Digital technology and entertainment is a significant driver of electricity use globally, resulting in increased GHG emissions. Research has been conducted on electricity use associated with adigital services, but to date no complete study of television distribution has been conducted. Here we present the first assessment of electricity used for distribution and viewing of television over different distribution platforms terrestrial, satellite, cable and online streaming. We use a novel methodology that combines life cycle assessment techniques with models of the diversity of actual user behaviour, derived from detailed audience monitoring and online behaviour analytics data. This can be applied to assess overall electricity usage for a given media company's services and allows comparison of the electricity demanded per viewerhour of each distribution platform. We apply this to a representative national TV provider - the British Broadcasting Corporation – and show the mean estimate for BBC distribution/viewing electricity use in 2016 is 2171 GWh, resulting in emissions of 1.12 MtCO2e. We show that viewing over streaming, cable and satellite platforms used a mean of 0.17–0.18 KWh per device-hour (88–93 gCO2e) while terrestrial broadcast used a mean of 0.07 kWh (36 gCO2e). We identify home networking equipment and set-top boxes as key hotspots in the system, and show that though streaming is similar in impact to cable and satellite, this is because people use smaller devices to view – meaning the networking equipment in and beyond the home has a higher impact while the end device has a lower one.

The exponential growth in online content consumption is a key concern for designing future generation network architectures. In this paper, we use content access patterns from a large trace of content accesses comprising about half the population of United Kingdom to make the case that a large portion of the backhaul load can be mitigated by content sharing amongst edge devices. We explore various models for edge devices to store and share content amongst each other, ranging from reactive opportunistic sharing to predicting future content access and speculatively placing content on strategic devices prior to request. We analyse the performance of each of these models in terms of content placement and traffic savings, which are constrained by the storage available on edge devices, the performance of the speculation engine and the wireless channel conditions. We formulate and solve at scale an optimisation problem for strategically placing content for sharing within a geographically localised cell to show such an approach can save up to 47% of the traffic generated from a small cell.

P2P sharing amongst consumers has been proposed as a way to decrease load on Content Delivery Networks. This paper develops an analytical model that shows an additional benefit of sharing content locally: Selecting close by peers to share content from leads to shorter paths compared to traditional CDNs, decreasing the overall carbon footprint of the system. Using data from a month-long trace of over 3 million monthly users in London accessing TV shows online, we show that local sharing can result in a decrease of 24-48% in the system-wide carbon footprint of online video streaming, despite various obstacle factors that can restrict swarm sizes. We confirm the robustness of the savings by using realistic energy parameters drawn from two widely used settings. We also show that if the energy savings of the CDN servers are transferred as carbon credits to the end users, over 70% of users can become carbon positive, i.e., are able to support their content consumption without incurring any carbon footprint, and are able to offset their other carbon consumption. We suggest carbon credit transfers from CDNs to end users as a novel way to incentivise participation in peer-assisted content delivery.

Wi-Fi, the most commonly used access technology at the very edge, supports download speeds that are orders of magnitude faster than the average home broadband or cellular data connection. Furthermore, it is extremely common for users to be within reach of their neighbours' Wi-Fi access points. Given the skewed nature of interest in content items, it is likely that some of these neighbours are interested in the same items as the users. We sketch the design of Wi-Stitch, an architecture that exploits these observations to construct a highly efficient content sharing infrastructure at the very edge and show through analysis of a real workload that it can deliver substantial (up to 70%) savings in network traffic. The Wi-Stitch approach can be used both by clients of fixed-line broadband, as well as mobile devices obtaining indoors access in converged networks.

Wi-Fi, the most commonly used access technology at the very edge, supports download speeds that are orders of magnitude faster than the average home broadband or cellular data connection. Furthermore, it is extremely common for users to be within reach of their neighbours' Wi-Fi access points. Given the skewed nature of interest in content items, it is likely that some of these neighbours are interested in the same items as the users. We sketch the design of Wi-Stitch, an architecture that exploits these observations to construct a highly efficient content sharing infrastructure at the very edge and show through analysis of a real workload that it can deliver substantial (up to 70%) savings in network traffic. The Wi-Stitch approach can be used both by clients of fixed-line broadband, as well as mobile devices obtaining indoors access in converged networks.

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.

Mobile data offloading can greatly decrease the load on and usage of current and future cellular data networks by exploiting opportunistic and frequent access to Wi-Fi connectivity. Unfortunately, Wi-Fi access from mobile devices can be difficult during typical work commutes, e.g., via trains or cars on highways. In this paper, we propose a new approach: to preload the mobile device with content that a user might be interested in, thereby avoiding the need for cellular data access. We demonstrate the feasibility of this approach by developing a supervised machine learning model that learns from user preferences for different types of content, and propensity to be guided by the user interface of the player, and predictively preload entire TV shows. Testing on a data set of nearly 3.9 million sessions from all over the U.K. to BBC TV shows, we find that predictive preloading can save over 71% of the mobile data for an average user.

Using nine months of access logs comprising 1.9 Billion sessions to BBC iPlayer, we survey the UK ISP ecosystem to understand the factors affecting adoption and usage of a high bandwidth TV streaming application across different providers.We find evidence that connection speeds are important and that external events can have a huge impact for live TV usage.Then, through a temporal analysis of the access logs, we demonstrate that data usage caps imposed by mobile ISPs significantly affect usage patterns, and look for solutions.We show that product bundle discounts with a related fixed-line ISP, a strategy already employed by some mobile providers, can better support user needs and capture a bigger share of accesses.We observe that users regularly split their sessions between mobile and fixed-line connections, suggesting a straightforward strategy for offloading by speculatively pre-fetching content from a fixed-line ISP before access on mobile devices.

