User Generated Content (UGC) is re-shaping the way people watch video and TV, with millions of video producers and consumers. In particular, UGC sites are creating new viewing patterns and social interactions, empowering users to be more creative, and developing new business opportunities. To better understand the impact of UGC systems, we have analyzed YouTube, the world's largest UGC VoD system. Based on a large amount of data collected, we provide an in-depth study of YouTube and other similar UGC systems. In particular, we study the popularity life-cycle of videos, the intrinsic statistical properties of requests and their relationship with video age, and the level of content aliasing or of illegal content in the system. We also provide insights on the potential for more efficient UGC VoD systems (e.g. utilizing P2P techniques or making better use of caching). Finally, we discuss the opportunities to leverage the latent demand for niche videos that are not reached today due to information filtering effects or other system scarcity distortions. Overall, we believe that the results presented in this paper are crucial in understanding UGC systems and can provide valuable information to ISPs, site administrators, and content owners with major commercial and technical implications.

/pdf/i-tube-you-tube-everybody-tubes-analyzing-the-world-s-xhp615maf2.pdf

I tube, you tube, everybody tubes: analyzing the world's largest user generated content video system

This paper presents a traffic characterization study of the popular video sharing service, YouTube. Over a three month period we observed almost 25 million transactions between users on an edge network and YouTube, including more than 600,000 video downloads. We also monitored the globally popular videos over this period of time.In the paper we examine usage patterns, file properties, popularity and referencing characteristics, and transfer behaviors of YouTube, and compare them to traditional Web and media streaming workload characteristics. We conclude the paper with a discussion of the implications of the observed characteristics. For example, we find that as with the traditional Web, caching could improve the end user experience, reduce network bandwidth consumption, and reduce the load on YouTube's core server infrastructure. Unlike traditional Web caching, Web 2.0 provides additional meta-data that should be exploited to improve the effectiveness of strategies like caching.

/pdf/youtube-traffic-characterization-a-view-from-the-edge-53v2b6giu5.pdf

Youtube traffic characterization: a view from the edge

Video-on-demand over IP (VOD) is one of the best-known examples of "next-generation" Internet applications cited as a goal by networking and multimedia researchers. Without empirical data, researchers have generally relied on simulated models to drive their design and developmental efforts. In this paper, we present one of the first measurement studies of a large VOD system, using data covering 219 days and more than 150,000 users in a VOD system deployed by China Telecom. Our study focuses on user behavior, content access patterns, and their implications on the design of multimedia streaming systems. Our results also show that when used to model the user-arrival rate, the traditional Poisson model is conservative and overestimates the probability of large arrival groups. We introduce a modified Poisson distribution that more accurately models our observations. We also observe a surprising result, that video session lengths has a weak inverse correlation with the video's popularity. Finally, we gain better understanding of the sources of video popularity through analysis of a number of internal and external factors.

/pdf/understanding-user-behavior-in-large-scale-video-on-demand-2ercv8cu0q.pdf

Understanding user behavior in large-scale video-on-demand systems

As the distribution of the video over the Internet becomes main- stream and its consumption moves from the computer to the TV screen, user expectation for high quality is constantly increasing. In this context, it is crucial for content providers to understand if and how video quality affects user engagement and how to best invest their resources to optimize video quality. This paper is a first step towards addressing these questions. We use a unique dataset that spans different content types, including short video on demand (VoD), long VoD, and live content from popular video con- tent providers. Using client-side instrumentation, we measure quality metrics such as the join time, buffering ratio, average bitrate, rendering quality, and rate of buffering events.We quantify user engagement both at a per-video (or view) level and a per-user (or viewer) level. In particular, we find that the percentage of time spent in buffering (buffering ratio) has the largest impact on the user engagement across all types of content. However, the magnitude of this impact depends on the content type, with live content being the most impacted. For example, a 1% increase in buffering ratio can reduce user engagement by more than three minutes for a 90-minute live video event. We also see that the average bitrate plays a significantly more important role in the case of live content than VoD content.

/pdf/understanding-the-impact-of-video-quality-on-user-engagement-dbkb3mbmmp.pdf

Understanding the impact of video quality on user engagement

User generated content (UGC), now with millions of video producers and consumers, is re-shaping the way people watch video and TV. In particular, UGC sites are creating new viewing patterns and social interactions, empowering users to be more creative, and generating new business opportunities. Compared to traditional video-on-demand (VoD) systems, UGC services allow users to request videos from a potentially unlimited selection in an asynchronous fashion. To better understand the impact of UGC services, we have analyzed the world's largest UGC VoD system, YouTube, and a popular similar system in Korea, Daum Videos. In this paper, we first empirically show how UGC services are fundamentally different from traditional VoD services. We then analyze the intrinsic statistical properties of UGC popularity distributions and discuss opportunities to leverage the latent demand for niche videos (or the so-called "the Long Tail" potential), which is not reached today due to information filtering or other system scarcity distortions. Based on traces collected across multiple days, we study the popularity lifetime of UGC videos and the relationship between requests and video age. Finally, we measure the level of content aliasing and illegal content in the system and show the problems aliasing creates in ranking the video popularity accurately. The results presented in this paper are crucial to understanding UGC VoD systems and may have major commercial and technical implications for site administrators and content owners.

/pdf/analyzing-the-video-popularity-characteristics-of-large-5c2t5dkq42.pdf

Analyzing the video popularity characteristics of large-scale user generated content systems

This paper provides an extensive analysis of pre-stored streaming media workloads, focusing on the client interactive behavior. We analyze four workloads that fall into three different domains, namely, education, entertainment video and entertainment audio. Our main goals are: (a) to identify qualitative similarities and differences in the typical client behavior for the three workload classes and (b) to provide data for generating realistic synthetic workloads.

