Percolation analysis for constructing a robust modular topology based on a binary-dynamics model

In the context of Internet of Things, virtualization of wireless sensor networks is a crucial technology for sharing sensors as infrastructure. In our previous work, we proposed a brain-inspired method for constructing a robust and adaptive virtual wireless sensor network topology and showed that th...

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Main Authors: Shinya Toyonaga, Daichi Kominami, Masayuki Murata
Format: Article
Language:English
Published: Wiley 2017-04-01
Series:International Journal of Distributed Sensor Networks
Online Access:https://doi.org/10.1177/1550147717701141
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author Shinya Toyonaga
Daichi Kominami
Masayuki Murata
author_facet Shinya Toyonaga
Daichi Kominami
Masayuki Murata
author_sort Shinya Toyonaga
collection DOAJ
description In the context of Internet of Things, virtualization of wireless sensor networks is a crucial technology for sharing sensors as infrastructure. In our previous work, we proposed a brain-inspired method for constructing a robust and adaptive virtual wireless sensor network topology and showed that the method of constructing links between modules has crucial effect on robustness and adaptivity of the constructed virtual wireless sensor network topology. However, the best way of constructing a robust and adaptive virtual wireless sensor network topology is still unclear. Therefore, in this article, we use an analytical approach and propose a method for clarifying robustness of a topology according to the method of constructing links between modules. We add a new tool to a binary-dynamics model which is an analytical method for investigating percolation dynamics on a modular network. Evaluation by simulation showed that graphs in which the number of nodes selected as endpoint nodes of inter-module links and the degrees of the endpoint nodes before the link addition are large have robust connectivity in terms of the point of fragmentation of the network into modules when we fix the degree of the endpoint nodes after the link addition. After the point, the internal structure of modules may matter more. We additionally investigate an applicable range of our proposed method.
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institution Kabale University
issn 1550-1477
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publishDate 2017-04-01
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spelling doaj-art-6da34c4bd9fd4a76b42b55c7a5c9a6b12025-02-03T05:55:23ZengWileyInternational Journal of Distributed Sensor Networks1550-14772017-04-011310.1177/1550147717701141Percolation analysis for constructing a robust modular topology based on a binary-dynamics modelShinya Toyonaga0Daichi Kominami1Masayuki Murata2Graduate School of Information Science and Technology, Osaka University, Suita, JapanGraduate School of Economics, Osaka University, Suita, JapanGraduate School of Information Science and Technology, Osaka University, Suita, JapanIn the context of Internet of Things, virtualization of wireless sensor networks is a crucial technology for sharing sensors as infrastructure. In our previous work, we proposed a brain-inspired method for constructing a robust and adaptive virtual wireless sensor network topology and showed that the method of constructing links between modules has crucial effect on robustness and adaptivity of the constructed virtual wireless sensor network topology. However, the best way of constructing a robust and adaptive virtual wireless sensor network topology is still unclear. Therefore, in this article, we use an analytical approach and propose a method for clarifying robustness of a topology according to the method of constructing links between modules. We add a new tool to a binary-dynamics model which is an analytical method for investigating percolation dynamics on a modular network. Evaluation by simulation showed that graphs in which the number of nodes selected as endpoint nodes of inter-module links and the degrees of the endpoint nodes before the link addition are large have robust connectivity in terms of the point of fragmentation of the network into modules when we fix the degree of the endpoint nodes after the link addition. After the point, the internal structure of modules may matter more. We additionally investigate an applicable range of our proposed method.https://doi.org/10.1177/1550147717701141
spellingShingle Shinya Toyonaga
Daichi Kominami
Masayuki Murata
Percolation analysis for constructing a robust modular topology based on a binary-dynamics model
International Journal of Distributed Sensor Networks
title Percolation analysis for constructing a robust modular topology based on a binary-dynamics model
title_full Percolation analysis for constructing a robust modular topology based on a binary-dynamics model
title_fullStr Percolation analysis for constructing a robust modular topology based on a binary-dynamics model
title_full_unstemmed Percolation analysis for constructing a robust modular topology based on a binary-dynamics model
title_short Percolation analysis for constructing a robust modular topology based on a binary-dynamics model
title_sort percolation analysis for constructing a robust modular topology based on a binary dynamics model
url https://doi.org/10.1177/1550147717701141
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AT daichikominami percolationanalysisforconstructingarobustmodulartopologybasedonabinarydynamicsmodel
AT masayukimurata percolationanalysisforconstructingarobustmodulartopologybasedonabinarydynamicsmodel