A study on the robustness and fragility of tree-based wireless sensor networks with community characteristics

Feifan Wang*, Baihai Zhang, Qiao Li, Senchun Chai, Linguo Cui, Shi Zhang, Zixiao Guan

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

2 Citations (Scopus)

Abstract

A number of recent studies have concentrated on the statistical properties of large-scale tree based wireless sensor network with community characteristics. The robustness and fragility of wireless sensor networks, whose underlying architecture patterns crucially affect the system functionality, is defined as the resilience to deletion of network nodes, which is equivalent to be a percolation model on a graph depicting the network. In this paper we have derived an analytic solution of the site percolation model using generating function formalism on a Cayley-Tree based wireless sensor network structure with community features. Our solution provides predictions for quantities including the position of the percolation threshold and the average cluster size as functions of rewiring probabilities and occupation proportion respectively. All the analytic results show great agreement with their extensive numerical simulations counterparts.

Original languageEnglish
Title of host publicationProceedings of 2017 IEEE International Conference on Unmanned Systems, ICUS 2017
EditorsXin Xu
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages307-312
Number of pages6
ISBN (Electronic)9781538631065
DOIs
Publication statusPublished - 2 Jul 2017
Event2017 IEEE International Conference on Unmanned Systems, ICUS 2017 - Beijing, China
Duration: 27 Oct 201729 Oct 2017

Publication series

NameProceedings of 2017 IEEE International Conference on Unmanned Systems, ICUS 2017
Volume2018-January

Conference

Conference2017 IEEE International Conference on Unmanned Systems, ICUS 2017
Country/TerritoryChina
CityBeijing
Period27/10/1729/10/17

Keywords

  • Cayley-Tree
  • Community
  • Epidemic
  • Percolation
  • Robustness
  • WSN

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