A scalable framework for content replication in multicast-based content distribution networks

Matalas, Y; Dragios, ND; Karetsos, GT

dc.contributor.author	Matalas, Y	en
dc.contributor.author	Dragios, ND	en
dc.contributor.author	Karetsos, GT	en
dc.date.accessioned	2014-03-01T02:43:52Z
dc.date.available	2014-03-01T02:43:52Z
dc.date.issued	2006	en
dc.identifier.issn	0302-9743	en
dc.identifier.uri	https://dspace.lib.ntua.gr/xmlui/handle/123456789/31533
dc.subject	Content Distribution Network	en
dc.subject.classification	Computer Science, Artificial Intelligence	en
dc.subject.other	Content based retrieval	en
dc.subject.other	Control system analysis	en
dc.subject.other	Multicasting	en
dc.subject.other	Robustness (control systems)	en
dc.subject.other	Servers	en
dc.subject.other	Content distribution networks (CDN)	en
dc.subject.other	Distributed replication decisions	en
dc.subject.other	Robust systems	en
dc.subject.other	Surrogate servers	en
dc.subject.other	Network protocols	en
dc.title	A scalable framework for content replication in multicast-based content distribution networks	en
heal.type	conferenceItem	en
heal.identifier.primary	10.1007/11907381_10	en
heal.identifier.secondary	http://dx.doi.org/10.1007/11907381_10	en
heal.language	English	en
heal.publicationDate	2006	en
heal.abstract	This paper proposes a framework for replicating content in multicast-based CDNs. We focus on the design of a scalable and robust system that provides local availability and redundancy of content. The system takes on-line and distributed replication decisions on a per-object basis. The scalability and local redundancy is achieved by partitioning the overlay of surrogate servers into fully meshed groups. The proposed framework can incorporate any set of local metrics and constraints for deciding the placement of replicas, thus allowing the CDN designer to tune it to his specific deployment characteristics. © IFIP International Federation for Information Processing 2006.	en
heal.publisher	SPRINGER-VERLAG BERLIN	en
heal.journalName	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)	en
heal.bookName	LECTURE NOTES IN ARTIFICIAL INTELLIGENCE	en
dc.identifier.doi	10.1007/11907381_10	en
dc.identifier.isi	ISI:000242560000010	en
dc.identifier.volume	4267 LNCS	en
dc.identifier.spage	110	en
dc.identifier.epage	115	en