Catch-up TV Services Research Articles

EdgeMart : A Sustainable Networked OTT Economy on the Wireless Edge for Saving Multimedia IP Bandwidth

With the advent of 5G+ services, it has become increasingly convenient for mobile users to enjoy high-quality multimedia content from CDN driven streaming and catch-up TV services (Netflix, iPlayer) in the (post-) COVID over-the-top (OTT) content rush. To relieve ISP owned fixed-line networks from CDN streamed multimedia traffic, system ideas (e.g., Wi-Stitch in [ 45 ]) have been proposed to (a) leverage 5G services and enable consumers to share cached multimedia content at the edge, and (b) consequently, and more importantly, reduce IP traffic at the core network. Unfortunately, given that contemporary multimedia content might be a monetized asset, these ideas do not take this important fact into account for shared content. We present EdgeMart —a content provider (CP) federated, and computationally sustainable networked (graphical) market economy for paid-sharing of cached licensed (OTT) content with autonomous users of a wireless edge network (WEN). EdgeMart is a unique oligopoly multimedia market (economy) that comprises competing networked sub-markets of non-cooperative content sellers/buyers—each sub-market consisting of a single buyer connected (networked) to only a subset of sellers. We prove that for any WEN-supported supply-demand topology , a pure strategy EdgeMart equilibrium exists that is (a) nearly efficient (in a microeconomic sense) indicating economy sustainability, (b) robust to edge user entry/exit, and (c) can be reached in poly-time (indicating computational sustainability). In addition, we experimentally show that for physical WENs of varying densities, a rationally selfish EdgeMart economy induces similar orders of multimedia IP traffic savings when compared to the ideal (relatively less practical), altruistic , and non-monetized “economy” implemented atop the recently introduced Wi-Stitch WEN-based content trading architecture. Moreover, the EdgeMart concept helps envision a regulated edge economy of opportunistic (pay per licensed file) client services for commercial OTT platforms.

Campaign to encourage pharmacy use 'irresponsible and extremely unhelpful', says negotiator

An advertising campaign intended to encourage more people to visit pharmacies for minor illnesses has been called “irresponsible and extremely unhelpful” by the Pharmaceutical Services Negotiating Committee (PSNC). The NHS England campaign, ‘Help Us Help You‘ will feature a series of “movie-inspired” advertisements on catch-up TV services, online video, radio and social media, with titles […]

Reaction or Speculation: Building Computational Support for Users in Catching-Up Series Based on an Emerging Media Consumption Phenomenon

A growing number of people are using catch-up TV services rather than watching simultaneously with other audience members at the time of broadcast. However, computational support for such catching-up users has not been well explored. In particular, we are observing an emerging phenomenon in online media consumption experiences in which speculation plays a vital role. As the phenomenon of speculation implicitly assumes simultaneity in media consumption, there is a gap for catching-up users, who cannot directly appreciate the consumption experiences. This conversely suggests that there is potential for computational support to enhance the consumption experiences of catching-up users. Accordingly, we conducted a series of studies to pave the way for developing computational support for catching-up users. First, we conducted semi-structured interviews to understand how people are engaging with speculation during media consumption. As a result, we discovered the distinctive aspects of speculation-based consumption experiences in contrast to social viewing experiences sharing immediate reactions that have been discussed in previous studies. We then designed two prototypes for supporting catching-up users based on our quantitative analysis of Twitter data in regard to reaction- and speculation-based media consumption. Lastly, we evaluated the prototypes in a user experiment and, based on its results, discussed ways to empower catching-up users with computational supports in response to recent transformations in media consumption.

A video engine supported by social buzz to automatically create TV summaries

Viewers post a lot of TV program-related information on social networks while they are watching TV, especially during its key moments. Therefore, this social buzz has the potential to be used as an automatic editorial criterion. Having this premise in consideration, this paper reports on the nowUP solution, a service developed with the main goal of automatically creating TV summaries of popular television programs (like football matches, talent or reality shows) based on the Twitter activity and integrating a part of that activity in the TV show summary. A data-mining engine continuously processes the activity of this social network looking for tweets associated with the TV shows. Based on the program metadata it indexes the twitter activity; correlates tweets; and creates clusters of peaks, being the relevant clusters associated with the highlights of the TV show. With this, the video engine automatically creates a full video summary (an edited sequence of TV highlights) and publishes it in an online platform and on a Catch-up TV service. The paper reports on the nowUP development and on the results of its evaluation, namely comparing its outputs with official editorial/professional video summaries. The results show that the solution was very successful in achieving the project main goal and users want to have access to this type of social buzz-based video summaries. The nowUP solution also promises potential gains in the value chain of TV producers and broadcasters.

