SCORE: Exploiting Global Broadcasts to Create Offline Personal Channels for On-Demand Access

Abstract

The last 5 years have seen a dramatic shift in media distribution. For decades, TV and radio were solely provisioned using push-based broadcast technologies, forcing people to adhere to fixed schedules. The introduction of catch-up services, however, has now augmented such delivery with online pull-based alternatives. Typically, these allow users to fetch content for a limited period after initial broadcast, allowing users flexibility in accessing content. Whereas previous work has investigated both of these technologies, this paper explores and contrasts them, focusing on the network consequences of moving towards this multifaceted delivery model. Using traces from nearly 6 million users of BBC iPlayer, one of the largest catch-up TV services, we study this shift from push-to pull-based access. We propose a novel technique for unifying both push-and pull-based delivery: the Speculative Content Offloading and Recording Engine (SCORE). SCORE operates as a set-top box, which interacts with both broadcast push and online pull services. Whenever users wish to access media, it automatically switches between these distribution mechanisms in an attempt to optimize energy efficiency and network resource utilization. SCORE also can predict user viewing patterns, automatically recording certain shows from the broadcast interface. Evaluations using our BBC iPlayer traces show that, based on parameter settings, an oracle with complete knowledge of user consumption can save nearly 77% of the energy, and over 90% of the peak bandwidth, of pure IP streaming. Optimizing for energy consumption, SCORE can recover nearly half of both traffic and energy savings.

Throughput–Outage Analysis and Evaluation of Cache-Aided D2D Networks With Measured Popularity Distributions

“…Although there are certain exceptions, user id and content id can generally help identify the user and the video content of each access. More detailed descriptions of the BBC iPlayer dataset can be found in [12], [35], [36].…”

Facebook (A)Live?

“…This allows for a number of new lines of exploration, particularly relating to how live videos are created and consumed by social ties. There have been a small number of studies into live streaming platforms, including Akamai [28], BBC iPlayer [15][16][17]24] or CNLive [20]. These professional platforms serve a wide range of international and professional content, although we emphasise that this differs dramatically from the user generated content discussed above.…”

Measurements and Analysis of a Major Adult Video Portal

“…That said, there are several seminal studies into more traditional video streaming systems. These include catch-up TV [Abrahamsson and Nordmark 2012;Nencioni et al 2015], UGC [Cha et al 2009;Zink et al 2009], VoD [Yu et al 2006] and IPTV [Cha et al 2008;Hei et al 2007;Elkhatib et al 2014]. Studies such as these have provided a range of insights, including content popularity models [Guo et al 2008], optimised caching techniques [Abrahamsson and Nordmark 2012] and improved delivery schemes [Apostolopoulos et al 2002].…”

“…For example, in mainstream VoD services, users often have relatively tight constraints on what they wish to watch. This might be a certain programme, a serialised TV show, or a particular genre [Nencioni et al 2015]. Without these constraints, however, much larger sets of objects become acceptable for consumption, leading to a lesser skew in the popularity.…”

“…Video content is particularly popular: by 2019, 80% of all Internet traffic is predicted to be video [Cisco 2015]. This trend has been accompanied by a range of studies into video on demand (VoD) [Yu et al 2006], Internet TV (IPTV) [Cha et al 2008;Elkhatib et al 2014], user-generated content (UGC) [Cha et al 2009] and catch-up TV [Abrahamsson and Nordmark 2012;Nencioni et al 2015]. Through these, our knowledge has been expanded and, in many cases, the infrastructures improved.…”