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Using Link Disconnection Entropy Disorder to Detect Fast Moving Nodes in MANETs
Mobile ad-hoc networks (MANETs) are dynamic by nature; this dynamism comes from node mobility, traffic congestion, and other transmission conditions. Metrics to evaluate the effects of those conditions shine a light on node’s behavior in an ad-hoc network, helping to identify the node or nodes with...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2016
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4878810/ https://www.ncbi.nlm.nih.gov/pubmed/27219671 http://dx.doi.org/10.1371/journal.pone.0155820 |
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author | Alvarez, Carlos F. Palafox, Luis E. Aguilar, Leocundo Sanchez, Mauricio A. Martinez, Luis G. |
author_facet | Alvarez, Carlos F. Palafox, Luis E. Aguilar, Leocundo Sanchez, Mauricio A. Martinez, Luis G. |
author_sort | Alvarez, Carlos F. |
collection | PubMed |
description | Mobile ad-hoc networks (MANETs) are dynamic by nature; this dynamism comes from node mobility, traffic congestion, and other transmission conditions. Metrics to evaluate the effects of those conditions shine a light on node’s behavior in an ad-hoc network, helping to identify the node or nodes with better conditions of connection. In this paper, we propose a relative index to evaluate a single node reliability, based on the link disconnection entropy disorder using neighboring nodes as reference. Link disconnection entropy disorder is best used to identify fast moving nodes or nodes with unstable communications, this without the need of specialized sensors such as GPS. Several scenarios were studied to verify the index, measuring the effects of Speed and traffic density on the link disconnection entropy disorder. Packet delivery ratio is associated to the metric detecting a strong relationship, enabling the use of the link disconnection entropy disorder to evaluate the stability of a node to communicate with other nodes. To expand the utilization of the link entropy disorder, we identified nodes with higher speeds in network simulations just by using the link entropy disorder. |
format | Online Article Text |
id | pubmed-4878810 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2016 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-48788102016-06-09 Using Link Disconnection Entropy Disorder to Detect Fast Moving Nodes in MANETs Alvarez, Carlos F. Palafox, Luis E. Aguilar, Leocundo Sanchez, Mauricio A. Martinez, Luis G. PLoS One Research Article Mobile ad-hoc networks (MANETs) are dynamic by nature; this dynamism comes from node mobility, traffic congestion, and other transmission conditions. Metrics to evaluate the effects of those conditions shine a light on node’s behavior in an ad-hoc network, helping to identify the node or nodes with better conditions of connection. In this paper, we propose a relative index to evaluate a single node reliability, based on the link disconnection entropy disorder using neighboring nodes as reference. Link disconnection entropy disorder is best used to identify fast moving nodes or nodes with unstable communications, this without the need of specialized sensors such as GPS. Several scenarios were studied to verify the index, measuring the effects of Speed and traffic density on the link disconnection entropy disorder. Packet delivery ratio is associated to the metric detecting a strong relationship, enabling the use of the link disconnection entropy disorder to evaluate the stability of a node to communicate with other nodes. To expand the utilization of the link entropy disorder, we identified nodes with higher speeds in network simulations just by using the link entropy disorder. Public Library of Science 2016-05-24 /pmc/articles/PMC4878810/ /pubmed/27219671 http://dx.doi.org/10.1371/journal.pone.0155820 Text en © 2016 Alvarez et al http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. |
spellingShingle | Research Article Alvarez, Carlos F. Palafox, Luis E. Aguilar, Leocundo Sanchez, Mauricio A. Martinez, Luis G. Using Link Disconnection Entropy Disorder to Detect Fast Moving Nodes in MANETs |
title | Using Link Disconnection Entropy Disorder to Detect Fast Moving Nodes in MANETs |
title_full | Using Link Disconnection Entropy Disorder to Detect Fast Moving Nodes in MANETs |
title_fullStr | Using Link Disconnection Entropy Disorder to Detect Fast Moving Nodes in MANETs |
title_full_unstemmed | Using Link Disconnection Entropy Disorder to Detect Fast Moving Nodes in MANETs |
title_short | Using Link Disconnection Entropy Disorder to Detect Fast Moving Nodes in MANETs |
title_sort | using link disconnection entropy disorder to detect fast moving nodes in manets |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4878810/ https://www.ncbi.nlm.nih.gov/pubmed/27219671 http://dx.doi.org/10.1371/journal.pone.0155820 |
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