Internet Video Streaming Services Research Articles

Assessing the environmental impacts of wildlife television programmes

Abstract Wildlife TV programmes reach very large global audiences, but it is hard to measure their benefits for the natural world. The commercial need to entertain as well as inform means that many films omit the presence and impacts of people, giving the false impression that we do not affect the natural world. Many wildlife film‐makers want to address the linked climate and biodiversity emergencies, but the obligation to be impartial has made some broadcasters reluctant to commission and show films that seek to change people's behaviour. Internet video streaming services are less constrained, but commercial considerations do apply. Privately funded programmes need not be commercially successful or editorially impartial. They can be distributed over the internet, independently of broadcasters. Increasingly, impact producers are being employed as key components in wider campaigns, to maximise their effect. Mainstream TV companies are starting to follow. Making international wildlife programmes entails a large carbon footprint, much of it due to travel. Many broadcasters and production companies are committing to become carbon‐neutral. Programme‐makers would welcome research that helps them maximise the real‐world impacts of their films and quantifies positive changes for nature. A free Plain Language Summary can be found within the Supporting Information of this article.

An Adaptive Neuro-Fuzzy Model for Quality Estimation in Wireless 2D/3D Video Streaming Systems

Delivering high Quality of Experience (QoE) is essential to the success of today’s subscription for internet video streaming services. Quality of Service (QoS) metrics are considered by the research community as the most influential factor on video QoE. Therefore, establishing QoS-QoE correlation becomes critical for improving video QoE estimation. This paper presents experimental development of effective correlation between QoE and QoS for both 2D and 3D video streaming services. This is then used to build an objective QoE estimation model for real-time streaming of both 2D and 3D video contents over wireless networks. This model is based on using Adaptive Neural Fuzzy Inference System (ANFIS) to estimate the perceived video QoE. The proposed QoE model was trained with a set of media and packet layers’ metrics, taking into account the effect of video content type, dimension, and different packet loss metrics. The performance of the proposed QoE estimation model shows a considerable estimation accuracy with a correlation coefficient of 92% and 0.167 RMSE.

A Practical Evaluation of Rate Adaptation Algorithms in HTTP-based Adaptive Streaming

The HTTP-based Adaptive Streaming (HAS) techniques are widely used in Internet video streaming services, including YouTube and Netflix. The Dynamic Adaptive Streaming over HTTP (DASH) is the latest international standard that facilitates the interoperability of different HAS techniques of various vendors. DASH specification defines the media presentation description (MPD), which describes a list of available content, URL addresses, and the segment format. The rate adaptation algorithms, however, are not part of the standard, and the details of the algorithms are left to vendors. As a result, there are many different algorithms adopted in both commercial and open source players while the detailed algorithms and their performance are barely understood. In this paper, we investigate the detailed operations of the different players by code level analysis and through reverse engineering. Specifically, we present the pseudo codes of 3 open source players and devise a method to obtain the detailed operation information, e.g., bitrate and buffer amount, of popular streaming players whose source codes are not publicly available. We conduct extensive experiments on our testbed and provide suggestions based on the behaviors of these players, including the repeated over-estimation of the available bandwidth, unfair bitrate selection when multiple players compete for the bandwidth, and insensitivity of Quick UDP Internet Connections (QUIC) protocol to the varying network bandwidth.

Cost-Aware Capacity Provisioning for Internet Video Streaming CDNs

With the increasing popularity of the Internet video streaming services (e.g. YouTube and Netflix), content delivery networks (CDNs) are heavily used to stream video contents to users, and consume more and more power and bandwidths in recent years. In this paper, we investigate the problem of saving a video streaming CDN’s operating expense, including both its energy cost and the traffic cost. From our measurement study on the CDN infrastructure of Youku, which is the largest video site in China, we find that there exists an inherent conflict between improving a video streaming CDN’s energy efficiency for power saving, and maintaining the CDN’s ISP-friendly server selection policy. To address this problem, we propose a cost-aware capacity provisioning algorithm, which dynamically plans the service capacities of a CDN’s server clusters in numerous ISPs, and optimizes its overall operating cost regarding both the energy consumptions and the cross-ISP traffics. By using the workload derived from real-world measurement and applying actual power and bandwidth price parameters, we show with experiments that our approach can significantly reduce a video streaming CDN’s overall operating cost, and avoid frequent server switches effectively. To our best knowledge, this work is the first one that identifies and resolves the inherent conflict between a CDN’s energy efficiency and its ISP-friendly policy.

Performance Evaluation of Peer-to-Peer Progressive Download in Broadband Access Networks

P2P (Peer-to-Peer) file sharing architectures have scalable and cost-effective features. Hence, the application of P2P architectures to media streaming is attractive and expected to be an alternative to the current video streaming using IP multicast or content delivery systems because the current systems require expensive network infrastructures and large scale centralized cache storage systems. In this paper, we investigate the P2P progressive download enabling Internet video streaming services. We demonstrated the capability of the P2P progressive download in both laboratory test network as well as in the Internet. Through the experiments, we clarified the contribution of the FTTH links to the P2P progressive download in the heterogeneous access networks consisting of FTTH and ADSL links. We analyzed the cause of some download performance degradation occurred in the experiment and discussed about the effective methods to provide the video streaming service using P2P progressive download in the current heterogeneous networks.

Enabling on-demand internet video streaming services to multi-terminal users in large scale

In the ubiquitous era of streaming multimedia over the Internet, an increasing number of users are accessing to Internet video services through varieties of terminals, e.g PC, Set-Top Box IPTV and mobile phones, etc. Whereas extending streaming media to multiple ends adds much to consumer electronic industry, the challenge remains on how to provide on-demand services to heterogeneous users with different bandwidth requirement, access manner, QoS demand, etc. The success of a large-scale video streaming system relies heavily on how they address the critical issues in QoS, scalability and heterogeneity, yet no single system has delivered the expected scale and quality for commercial applications. Thus this paper provides a complete portfolio of solutions for providing multiple Internet video streaming services (live video broadcast, video on demand, video downloading) on 3 Screens (PC, TV, mobile), through a unified Peer-to-Peer (P2P) video platform. Upon manageable P2P framework, different terminals access are supported and end user bandwidth are utilized to scale the system. With our multi-process server management, efficient topology organization, enhanced UDP transmission and intelligent content distribution, our P2P streaming media platform is proved to have lower operation cost and higher user quality. The significance of such paper lies not only in the proposed system framework and on-field engineering techniques to enable an enterprise-grade and telecom-class application, but also the industrial insights inside designing such commercialized large-scale platform with full consideration of function, process, configuration and cost1.