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Measuring and optimizing video player streaming profile algorithm / Guillaume Bouillon

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Titre :	Measuring and optimizing video player streaming profile algorithm
Type de document :	Travail de fin d'études
Auteurs :	Guillaume Bouillon, Auteur ; Dieter Boschloos, ; Philippe Dekimpe,
Editeur :	ECAM
Année de publication :	2022
Note générale :	PROXIMUS
Langues :	Anglais (eng)
Index. décimale :	TFE - Informatique (ECAM)
Résumé :	Over the past decades over-the-top (OTT) streaming has grown and gained popularity. Thanks to the technical development and innovation, internet streaming became the most widely used medium to watch remote content as it became easier and easier for user to access video content. Now people can listen to audio streams, watch VoD or watch live TV on their cellphone at any time and place. This lead us to a new way of consuming content and a lot of company did not want to miss that evolution. First Apple with the media player iTunes in 2001, then Netflix with its large movie and TV shows catalogue in 2007 and now in Belgium RTBF Auvio and Proximus Pickx TV with Live TV, records and VoD services. According to Statista, the subscriptions in VoD sector increased enough for their revenue to triple between 2016 and 2020 and is expected to reach $126 billion in 2026 worldwide. In its ambition to have the best quality of experience (QoE), the Belgian telecom company Proximus focused on improving its streaming services by, for example, optimizing startup latency or increasing streaming quality. One problem they are facing is the optimization of the streaming profile selection algorithm within video players. Their video players are provided by licensed vendors and came with their default algorithm that may not fit all the Pickx TV use cases.

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