Live TV Channels Research Articles

Facing Cold-Start: A Live TV Recommender System Based on Neural Networks

With the increase in the number of live TV channels, audiences must spend increasing amounts of time and energy deciding which shows to watch; this problem is called information overload, and recommender systems (RSs) are effective methods for addressing such problems. Due to the high update rates and low replay rates of TV programs, the item cold-start problem is prominent, and this problem seriously affects the effectiveness of the recommender and limits the application of recommendation algorithms for live TV. To solve this problem better, RSs must consider information in addition to the time slot strategy, which relies on experience. At present, no methods make good use of viewing behavior records. Therefore, in this paper, we proposed a viewing environment model called DeepTV that considers viewing behavior records and electronic program guides and includes a feature generation process and a model construction process. In the feature generation process, we defined seven key features by clustering viewing time, distinguishing positive and negative feedback, capturing continuous viewing preference and introducing the remaining time proportion of candidate programs. We normalize the continuous features and add powers of them. In the model construction process, we regard the live TV recommendation task as a classification problem and fuse the above features by using a neural network. Finally, experiments on industrial datasets show that the proposed model significantly outperforms baseline algorithms.

On the synthetic dataset generation for IPTV services based on user behavior

The adoption of the paradigm shift from push-based media broadcasting to pull-based media streaming has seen a significant growth in the recent decade. IPTV is good example to illustrate this claim. In IPTV systems hundreds (or maybe thousands in near future) of live TV channels and video contents are available to subscribers. In many application domains a clear understanding of access pattern to the items is necessary. However, for security reasons, in IPTV systems this kind of information is not publicly available. In this paper, taking into account a model which mimics the behavior of a typical IPTV user, and with the aid of MovieLens dataset, we produce a trace file or synthetic dataset, named UBSDI. We then show that, this dataset can reflect many properties of real datasets quite realistically. This dataset is publically available and can be used in many applications such as recommender systems, network capacity planning, network dimensioning, and system performance optimization.

Measures to quantify the gain of multicast with application to IPTV transmissions via WiMAX networks

In applications like IPTV, multicasting provides beneficial services. However, due to overhead and problems of multicast transmission, multicasting is not always profitable. In order to make well-justified decisions whether it is worthwhile to use multicasting or not, its efficiency must be quantified. Therefore, the metric of `multicast gain' is introduced as a measure for the bandwidth reduction which can be expected when using multicast (instead of multiple unicast). Different definitions for multicast gain are given to cover different types of links. As an application of our metric, multicast transmission of live TV channels in WiMAX-based access networks is analyzed. WiMAX as one of the 4G candidates can transmit IPTV services to mobile subscribers because of salient features such as multicast support, wide coverage range and high bandwidth. In OFDMA-based WiMAX the smallest logical bandwidth allocation unit is a slot. In this article, we use the term slot to measure the efficiency of multicasting in WiMAX networks. We show that for unpopular TV channels, using unicast flows can be preferable.

Measurement study on P2P streaming systems

Originally used as the default infrastructure for efficient file sharing, peer-to-peer (P2P) architecture achieved great successes. Now, the P2P model has been adopted for many other distributed applications, such as instant message and phone services, Internet gaming, and large-scale scientific computing. In recent years, P2P streaming systems experienced tremendous growth and became one of the largest bandwidth consumers on the Internet. Compared to standard file sharing systems, the streaming services show unique characteristics with more stringent time constraints and require much higher network bandwidth. It is extremely important to evaluate and analyze existing applications, and investigate the merits and weaknesses in these systems for future development. In this paper, we conduct a comprehensive measurement study on two of the most popular P2P streaming systems, namely, PPLive and PPStream. They are very popular P2P streaming applications, and serving millions of registered users with hundreds of live TV channels and millions of other video clips. In our measurement, we deploy our collectors in China, and both live TV and video-on-demand (VoD) channels are evaluated. We record run-time network traffic on the client side, compare and analyze the characteristics of these channels based on their popularity. For both categories, we perceive that, in general, the two measured P2P streaming systems provide satisfactory experience to the audiences for all channels regardless of popularity. However, the most of data are downloaded from the dedicated servers for unpopular channels. We also observe that live TV channels show better peer coordination than VoD channels. Beside the traffic, we have also collected cache replacement information for VoD channels, and these measurement results can help us understand the caching mechanism of P2P streaming systems. With the support of the cache, VoD channels perform better than their counterparts in the live TV category in terms of data transmission, workload distribution, and signal traffic overhead. Overall, our results reveal that although P2P streaming systems can usually provide excellent viewing experience for popular channels, there are still challenges to fully support unpopular channels. New designs and algorithms are in urgent need, especially for unpopular live TV channels.

