On a class of stochastic multilayer networks

Bo Jiang, Don Towsley, Philippe Nain, Saikat Guha

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Scopus citations

Abstract

In this paper, we introduce a new class of stochastic multilayer networks. A stochastic multilayer network is the aggregation of M networks (one per layer) where each is a subgraph of a foundational network G. Each layer network is the result of probabilistically removing links and nodes from G. The resulting network includes any link that appears in at least K layers. This model is an instance of a non-standard site-bond percolation model. Two sets of results are obtained:fi rst, we derive the probability distribution that the M-layer network is in a given configuration for some particular graph structures (explicit results are provided for a line and an algorithm is provided for a tree), where a configuration is the collective state of all links (each either active or inactive). Next, we show that for appropriate scalings of the node and link selection processes in a layer, links are asymptotically independent as the number of layers goes to infinity, and follow Poisson distributions. Numerical results are provided to highlight the impact of having several layers on some metrics of interest (including expected size of the cluster a node belongs to in the case of the line). This model finds applications in wireless communication networks with multichannel radios, multiple social networks with overlapping memberships, transportation networks, and, more generally, in any scenario where a common set of nodes can be linked via co-existing means of connectivity.

Original languageEnglish (US)
Title of host publicationSIGMETRICS 2018 - Abstracts of the 2018 ACM International Conference on Measurement and Modeling of Computer Systems
PublisherAssociation for Computing Machinery, Inc
Pages119-121
Number of pages3
ISBN (Electronic)9781450358460
DOIs
StatePublished - Jun 12 2018
Event2018 ACM International Conference on Measurement and Modeling of Computer Systems, SIGMETRICS 2018 - Irvine, United States
Duration: Jun 18 2018Jun 22 2018

Publication series

NameSIGMETRICS 2018 - Abstracts of the 2018 ACM International Conference on Measurement and Modeling of Computer Systems

Conference

Conference2018 ACM International Conference on Measurement and Modeling of Computer Systems, SIGMETRICS 2018
CountryUnited States
CityIrvine
Period6/18/186/22/18

ASJC Scopus subject areas

  • Computer Networks and Communications
  • Hardware and Architecture
  • Computational Theory and Mathematics
  • Software

Fingerprint Dive into the research topics of 'On a class of stochastic multilayer networks'. Together they form a unique fingerprint.

  • Cite this

    Jiang, B., Towsley, D., Nain, P., & Guha, S. (2018). On a class of stochastic multilayer networks. In SIGMETRICS 2018 - Abstracts of the 2018 ACM International Conference on Measurement and Modeling of Computer Systems (pp. 119-121). (SIGMETRICS 2018 - Abstracts of the 2018 ACM International Conference on Measurement and Modeling of Computer Systems). Association for Computing Machinery, Inc. https://doi.org/10.1145/3219617.3219667