Competitive video on demand schedulers for popular movies

dc.contributor.author	Μπούρας, Χρήστος	el
dc.contributor.author	Καπούλας, Βαγγέλης	el
dc.contributor.author	Πάντζιου, Γραμματή Ε.	el
dc.contributor.author	Σπυράκης, Παύλος	el
dc.date.accessioned	2015-05-24T19:32:52Z
dc.date.available	2015-05-24T19:32:52Z
dc.date.issued	2015-05-24
dc.identifier.uri	http://hdl.handle.net/11400/11077
dc.rights	Αναφορά Δημιουργού-Μη Εμπορική Χρήση-Όχι Παράγωγα Έργα 3.0 Ηνωμένες Πολιτείες	*
dc.rights.uri	http://creativecommons.org/licenses/by-nc-nd/3.0/us/	*
dc.source	http://www.sciencedirect.com/science/article/pii/S0166218X02002330	en
dc.subject	βίντεο κατά παραγγελία
dc.subject	Συνδεδεμένοι αλγόριθμοι προγραμματισμού
dc.subject	Ανταγωνιστική σχέση
dc.subject	Κατανομή πιθανότητας
dc.subject	Video on demand
dc.subject	Online scheduling algorithm
dc.subject	Competitive ratio
dc.subject	probability distribution
dc.title	Competitive video on demand schedulers for popular movies	en
heal.type	journalArticle
heal.classification	Πληροφορική
heal.classification	Μαθηματικά
heal.classification	Computer science
heal.classification	Mathematics
heal.classificationURI	N/A-Πληροφορική
heal.classificationURI	N/A-Μαθηματικά
heal.classificationURI	http://skos.um.es/unescothes/C00750
heal.classificationURI	http://skos.um.es/unescothes/C02437
heal.keywordURI	http://lod.nal.usda.gov/137373
heal.identifier.secondary	DOI: 10.1016/S0166-218X(02)00233-0
heal.language	en
heal.access	campus
heal.recordProvider	Τεχνολογικό Εκπαιδευτικό Ίδρυμα Αθήνας. Σχολή Τεχνολογικών Εφαρμογών. Τμήμα Μηχανικών Πληροφορικής Τ.Ε.	el
heal.publicationDate	2003-06-13
heal.bibliographicCitation	Bouras, C., Kapoulas, V., Pantziou, G. and Spirakis, P. (2003) Competitive video on demand schedulers for popular movies. Discrete Applied Mathematics. [Online] 129 (1). pp.49-61. Available from: http://www.sciencedirect.com [Accessed 24/05/2015]	en
heal.abstract	In this paper we investigate the online video on demand problem, namely having to accept or reject a request for a movie without knowing the future requests. We present online movie-scheduling schemes that implement the principles of refusal by choice and delayed notification. A novel way to schedule movies that exploits the knowledge of the distribution of the preference of requests for movies, is shown to have a competitive ratio that outperforms all the previously known schemes in practical situations. In fact, our scheduler has a competitive ratio bounded above by a constant, independent of the number of the users, channels, or movies, in the case that a large fraction of the requests tends to concentrate in a small number of movies. We extend our approach by presenting an “adaptive” randomized scheduler which initially is not aware of the movie popularities but it adapts to it, and achieves the same asymptotic competitive ratio.	en
heal.publisher	Elsevier	en
heal.journalName	Discrete Applied Mathematics	en
heal.journalType	peer-reviewed
heal.fullTextAvailability	true