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

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.

Catch-up TV analytics: statistical characterization and consumption patterns identification on a production service

Multimedia IP Television services, such as on-demand Catch-up TV, are in an active migration process towards Over-The-Top (OTT) delivery using state-of-the-art Content Delivery Networks (CDNs). Maintaining the same Quality-of-Experience (QoE) of managed IPTV networks is challenging and requires a thorough understanding of users’ behaviors and content demand characteristics. This article leverages Catch-up TV usage logs obtained from a Pay-TV operator’s live production IPTV service containing over 1 million subscribers to characterize and extract insights from service utilization at a scale and scope not yet addressed in the literature. A detailed analysis on the characteristics of users’ viewings is performed, with a study of when, where, and how often users access the service, along with how they behave during each viewing session. The results show that Catch-up TV consumption exhibits very high levels of utilization throughout the day, and is heavily polarized towards specific genres, recently aired programs, and content broadcasted during prime-time. The superstar effect is notorious. This analysis is complemented by a service optimization perspective, which shows that large gains are achievable by caching popular programs, and by loading content in advance to users’ Set-Top-Boxes (STBs). This comprehensive research study is supplemented by detailed statistical information tables, which highlight the feasibility of efficiently migrating Catch-up TV services to OTT-scenarios, and provide the foundations for future works able to explore these results.

Guest editorial: Networked television

This special issue on networked television consists of a selection of the best papers of the 7th European Interactive TV Conference (EuroITV 2009), which was held in Leuven, Belgium, in June of 2009. Networked television is a new concept, which is about TV sets becoming yet another node in many IP-based networks, such as managed IPTV networks and in-home networks. This increased level of connectivity allows for new types of services and will eventually result in the seamless integration of interactive TV into the wide range of other services that people have at their disposal. The papers in this special issue consider various challenges to make this vision a reality, such as scalability of catch-up TV services and the integration of interactive TV services and home control automation. The goal of EuroITV 2009 was to provide a discussion and dissemination platform for topics like these, both for industry and academia, so as to fuel new business and worldclass research in networked television. The conference program consisted of a technical track, a business track, and a track on user studies, embodying EuroITV’s unique multidisciplinary approach. The conference acceptance rate was 41% out of 88 submissions, which illustrates that it is a selective and popular event. The presented papers were from researchers and practitioners from Europe, Asia, and the Americas. EuroITV 2009 was attended by a total of 197 people, many of whom also contributed to the pre-conference workshops, the industry track, the tutorials, and the doctoral consortium. From the papers presented in Leuven, we invited the best six to submit an extended version of their work for this special issue of Multimedia System Journal, with the requirement that they should top up their EuroITV paper with at least 30% of new results. After a multi-round reviewing process with three or four experts reviewing each paper, we were able to retain three papers, which are the ones that are now part of this special issue. In the first paper, Avramova, De Vleeschauwer, Wittevrongel, and Bruneel present a rigorous performance analysis of a distributed caching algorithm for catch-up television. The authors developed the algorithm to avoid overloads in managed IPTV networks and evaluated it through extensive simulations. They conclude that their new algorithm clearly outperforms existing caching algorithms and also investigate how to configure the algorithm’s parameters for optimal performance. The second paper, by Viana and de Lucena, is about a software platform that seamlessly integrates interactive TV and home control services. The main advantage of their work is that the platform allows developers to easily write mixed interactive TV-home control applications. Such applications also facilitate new user experiences, such as synchronizing home appliances with the audio/video streams of a movie. The novelty of their work is that the platform transparently combines Ginga middleware technology (for interactive TV) with OSGi (for home control), while at the same time exploiting the declarative part of the Ginga middleware. C. Hesselman (&) Novay, P.O. Box 589, 7500AN Enschede, The Netherlands e-mail: cristian.hesselman@novay.nl