Probabilistic Multicast Trees

Autores
Wolff, Francis G.; McIntyre, David R.; Johnston, David A.
Año de publicación
2012
Idioma
inglés
Tipo de recurso
artículo
Estado
versión publicada
Descripción
Delivery of the same data content to many clients simultaneously over the Internet continues to be a challenging problem. Multicasting using a single tree structure for data distribution has been shown to be an effective methodology for distribution of data. Using the tree structure to distribute data relieves the source node from the burden of trying to unicast to each client and is efficient because the data delivery burden is distributed over all the participating client nodes. Using multiple tree multicasting further distributes the transmission burden over more participating client nodes and it improves the efficiency of the data distribution. Multiple multicast trees can also be used to manage dynamic behavior of the underlying network. We introduce a methodology which improves data delivery latency and efficiency upon current multiple tree multicast methods. This methodology incorporates a feedback mechanism, randomness and a weighted tree selection mechanism to determine the most efficient multicast tree for multicasting
Facultad de Informática
Materia
Informática
multicast
distribution
Trees
Nivel de accesibilidad
acceso abierto
Condiciones de uso
http://creativecommons.org/licenses/by-nc/3.0/
Repositorio
SEDICI (UNLP)
Institución
Universidad Nacional de La Plata
OAI Identificador
oai:sedici.unlp.edu.ar:10915/9709

id SEDICI_b104b9814dc5d1c1a028281792718d5c
oai_identifier_str oai:sedici.unlp.edu.ar:10915/9709
network_acronym_str SEDICI
repository_id_str 1329
network_name_str SEDICI (UNLP)
spelling Probabilistic Multicast TreesWolff, Francis G.McIntyre, David R.Johnston, David A.InformáticamulticastdistributionTreesDelivery of the same data content to many clients simultaneously over the Internet continues to be a challenging problem. Multicasting using a single tree structure for data distribution has been shown to be an effective methodology for distribution of data. Using the tree structure to distribute data relieves the source node from the burden of trying to unicast to each client and is efficient because the data delivery burden is distributed over all the participating client nodes. Using multiple tree multicasting further distributes the transmission burden over more participating client nodes and it improves the efficiency of the data distribution. Multiple multicast trees can also be used to manage dynamic behavior of the underlying network. We introduce a methodology which improves data delivery latency and efficiency upon current multiple tree multicast methods. This methodology incorporates a feedback mechanism, randomness and a weighted tree selection mechanism to determine the most efficient multicast tree for multicastingFacultad de Informática2012-04info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionArticulohttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdf16-21http://sedici.unlp.edu.ar/handle/10915/9709enginfo:eu-repo/semantics/altIdentifier/url/http://journal.info.unlp.edu.ar/wp-content/uploads/JCST-Apr12-3.pdfinfo:eu-repo/semantics/altIdentifier/issn/1666-6038info:eu-repo/semantics/openAccesshttp://creativecommons.org/licenses/by-nc/3.0/Creative Commons Attribution-NonCommercial 3.0 Unported (CC BY-NC 3.0)reponame:SEDICI (UNLP)instname:Universidad Nacional de La Platainstacron:UNLP2025-09-29T10:50:48Zoai:sedici.unlp.edu.ar:10915/9709Institucionalhttp://sedici.unlp.edu.ar/Universidad públicaNo correspondehttp://sedici.unlp.edu.ar/oai/snrdalira@sedici.unlp.edu.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:13292025-09-29 10:50:49.042SEDICI (UNLP) - Universidad Nacional de La Platafalse
dc.title.none.fl_str_mv Probabilistic Multicast Trees
title Probabilistic Multicast Trees
spellingShingle Probabilistic Multicast Trees
Wolff, Francis G.
Informática
multicast
distribution
Trees
title_short Probabilistic Multicast Trees
title_full Probabilistic Multicast Trees
title_fullStr Probabilistic Multicast Trees
title_full_unstemmed Probabilistic Multicast Trees
title_sort Probabilistic Multicast Trees
dc.creator.none.fl_str_mv Wolff, Francis G.
McIntyre, David R.
Johnston, David A.
author Wolff, Francis G.
author_facet Wolff, Francis G.
McIntyre, David R.
Johnston, David A.
author_role author
author2 McIntyre, David R.
Johnston, David A.
author2_role author
author
dc.subject.none.fl_str_mv Informática
multicast
distribution
Trees
topic Informática
multicast
distribution
Trees
dc.description.none.fl_txt_mv Delivery of the same data content to many clients simultaneously over the Internet continues to be a challenging problem. Multicasting using a single tree structure for data distribution has been shown to be an effective methodology for distribution of data. Using the tree structure to distribute data relieves the source node from the burden of trying to unicast to each client and is efficient because the data delivery burden is distributed over all the participating client nodes. Using multiple tree multicasting further distributes the transmission burden over more participating client nodes and it improves the efficiency of the data distribution. Multiple multicast trees can also be used to manage dynamic behavior of the underlying network. We introduce a methodology which improves data delivery latency and efficiency upon current multiple tree multicast methods. This methodology incorporates a feedback mechanism, randomness and a weighted tree selection mechanism to determine the most efficient multicast tree for multicasting
Facultad de Informática
description Delivery of the same data content to many clients simultaneously over the Internet continues to be a challenging problem. Multicasting using a single tree structure for data distribution has been shown to be an effective methodology for distribution of data. Using the tree structure to distribute data relieves the source node from the burden of trying to unicast to each client and is efficient because the data delivery burden is distributed over all the participating client nodes. Using multiple tree multicasting further distributes the transmission burden over more participating client nodes and it improves the efficiency of the data distribution. Multiple multicast trees can also be used to manage dynamic behavior of the underlying network. We introduce a methodology which improves data delivery latency and efficiency upon current multiple tree multicast methods. This methodology incorporates a feedback mechanism, randomness and a weighted tree selection mechanism to determine the most efficient multicast tree for multicasting
publishDate 2012
dc.date.none.fl_str_mv 2012-04
dc.type.none.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
Articulo
http://purl.org/coar/resource_type/c_6501
info:ar-repo/semantics/articulo
format article
status_str publishedVersion
dc.identifier.none.fl_str_mv http://sedici.unlp.edu.ar/handle/10915/9709
url http://sedici.unlp.edu.ar/handle/10915/9709
dc.language.none.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv info:eu-repo/semantics/altIdentifier/url/http://journal.info.unlp.edu.ar/wp-content/uploads/JCST-Apr12-3.pdf
info:eu-repo/semantics/altIdentifier/issn/1666-6038
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
http://creativecommons.org/licenses/by-nc/3.0/
Creative Commons Attribution-NonCommercial 3.0 Unported (CC BY-NC 3.0)
eu_rights_str_mv openAccess
rights_invalid_str_mv http://creativecommons.org/licenses/by-nc/3.0/
Creative Commons Attribution-NonCommercial 3.0 Unported (CC BY-NC 3.0)
dc.format.none.fl_str_mv application/pdf
16-21
dc.source.none.fl_str_mv reponame:SEDICI (UNLP)
instname:Universidad Nacional de La Plata
instacron:UNLP
reponame_str SEDICI (UNLP)
collection SEDICI (UNLP)
instname_str Universidad Nacional de La Plata
instacron_str UNLP
institution UNLP
repository.name.fl_str_mv SEDICI (UNLP) - Universidad Nacional de La Plata
repository.mail.fl_str_mv alira@sedici.unlp.edu.ar
_version_ 1844615758865235968
score 13.070432