. By analyzing several examples, we have found that a small amount of penalization reduces considerably the typical walk length, and from this we conclude that a network can be efficiently navigated with restricted information.