Live multimedia streaming from mobile devices is rapidly gaining popularity but little is known about the QoE they provide. In this paper, we examine the Periscope service. We first crawl the service in order to understand its usage patterns. Then, we study the protocols used, the typical quality of experience indicators, such as playback smoothness and latency, video quality, and the energy consumption of the Android application.
Live mobile streaming is subject to increasing attention, including from the sociological point of view @cite_0 . In the technical domain, research about live streaming focused on issues such as distribution optimization @cite_14 , including scenarios with direct communication among devices @cite_9 . The crowdsourcing of the streaming activity itself also received particular attention @cite_12 @cite_17 .
@cite_14 @cite_9 @cite_0 @cite_12 @cite_17
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MPEG has recently released a first public draft of the new Dynamic Adaptive Streaming over HTTP (DASH) specification. The new streaming technique is based on the 3GPP and partly also on the Open IPTV Forum (OIPF) specifications. In this paper, we give an overview about the new DASH specification with a special focus on Live streaming services. In order to re-use existing web content distribution schemes, the new streaming technique provides the live stream as a sequence of files, which are continuously downloaded by the streaming client. This way of streaming introduces new delay components into the system streaming. Live Streaming technology is often used for events like sport events to allow other users to virtually participate. It is generally preferred to minimize the end-to-end delay for live services. In the paper, we identify and analyze the different delay components of the new adaptive HTTP streaming technique and how they contribute to the end-to-end delay of live services. We also discuss the dependencies and system implications when minimizing the end to end delay. The evaluation principles are also applicable for other adaptive HTTP streaming formats. As video traffic has dominated the data flow of smartphones, traditional cellular communications face substantial transmission challenges. In this work, we study mobile device-to-device (D2D) video distribution that leverages the storage and communication capacities of smartphones. In such a mobile distributed framework, D2D communication represents an opportunistic process to selectively store and transmit local videos to meet the future demand of others. The performance is measured by the service time, which denotes the elapsed period for fulfilling the demand, and the corresponding implementation of each device depends on the video’s demand, availability, and size. The main contributions of this work lie in (1) considering the impact of video size in a practical mobile D2D video distribution scenario and proposing a general global estimation of the video distribution based on limited and local observations; (2) designing a purely distributed D2D video distribution scheme without the monitoring of any central controller; and (3) providing a practical implementation of the scheme, which does not need to know the video availability, user demand, and device mobility. Numerical results have demonstrated the efficiency and robustness of the proposed scheme. Mobile streaming video technologies (MSVTs) such as Meerkat and Periscope, which allow users an easily accessible way to stream live video to followers, have the potential to reshape the way people think about any right to privacy they may have in public places, as well as the rights of people to record video in public places. Using legal research methodology, this article examines the privacy law implications of MSVTs, finding that the intrusion upon seclusion tort is unequipped to provide remedies for potential privacy harms and that the First Amendment likely protects live streaming activities of users. With the advances in personal computing devices and the prevalence of broadband network and wireless mobile network accesses, end-users are no longer pure content consumers, but contributors, too. In today's crowdsourced streaming systems, numerous broadcasters lively stream their video content, e.g., live events or online game scenes, to fellow viewers. Compared to professional video producers and broadcasters, these new generation broadcasters are geo-distributed globally and highly heterogeneous in terms of the generated video quality and the network system configurations. The scalability and heterogeneity challenges therefore lie on both broadcasters and the viewers, which call for massive transcoding, and two critical issues: 1) choosing video representation set that maximizes viewer satisfaction and 2) allocating computational resources that minimize operational costs, must be systematically optimized in the global scale. In this paper, we present a generic framework utilizing the powerful and elastic cloud computing services for crowdsourced live streaming with heterogeneous broadcasters and viewers. We jointly consider the viewer satisfaction and the service availability pricing of geo-distributed cloud resources for transcoding. We develop an optimal scheduler for allocating cloud instances with no regional constraints. We then extend the solution to accommodate regional constraints, and discuss a series of practical enhancements, including popularity forecasting, initialization latency, and viewer feedbacks. Our solutions have been evaluated under diverse networks and cloud system configurations as well as parameter settings. The trace-driven simulation confirms the superiority of our design, while our Planetlab-based experiment offers further practical hints toward real-world migration. In recent years, empowered by rich media generation devices and convenient Internet access, Crowdsourced Live Game Video Streaming (CLGVS) has become one of the most popular Internet services. Twitch.tv, the most well-known CLGVS platform in the world, allows gamers to broadcast their gaming videos over the Internet. With the prevalence of mobile devices, viewers can watch gamers playing video games anywhere, anytime, on any devices (e.g., smartphones, tablets, or personal computers). However, the heterogeneity of user devices makes conventional solutions hard to ensure user-perceived quality. In this paper, we address the problem of cost-effective adaptive live game video streaming from the perspective of CLGVS service providers. Our purpose is to minimize the operational cost for CLGVS service providers by making live transcoding decisions, bit-rate adaptation decisions, and datacenter assignment decisions dynamically. Meanwhile, our algorithm also ensures good-enough service quality for viewers. Due to the diversity of game genres, we also consider game genres when designing our algorithm. To achieve the above purpose, we formulate the problem into a constrained stochastic optimization problem. By leveraging the Lyapunov optimization framework, we derive the online strategy with provable performance bound. To evaluate the effectiveness of our proposed algorithm, we further conduct a series of trace-driven simulations. The experimental results demonstrate the effectiveness of our algorithm in terms of operational cost and service quality. Our proposed algorithm can reduce operational cost by up to 50 while achieving good-enough viewer QoE compared with other alternatives.