Content storage architectures for boosted IPTV service

Abstract

Television (TV) consumers adore interactivity and personalization. Internet Protocol television (IPTV) systems help satisfy this desire by providing different services including video-on-demand (VoD), network personal video recording (NPVR), and time shift TV (TSTV). However, these services place a heavy traffic load on the network by requiring a unicast video stream for each active customer. This paper discusses means to reduce the network traffic load by introducing storage deep in the network-thus avoiding the need for unicast traffic support over the metro or core network-and algorithms to place content intelligently on those storage devices. An algorithm for intelligent redistribution is described that endeavors to place the most appropriate content close to consumers. The paper discusses further how this new paradigm of network storage can help improve quality of experience for the IPTV consumer and can assist in the deployment of Internet video and sharing of user-generated content (UGC).

Window-Based Popularity Caching for IPTV On-Demand Services

“…In reality, content popularity distribution is hard to know in advance and some previous works asserted that the popularity distribution will evolve and be volatile [6,7]. De Vleeschauwer and Laevens [7] proposed a generic model that captures popularity evolution trend and applied exponential smoothing (ES) method to track the momentary popularity.…”

“…De Vleeschauwer and Laevens [7] proposed a generic model that captures popularity evolution trend and applied exponential smoothing (ES) method to track the momentary popularity. Verhoeyen et al [6] proposed Alcatel-Lucent 5910 Video Server caching architecture (A-Lu 5910), which also used ES method for tracking each VOD popularity. A-Lu 5910 aimed to allocate content to cache dynamically and respond to adjust popularity automatically.…”

O desenvolvimento da TV não linear e a desprogramação da grelha

“…O projeto deste armazenamento foi estudado para as redes de televisão por cabo (Wauters et al, 2007), para os serviços baseados na Internet (Ho, Poon, & Lo, 2007) e para os serviços de IPTV (D. De Vleeschauwer & Laevens, 2009;Krogfoss, Sofman, & Agrawal, 2008;Verhoeyen, De Vleeschauwer, & Robinson, 2008). Outras investigações também desenvolveram algoritmos para prever qual o conteúdo mais procurado e definir onde cada tipo de programa deve ser gravado (Danny De Vleeschauwer et al, 2009 (Bury & Li, 2015).…”

Towards intelligent scheduling of multimedia content in future access networks

“…In [1], [2], the authors argue that the evolution of IPTV services from VoD to TimeShiftedTV services causes an explosion in the requested resources which can only be tackled by effectively caching requested multimedia content. Several caching algorithms have been proposed for streaming multimedia services [3], [4].…”