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dc.contributor.authorBui, Nicola 
dc.contributor.authorCesana, Matteo
dc.contributor.authorHosseini, S. Amir
dc.contributor.authorLiao, Qi
dc.contributor.authorMalanchini, Ilaria
dc.contributor.authorWidmer, Joerg 
dc.date.accessioned2021-07-13T09:29:14Z
dc.date.available2021-07-13T09:29:14Z
dc.date.issued2017-04-19
dc.identifier.issn1553-877X
dc.identifier.urihttp://hdl.handle.net/20.500.12761/366
dc.description.abstractA growing trend for information technology is to not just react to changes, but anticipate them as much as possible. This paradigm made modern solutions, such as recommendation systems, a ubiquitous presence in today’s digital transactions. Anticipatory networking extends the idea to communication technologies by studying patterns and periodicity in human behavior and network dynamics to optimize network performance. This survey collects and analyzes recent papers leveraging context information to forecast the evolution of network conditions and, in turn, to improve network performance. In particular, we identify the main prediction and optimization tools adopted in this body of work and link them with objectives and constraints of the typical applications and scenarios. Finally, we consider open challenges and research directions to make anticipatory networking part of next generation networks.
dc.language.isoeng
dc.publisherIEEE Communications Society
dc.titleA Survey of Anticipatory Mobile Networking: Context-Based Classification, Prediction Methodologies, and Optimization Techniquesen
dc.typejournal article
dc.journal.titleIEEE Communications Surveys & Tutorials
dc.type.hasVersionVoR
dc.rights.accessRightsopen access
dc.volume.number19
dc.issue.number3
dc.identifier.doiDOI: 10.1109/COMST.2017.2694140
dc.page.final1821
dc.page.initial1790
dc.subject.keywordAnticipatory
dc.subject.keywordPrediction
dc.subject.keywordOptimization
dc.subject.keyword5G
dc.subject.keywordMobile Networks
dc.description.statuspub
dc.eprint.idhttp://eprints.networks.imdea.org/id/eprint/1577


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