Multicast Gain for IPTV Transmission in WiMAX Multi-hop Relay Networks

Due to characteristics such as: multicast support, wide coverage range, high bandwidth and mobility support, WiMAX could be a leading solution to deliver bandwidth-hungry IPTV services to mobile users. Mobile multi-hop relay (MMR) was proposed as an amendment of the current mobile WiMAX standard to provide relaying capabilities. Relays are deployed as a cost-effective solution to extent coverage area and increase throughput without deploying expensive base stations. In this paper, we introduce multicast gain as a performance criterion, which can be used for computing multicast efficiency. In order to quantify the benefits of multicasting, we analyze multicast transmission for delivery of live TV channels in MMR networks, and determine the gain of access and relay links. The quantification of the efficiency of multicasting can be used by IPTV service providers in resource provisioning, access control or decision support mechanisms in delivery of different TV channels.

Global 1-Mbps Peer-Assisted Streaming: Fine-Grain Measurement of a Configurable Platform

High-resolution video is defining a new age of peer-assisted video streaming over the public Internet. Streaming over 1-Mbps videos in a scalable and global manner presents a challenging milestone. In this work, we examine the feasibility of 1-Mbps streaming through a global measurement study. In contrast to previous measurement studies that crawl commercial applications, we conduct fine-grain, controlled experiments on a configurable platform. We developed and deployed FastMesh-SIM, a novel peer-assisted streaming system that leverages proxies, scalable streaming trees and IP multicast to achieve 1-Mbps streaming at a global scale. With the configurability-enabled design, we are allowed to conduct controlled experiments by varying design decisions under a wide range of operating conditions, and measuring in-depth, finegrain metrics at a per-hop, per-segment level. We collected hundreds of hours of streaming traces that broadcast live TV channels to more than 120 peers and 30 proxies, with a global geographic footprint over 8 different countries. Data analysis demonstrates how a set of design decisions collectively overcome the 1-Mbps barrier. The various operational issues we uncovered provide insights to service providers that want to deploy a commercial system at a larger scale and a higher streaming rate. By comparing theory and practice, we also confirm theory-inspired architectural decisions, and show that our system indeed achieves throughputs close to theoretical upper-bound calculated under many ideal assumptions.

Social TV

Internet Television (IPTV) is emerging as a new delivery method for offering access to digital TV and interactive services which potentially merge the “lean back” broadcast experience with more bidirectional “lean forward” interactivity. Within these environments, there is a significant growth in the volume and variety of content being offered which increases the difficulty and burden for the end-user in locating relevant content and finding something to watch. In this article we detail the design, implementation, and evaluation of a production IPTV service which operates on our University campus network. Our approach makes use of social networks as a mechanism for providing social awareness to individual users of an IPTV system. The goal is to facilitate an intuitive and simple media selection mechanism when considering vast amounts of live TV channels and on-demand content. Ultimately, we seek to explore whether social awareness can or does influence user behavior.

Exploiting the In-Network Capabilities of Multicast to Discover Proximate IPTV Channels

IPTV has become the next generation of television due, in part, to its ability to support features that have been lacking in conventional broadcasting—for example, end-user interactivity, personalisation and localisation. Providers are also searching for the most efficient delivery methods to provide the greatest amount of contents at the lowest cost. At present IPTV uses IP multicast to deliver live TV channels in an over-provisioned walled-garden network due to issues of deploying multicast and QoS challenges in the public Internet. However, IPTV is likely to shift into some parts of the public Internet in the future as a managed service. Multicast routing is performed on a per-session destination-address basis so each router maintains a table of all of the multicast addresses to which the content is being forwarded. We exploit this information to discover and join the in-progress channels of geographically proximate users and to create a new incentivised premium service in future IPTV networks called ProxyTV. This approach is expected to minimise network bandwidth requirements as it enables ISPs to optimise bandwidth on their edge networks. This becomes increasingly significant as TV content consumes more and more bandwidth, especially with the onset of HD and 3D capabilities. In this paper, we have presented in detail the concept with the results of a survey and an analysis of network traffic to justify the proposed approach.

A statistical model of FM‐TV spectra for satellite interference and distortion prediction

AbstractThe requirement for a model of FM‐TV spectra in the planning procedure of satellite communication systems is introduced. Based on long‐term measurements of live TV channels, statistical properties of video spectra are examined and probability distributions for the luminance and chrominance components are proposed.The spectrum of the frequency‐modulated signal is then derived, and signal distortion due to bandlimiting is calculated. Adjacent and cochannel interference effects are also investigated, with example cases illustrating influences of subcarrier loading and energy dispersion.The proposed model, which describes FM‐TV spectra in terms of random variables, makes it possible to examine relative effects of system parameters, and will, therefore, be of benefit in the planning of new satellite services.