Abstract

We introduce a generative model for multilayer networks consisting of awareness layers and active layers. Nodes themselves seek to build (or weight) links in active layers based on information available through their connections in awareness layers, including via discrete choice processes. For the generative network models we define, we use actor-based simulations and analytical approaches to examine the properties of resultant networks, such as degree distributions.

Original languageEnglish (US)
Title of host publication56th Asilomar Conference on Signals, Systems and Computers, ACSSC 2022
EditorsMichael B. Matthews
PublisherIEEE Computer Society
Pages1269-1275
Number of pages7
ISBN (Electronic)9781665459068
DOIs
StatePublished - 2022
Event56th Asilomar Conference on Signals, Systems and Computers, ACSSC 2022 - Virtual, Online, United States
Duration: Oct 31 2022Nov 2 2022

Publication series

NameConference Record - Asilomar Conference on Signals, Systems and Computers
Volume2022-October
ISSN (Print)1058-6393

Conference

Conference56th Asilomar Conference on Signals, Systems and Computers, ACSSC 2022
Country/TerritoryUnited States
CityVirtual, Online
Period10/31/2211/2/22

ASJC Scopus subject areas

  • Signal Processing
  • Computer Networks and Communications

Fingerprint

Dive into the research topics of 'Awareness-Constrained Discrete Choice in Multilayer Network Formation and Evolution'. Together they form a unique fingerprint.

Cite this