/pdf/analyzing-client-interactivity-in-streaming-media-12n26qkqn4.pdf

Analyzing client interactivity in streaming media

Recently, a number of scalable stream sharing protocols have been proposed with the promise of great reductions in the server and network bandwidth required for delivering popular media content. Although the scalability of these protocols has been evaluated mostly for sequential user accesses, a high degree of interactivity has been observed in the accesses to several real media servers. Moreover, some studies have indicated that user interactivity can severely penalize the scalability of stream sharing protocols.This paper investigates alternative mechanisms for scalable streaming to interactive users. We first identify a set of workload aspects that are determinant to the scalability of classes of streaming protocols. Using real workloads and a new interactive media workload generator, we build a rich set of realistic synthetic workloads. We evaluate Bandwidth Skimming and Patching, two state-of-the-art streaming protocols, covering, with our workloads, a larger region of the design space than previous work. Finally, we propose and evaluate five optimizations to Bandwidth Skimming, the most scalable of the two protocols. Our best optimization reduces the average server bandwidth required for interactive workloads in up to 54%, for unlimited client buffers, and 29%, if buffers are constrained to 25% of media size.

https://homepages.dcc.ufmg.br/~cunha/papers/rocha05mm-interactive.pdf

Scalable media streaming to interactive users

Peer-to-Peer live streaming systems help content providers and distributors drastically reduce bandwidth costs by sharing costs among peers. Researchers have dedicated significant effort developing techniques to discourage or exclude uncooperative peers from peer-to-peer systems. However, users are often unable to cooperate, e.g., users using a mobile device with limited, costly bandwidth. We study the impact of uncooperative peers on video discontinuity and latency using PlanetLab. We find that simple mechanisms, like forwarding video data requests to cooperative peers instead of wasting effort sending requests to uncooperative peers, allows peer-to-peer live streaming to serve 50% of uncooperative peers without performance degradation. We argue that denying service to uncooperative peers may not be the best long-term approach; our findings suggest that peer-to-peer live streaming can support uncooperative peers.

https://homepages.dcc.ufmg.br/~cunha/papers/oliveira13p2p-freerider.pdf

Can Peer-to-Peer live streaming systems coexist with free riders?

In order to minimize bandwidth requirements and improve on demand streaming media distribution scalability, several distribution protocols based on stream sharing by multiple users have been proposed. Despite the great scalability of these protocols proven for workloads where users access the entire media with no interruptions, several studies show that protocol scalability is severely degraded under interactive scenarios, where users access media segments. These scenarios are commonly observed in real streaming media server workloads. In reply to these results, a number of extensions to the original protocols, optimized for interactive access, have been proposed and evaluated, indicating significant server bandwidth savings even under highly interactive scenarios. However, one of the most promissing class of optimizations may send extra streams through the network during inactive client periods. Therefore, network bandwidth requirements for these optimizations become a critical issue that has not been evaluated yet. This work presents an evaluation of the network bandwidth requirements for the interactive access optimized protocols, considering realistic workloads of different interactivity levels and canonical and real network topologies. Results indicate that the optimizations also lead to a significant reduction in the average network bandwidth requirements (peak of 60%).Visando minimizar os requisitos de banda e aumentar a escalabilidade da distribuicao sob demanda de midia continua, v´rios protocolos de distribuicao baseados em compartilhamento de fluxos por multiplos usu´rios foram propostos. Embora esteja comprovada a grande escalabilidade desses protocolos para cargas onde os usu´rios acessam toda a midia sem interrupcoes, v´rios estudos mostraram que a mesma e severamente degradada em cen´rios interativos, onde os usu´rios acessam segmentos da midia. Cen´rios comumente observados em cargas de acesso a servidores reais de midia continua. Em resposta a esse resultado, v´rias extensoes dos protocolos originais, otimizadas para acesso interativo, foram propostas e avaliadas, indicando uma grande economia de banda de servidor mesmo em cen´rios com alta interatividade. Entretanto, uma das classes de otimizacoes mais promissoras pode enviar fluxos extras pela rede durante periodos inativos do cliente. Assim, os requisitos de banda de rede dessas otimizacoes se torna um ponto critico que ainda nao foi avaliado. Este artigo avalia o consumo de banda de rede pelos protocolos otimizados para acessos interativos, considerando cargas de trabalho realistas com diferentes niveis de interatividade e topologias de redes canonicas e reais. Os resultados indicam que as otimizacoes tambem levam a uma significativa reducao no consumo medio de banda de rede (pico de ate 60%).

Network bandwidth requirements for optimized streaming media transmission to interactive users

Despite the growing popularity of live P2P continuous media transmission applications, still limited the current understanding of important aspects of the behavior of the participants, like the arrival time between them and time spent on the network. This work aims to fill this gap by presenting a characterization of the behavior of participants in SopCast, one of the most popular live transmission applications on P2P. The analysis includes properties for the session, such as gaps between the arrival of new participants, staying time, number of sessions and inactivity time between sessions. We also present properties of partnerships among participants, such as number of partners. In addition, the study deals with different SopCast channels, highlighting differences in patterns of behavior depending on content. The characterizations present a model set of participants, which can be used as a basis for creating new protocols and generation of realistic synthetic loads for live broadcast on P2P.

Marcus Rocha

Papers

Analyzing client interactivity in streaming media

Scalable media streaming to interactive users

Can Peer-to-Peer live streaming systems coexist with free riders?

Network bandwidth requirements for optimized streaming media transmission to interactive users

A behaviour model of the SopCast users