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dc.contributor.authorKilanioti, Ireneen
dc.contributor.authorPapadopoulos, George Angelosen
dc.contributor.editorRana O.en
dc.contributor.editorBuyya, R.en
dc.contributor.editorRaicu I.en
dc.creatorKilanioti, Ireneen
dc.creatorPapadopoulos, George Angelosen
dc.date.accessioned2019-11-13T10:40:43Z
dc.date.available2019-11-13T10:40:43Z
dc.date.issued2015
dc.identifier.isbn978-0-7695-5697-0
dc.identifier.urihttp://gnosis.library.ucy.ac.cy/handle/7/54261
dc.description.abstractMost Content Delivery Networks (CDNs) are operated as a Software as a Service (SaaS): Many cloud providers build their custom CDNs to benefit from content users, as well as reduce demand on their own telecommunications infrastructure. More importantly, though, CDNs contribute to cloud adoption, as they can address network problems of cloud computing. With multimedia content providers requiring CDN services to enable the delivery of bandwindth-demanding media to end-users, and the growth of HTTP traffic due to media files circulating over Online Social Networks (OSNs), a social-awareness mechanism over a CDN becomes essential, to mitigate the considerable weight placed on bandwidth. A social awareness mechanism augmented to a stand-alone CDN traffic simulator addresses the issue of which content will be copied in the surrogate servers of a CDN infrastructure and to what extent. Hence, it ensures an optimized content diffusion placement. Herein, we further address the issue of temporal diffusion, related to the most efficient timing of the content placement. We exploit the knowledge of peak times for upload and download, so that content is prefetched in the hours with less traffic. We also incorporate other contextual information, such as the viewership within the media service, to ensure performance optimization. Our variations are experimentally proven to contribute toward maximization of CDNs' performance and minimization of content replication costs. © 2015 IEEE.en
dc.publisherInstitute of Electrical and Electronics Engineers Inc.en
dc.sourceProceedings - 2015 IEEE/ACM 8th International Conference on Utility and Cloud Computing, UCC 2015en
dc.source8th IEEE/ACM International Conference on Utility and Cloud Computing, UCC 2015en
dc.source.urihttps://www.scopus.com/inward/record.uri?eid=2-s2.0-84965007410&doi=10.1109%2fUCC.2015.48&partnerID=40&md5=51d1af36ca57b28527ad8818a6342b76
dc.subjectWebsitesen
dc.subjectDistributed computer systemsen
dc.subjectMultimedia servicesen
dc.subjectVehicle actuated signalsen
dc.subjectSocial networking (online)en
dc.subjectWeb servicesen
dc.subjectCloud applicationsen
dc.subjectCloud computingen
dc.subjectInternet measurementen
dc.subjectInternet Measurementsen
dc.subjectSocial Cascadingen
dc.subjectSocial Video Sharingen
dc.subjectTwitteren
dc.subjectYouTubeen
dc.subjectBig dataen
dc.subjectHTTPen
dc.subjectSocial sciences computingen
dc.subjectBig Data and Analyticsen
dc.subjectCloud Applications: social networksen
dc.subjectCloud Computing toolsen
dc.subjectContent delivery networken
dc.subjectContent Delivery Networksen
dc.subjectdelivery networks and servicesen
dc.subjectSocial videosen
dc.subjectSoftware as a service (SaaS)en
dc.titleSocially-Aware Multimedia Content Delivery for the Clouden
dc.typeinfo:eu-repo/semantics/conferenceObject
dc.identifier.doi10.1109/UCC.2015.48
dc.description.startingpage300
dc.description.endingpage309
dc.author.faculty002 Σχολή Θετικών και Εφαρμοσμένων Επιστημών / Faculty of Pure and Applied Sciences
dc.author.departmentΤμήμα Πληροφορικής / Department of Computer Science
dc.type.uhtypeConference Objecten
dc.description.notes<p>Sponsors: Association for Computing Machinery (ACM)en
dc.description.notesIEEE Computer Societyen
dc.description.notesConference code: 119981en
dc.description.notesCited By :3</p>en
dc.contributor.orcidPapadopoulos, George Angelos [0000-0001-9250-4916]
dc.gnosis.orcid0000-0001-9250-4916


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