Scaling up publish/subscribe overlays using interest correlation for link sharing

Detalhes bibliográficos
Autor(a) principal: Miguel Marques Matos
Data de Publicação: 2013
Outros Autores: Felber,P, Rui Carlos Oliveira, José Orlando Pereira, Riviere,E
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
Texto Completo: http://repositorio.inesctec.pt/handle/123456789/6735
http://dx.doi.org/10.1109/tpds.2013.6
Resumo: Topic-based publish/subscribe is at the core of many distributed systems, ranging from application integration middleware to news dissemination. Therefore, much research was dedicated to publish/subscribe architectures and protocols, and in particular to the design of overlay networks for decentralized topic-based routing and efficient message dissemination. Nonetheless, existing systems fail to take full advantage of shared interests when disseminating information, hence suffering from high maintenance and traffic costs, or construct overlays that cope poorly with the scale and dynamism of large networks. In this paper, we present StaN, a decentralized protocol that optimizes the properties of gossip-based overlay networks for topic-based publish/subscribe by sharing a large number of physical connections without disrupting its logical properties. StaN relies only on local knowledge and operates by leveraging common interests among participants to improve global resource usage and promote topic and event scalability. The experimental evaluation under two real workloads, both via a real deployment and through simulation, shows that StaN provides an attractive infrastructure for scalable topic-based publish/subscribe. © 1990-2012 IEEE.
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spelling Scaling up publish/subscribe overlays using interest correlation for link sharingTopic-based publish/subscribe is at the core of many distributed systems, ranging from application integration middleware to news dissemination. Therefore, much research was dedicated to publish/subscribe architectures and protocols, and in particular to the design of overlay networks for decentralized topic-based routing and efficient message dissemination. Nonetheless, existing systems fail to take full advantage of shared interests when disseminating information, hence suffering from high maintenance and traffic costs, or construct overlays that cope poorly with the scale and dynamism of large networks. In this paper, we present StaN, a decentralized protocol that optimizes the properties of gossip-based overlay networks for topic-based publish/subscribe by sharing a large number of physical connections without disrupting its logical properties. StaN relies only on local knowledge and operates by leveraging common interests among participants to improve global resource usage and promote topic and event scalability. The experimental evaluation under two real workloads, both via a real deployment and through simulation, shows that StaN provides an attractive infrastructure for scalable topic-based publish/subscribe. © 1990-2012 IEEE.2018-01-17T15:29:33Z2013-01-01T00:00:00Z2013info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleapplication/pdfhttp://repositorio.inesctec.pt/handle/123456789/6735http://dx.doi.org/10.1109/tpds.2013.6engMiguel Marques MatosFelber,PRui Carlos OliveiraJosé Orlando PereiraRiviere,Einfo:eu-repo/semantics/openAccessreponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãoinstacron:RCAAP2023-05-15T10:20:30Zoai:repositorio.inesctec.pt:123456789/6735Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-19T17:53:14.496653Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãofalse
dc.title.none.fl_str_mv Scaling up publish/subscribe overlays using interest correlation for link sharing
title Scaling up publish/subscribe overlays using interest correlation for link sharing
spellingShingle Scaling up publish/subscribe overlays using interest correlation for link sharing
Miguel Marques Matos
title_short Scaling up publish/subscribe overlays using interest correlation for link sharing
title_full Scaling up publish/subscribe overlays using interest correlation for link sharing
title_fullStr Scaling up publish/subscribe overlays using interest correlation for link sharing
title_full_unstemmed Scaling up publish/subscribe overlays using interest correlation for link sharing
title_sort Scaling up publish/subscribe overlays using interest correlation for link sharing
author Miguel Marques Matos
author_facet Miguel Marques Matos
Felber,P
Rui Carlos Oliveira
José Orlando Pereira
Riviere,E
author_role author
author2 Felber,P
Rui Carlos Oliveira
José Orlando Pereira
Riviere,E
author2_role author
author
author
author
dc.contributor.author.fl_str_mv Miguel Marques Matos
Felber,P
Rui Carlos Oliveira
José Orlando Pereira
Riviere,E
description Topic-based publish/subscribe is at the core of many distributed systems, ranging from application integration middleware to news dissemination. Therefore, much research was dedicated to publish/subscribe architectures and protocols, and in particular to the design of overlay networks for decentralized topic-based routing and efficient message dissemination. Nonetheless, existing systems fail to take full advantage of shared interests when disseminating information, hence suffering from high maintenance and traffic costs, or construct overlays that cope poorly with the scale and dynamism of large networks. In this paper, we present StaN, a decentralized protocol that optimizes the properties of gossip-based overlay networks for topic-based publish/subscribe by sharing a large number of physical connections without disrupting its logical properties. StaN relies only on local knowledge and operates by leveraging common interests among participants to improve global resource usage and promote topic and event scalability. The experimental evaluation under two real workloads, both via a real deployment and through simulation, shows that StaN provides an attractive infrastructure for scalable topic-based publish/subscribe. © 1990-2012 IEEE.
publishDate 2013
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2013
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