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Generation of 2-mode scale-free graphs for link-level internet topology modeling
Comprehensive analysis that aims to understand the topology of real-world networks and the development of algorithms that replicate their characteristics has been significant research issues. Although the accuracy of newly developed network protocols or algorithms does not depend on the underlying t...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7652253/ https://www.ncbi.nlm.nih.gov/pubmed/33166286 http://dx.doi.org/10.1371/journal.pone.0240100 |
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author | Bakhshaliyev, Khalid Gunes, Mehmet Hadi |
author_facet | Bakhshaliyev, Khalid Gunes, Mehmet Hadi |
author_sort | Bakhshaliyev, Khalid |
collection | PubMed |
description | Comprehensive analysis that aims to understand the topology of real-world networks and the development of algorithms that replicate their characteristics has been significant research issues. Although the accuracy of newly developed network protocols or algorithms does not depend on the underlying topology, the performance generally depends on the topology. As a result, network practitioners have concentrated on generating representative synthetic topologies and utilize them to investigate the performance of their design in simulation or emulation environments. Network generators typically represent the Internet topology as a graph composed of point-to-point links. In this study, we discuss the implications of multi-access links on the synthetic network generation and modeling of the networks as bi-partite graphs to represent both subnetworks and routers. We then analyze the characteristics of sampled Internet topology data sets from backbone Autonomous Systems (AS) and observe that in addition to the commonly recognized power-law node degree distribution, the subnetwork size and the router interface distributions often exhibit power-law characteristics. We introduce a SubNetwork Generator (SubNetG) topology generation approach that incorporates the observed measurements to produce bipartite network topologies. In particular, generated topologies capture the 2-mode relation between the layer-2 (i.e., the subnetwork and interface distributions) and the layer-3 (i.e., the degree distribution) that is missing from the current network generators that produce 1-mode graphs. The SubNetG source code and experimental data is available at https://github.com/netml/sonet. |
format | Online Article Text |
id | pubmed-7652253 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-76522532020-11-18 Generation of 2-mode scale-free graphs for link-level internet topology modeling Bakhshaliyev, Khalid Gunes, Mehmet Hadi PLoS One Research Article Comprehensive analysis that aims to understand the topology of real-world networks and the development of algorithms that replicate their characteristics has been significant research issues. Although the accuracy of newly developed network protocols or algorithms does not depend on the underlying topology, the performance generally depends on the topology. As a result, network practitioners have concentrated on generating representative synthetic topologies and utilize them to investigate the performance of their design in simulation or emulation environments. Network generators typically represent the Internet topology as a graph composed of point-to-point links. In this study, we discuss the implications of multi-access links on the synthetic network generation and modeling of the networks as bi-partite graphs to represent both subnetworks and routers. We then analyze the characteristics of sampled Internet topology data sets from backbone Autonomous Systems (AS) and observe that in addition to the commonly recognized power-law node degree distribution, the subnetwork size and the router interface distributions often exhibit power-law characteristics. We introduce a SubNetwork Generator (SubNetG) topology generation approach that incorporates the observed measurements to produce bipartite network topologies. In particular, generated topologies capture the 2-mode relation between the layer-2 (i.e., the subnetwork and interface distributions) and the layer-3 (i.e., the degree distribution) that is missing from the current network generators that produce 1-mode graphs. The SubNetG source code and experimental data is available at https://github.com/netml/sonet. Public Library of Science 2020-11-09 /pmc/articles/PMC7652253/ /pubmed/33166286 http://dx.doi.org/10.1371/journal.pone.0240100 Text en © 2020 Bakhshaliyev, Gunes 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 Bakhshaliyev, Khalid Gunes, Mehmet Hadi Generation of 2-mode scale-free graphs for link-level internet topology modeling |
title | Generation of 2-mode scale-free graphs for link-level internet topology modeling |
title_full | Generation of 2-mode scale-free graphs for link-level internet topology modeling |
title_fullStr | Generation of 2-mode scale-free graphs for link-level internet topology modeling |
title_full_unstemmed | Generation of 2-mode scale-free graphs for link-level internet topology modeling |
title_short | Generation of 2-mode scale-free graphs for link-level internet topology modeling |
title_sort | generation of 2-mode scale-free graphs for link-level internet topology modeling |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7652253/ https://www.ncbi.nlm.nih.gov/pubmed/33166286 http://dx.doi.org/10.1371/journal.pone.0240100 |
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