Multimedia content distribution optimization using software-defined networking

• Autor(a) principal: Oliveira, Tiago Alexandre Soares
• Data de Publicação: 2018
• Tipo de documento: Dissertação
• Idioma: eng
• Título da fonte: Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
• Texto Completo: http://hdl.handle.net/10773/25983
• topic: Digital Television; IPTV; OTT; DASH; SDN networks; Quality-of-Experience; Load Balancing

The general use of Internet access and user equipments, such as smartphones, tablets and personal computers, is creating a new wave of video content consumption. In the past two decades, the Television broadcasting industry went through several evolutions and changes, evolving from analog to digital distribution, standard definition to high definition TV-channels, form the IPTV method of distribution to the latest set of technologies in content distribution, OTT. The IPTV technology introduced features that changed the passive role of the client to an active one, revolutionizing the way users consume TV content. Thus, the clients’ habits started to shape the services offered, leading to an anywhere and anytime offer of video content. OTT video delivery is a reflection of those habits, meeting the users’ desire, introducing several benefits discussed in this work over the previous technologies. However, the OTT type of delivery poses several challenges in terms of scalability and threatens the Telecommunications Operators business model, because OTT companies use the Telcos infrastructure for free. Consequently, Telecommunications Operators must prepare their infrastructure for future demand while offering new services to stay competitive. This dissertation aims to contribute with insights on what infrastructure changes a Telecommunications Operator must perform with a proposed bandwidth forecasting model. The results obtained from the forecast model paved the way to the proposed video content delivery method, which aims to improve users’ perceived Quality-of-Experience while optimizing load balancing decisions. The overall results show an improvement of users’ experience using the proposed method.