In search of scalable solutions, CDNs are exploring P2P support.However, the benefits of peer assistance can be limited by various obstacle factors such as ISP friendlinessrequiring peers to be within the same ISP, bitrate stratificationthe need to match peers with others needing similar bitrate, and partial participation-some peers choosing not to redistribute content.This work relates potential gains from peer assistance to the average number of users in a swarm, its capacity, and empirically studies the effects of these obstacle factors at scale, using a monthlong trace of over 2 million users in London accessing BBC shows online.Results indicate that even when P2P swarms are localised within ISPs, up to 88% of traffic can be saved.Surprisingly, bitrate stratification results in 2 large sub-swarms and does not significantly affect savings.However, partial participation, and the need for a minimum swarm size do affect gains.We investigate improvements to gain from increasing content availability through two well-studied techniques: content bundlingcombining multiple items to increase availability, and historical caching of previously watched items.Bundling proves ineffective as increased server traffic from larger bundles outweighs benefits of availability, but simple caching can considerably boost traffic gains from peer assistance.

"Catch-up", or on-demand access of previously broadcast TV content over the public Internet, constitutes a significant fraction of peak time network traffic. This paper analyses consumption patterns of nearly 6 million users of a nationwide deployment of a catch-up TV service, to understand the network support required. We find that catch-up has certain natural scaling properties compared to traditional TV: The on-demand nature spreads load over time, and users have much higher completion rates for content streams than previously reported. Users exhibit strong preferences for serialised content, and for specific genres. Exploiting this, we design a Speculative Content Offloading and Recording Engine (SCORE) that predictively records a personalised set of shows on user-local storage, and thereby offloads traffic that might result from subsequent catch-up access. Evaluations show that even with a modest storage of ~32GB, an oracle with complete knowledge of user consumption can save up to 74% of the energy, and 97% of the peak bandwidth compared to the current IP streaming-based architecture. In the best case, optimising for energy consumption, SCORE can recover more than 60% of the traffic and energy savings achieved by the oracle. Optimising purely for traffic rather than energy can reduce bandwith by an additional 5%.

This study estimated the carbon footprint of watching broadcast television using digital terrestrial television and online delivery of video-on-demand. The carbon footprint for digital terrestrial television was found to be 0.088 kg CO2e/viewer-hour and for online delivery of video-on-demand ranges from 0.030-0.086 kg CO2e/viewer-hour. This was based mainly on the energy consumption in the use phase. Results were sensitive to the number of viewers per display. It was found that the largest environmental impact from watching television is due to the power consumption of the consumer equipment. This amounts to 76% of the total for digital terrestrial television and 78% and 37% for video-on-demand using desktop and laptop computers respectively. The trend for larger television screens which have higher power consumption could increase this. Programme production contributes 12% to 35% and distribution contributes 10-28%. It was found that the audience size of a digital terrestrial channel and whether or not an aerial amplifier was used have a large effect on which distribution method appears to be the most energy efficient.

When broadcasting sports events it is useful to be able to place virtual 3D annotations on the ground, to indicate things such as world record lines and distances. This requires the camera pose to be estimated in real time, so that the graphics can be rendered to match the camera view. Whilst camera calibration data can be obtained by using sensors on the camera mount and lens, such sensors can be impractical or expensive to install, and often the broadcaster only has access to the video feed itself. An image-based method of tracking the camera movement is thus the only practical approach in many situations. This paper reviews past work on image-based camera tracking, and presents the method we have developed. Our approach uses a method based on randomized trees for initial feature identification, and a KLT-based tracker to track features from frame to frame. Results of our system are presented on a selection of material representative of typical broadcast athletics, and the performance benefits of the approach we have taken are compared to a simple KLT-based tracker.

Recent studies have estimated that television and related equipment account for 1.8% of global greenhouse gas (GHG) emissions and Information and Communication Technology is responsible for 2% of global GHG emissions. Both these sectors are forecast to grow as the developing world increases its uptake of technology.This study estimates the carbon footprint of two different ways of watching television: using broadcast digital terrestrial television (DTT) and video-ondemand (VOD) over the Internet. It compares the two distribution methods and the corresponding consumer equipment. It uses the principles of life cycle assessment (LCA) to derive the carbon footprints using a bottom-up analysis of the system applied to the BBC’s television services. This was the only environmental impact considered and was mainly from electricity use. Equipment manufacturing was not included.

Radio cameras allow more freedom when deploying cameras to cover events but there are some places where it is not possible to place a cameraman, such as on a football pitch during play, in a boxing ring or on the back of a race horse. Small cameras can be mounted on the event participants, for example on the head of a boxing referee but the motion of the mounting surface makes viewing uncomfortable and it is not possible to control the shot framing. This paper describes a system for both stabilising an image and allowing control of shot-framing for cameras mounted on unstable and uncontrollable surfaces.

The term “Augmented Reality” covers a wide range of applications, from the overlay of virtual graphics on a real scene using a head-mounted display for use in areas such as industrial maintenance, through to the insertion of real-time virtual graphics in TV programmes. Fundamental to all these applications is the need to be able to accurately track the motion of the camera, so that the graphics may be rendered so as to appear rigidly locked to the real world. To overcome the limitations of existing tracking systems, the MATRIS project has developed a real-time system for measuring the movement of a camera, which uses image analysis to track naturally occurring features in the scene, and data from an inertial sensor. No additional sensors, special markers, or camera mounts are required. This paper gives an overview of the system, provides the context for the other articles in this journal and presents some results.