An emerging Internet application, IPTV, has the potential to flood Internet access and backbone ISPs with massive amounts of new traffic. Although many architectures are possible for IPTV video distribution, several mesh-pull P2P architectures have been successfully deployed on the Internet. In order to gain insights into mesh-pull P2P IPTV systems and the traffic loads they place on ISPs, we have undertaken an in-depth measurement study of one of the most popular IPTV systems, namely, PPLive. We have developed a dedicated PPLive crawler, which enables us to study the global characteristics of the mesh-pull PPLive system. We have also collected extensive packet traces for various different measurement scenarios, including both campus access networks and residential access networks. The measurement results obtained through these platforms bring important insights into P2P IPTV systems. Specifically, our results show the following. 1) P2P IPTV users have the similar viewing behaviors as regular TV users. 2) During its session, a peer exchanges video data dynamically with a large number of peers. 3) A small set of super peers act as video proxy and contribute significantly to video data uploading. 4) Users in the measured P2P IPTV system still suffer from long start-up delays and playback lags, ranging from several seconds to a couple of minutes. Insights obtained in this study will be valuable for the development and deployment of future P2P IPTV systems.

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A Measurement Study of a Large-Scale P2P IPTV System

A super-peer is a node in a peer-to-peer network that operates both as a server to a set of clients, and as an equal in a network of super-peers. Super-peer networks strike a balance between the efficiency of centralized search, and the autonomy, load balancing and robustness to attacks provided by distributed search. Furthermore, they take advantage of the heterogeneity of capabilities (e.g., bandwidth, processing power) across peers, which recent studies have shown to be enormous. Hence, new and old P2P systems like KaZaA and Gnutella are adopting super-peers in their design. Despite their growing popularity, the behavior of super-peer networks is not well understood. For example, what are the potential drawbacks of super-peer networks? How can super-peers be made more reliable? How many clients should a super-peer take on to maximize efficiency? we examine super-peer networks in detail, gaming an understanding of their fundamental characteristics and performance tradeoffs. We also present practical guidelines and a general procedure for the design of an efficient super-peer network.

Designing an Super-Peer Network

The dynamics of peer participation, or churn, are an inherent property of Peer-to-Peer (P2P) systems and critical for design and evaluation. Accurately characterizing churn requires precise and unbiased information about the arrival and departure of peers, which is challenging to acquire. Prior studies show that peer participation is highly dynamic but with conflicting characteristics. Therefore, churn remains poorly understood, despite its significance.In this paper, we identify several common pitfalls that lead to measurement error. We carefully address these difficulties and present a detailed study using three widely-deployed P2P systems: an unstructured file-sharing system (Gnutella), a content-distribution system (BitTorrent), and a Distributed Hash Table (Kad). Our analysis reveals several properties of churn: (i) overall dynamics are surprisingly similar across different systems, (ii) session lengths are not exponential, (iii) a large portion of active peers are highly stable while the remaining peers turn over quickly, and (iv) peer session lengths across consecutive appearances are correlated. In summary, this paper advances our understanding of churn by improving accuracy, comparing different P2P file sharingdistribution systems, and exploring new aspects of churn.

/pdf/understanding-churn-in-peer-to-peer-networks-3wbu3nj8po.pdf

Understanding churn in peer-to-peer networks

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

Within a decade, P2P has proven to be a technology that enables innovative new services and is used by millions of people every day.

Peer-to-peer systems

With over 100,000 simultaneous users (typically), PPLive is the most popular IPTV application today. PPLive uses a peer-to-peer design, in which peers download and redistribute live television content from and to other peers. Although PPLive is paving the way for an important new class of bandwidth intensive applica- tions, little is known about it due to the proprietary nature of its protocol. In this paper we undertake a preliminary measurement study of PPLive, reporting results from passive packet sniffing of residential and campus peers. We report results for streaming per- formance, workload characteristics, and overlay properties.

/pdf/insights-into-pplive-a-measurement-study-of-a-large-scale-3jyu351fe9.pdf

Insights into PPLive: A Measurement Study of a Large-Scale P2P IPTV System

P2P file-sharing systems have indexes, which users search to find locations of desired titles. In the index poisoning attack, the attacker inserts massive numbers of bogus records into the index for a set of targeted titles. As a result, when a user searches for a targeted title, the index returns bogus results, such as bogus file identifiers, bogus IP addresses, or bogus port numbers. In this paper we first show that both structured and unstructured P2P file-sharing systems are highly vulnerable to the index poisoning attack. We then develop a novel and efficient methodology for estimating index poisoning levels and pollution levels in file-sharing systems. The methodology is efficient in that involves neither the downloading nor the analysis of binary content files. We deploy data-harvesting platforms for FastTrack, an unstructured file-sharing system, and Overnet, a DHT-based file-sharing system. Applying our methodology to harvested data, we find that index poisoning is pervasive in both systems. We also outline a distributed blacklisting procedure for countering the index poisoning and pollution attacks.

/pdf/the-index-poisoning-attack-in-p2p-file-sharing-systems-5a8kxwc5tx.pdf

The Index Poisoning Attack in P2P File Sharing Systems

http://www.land.ufrj.br/~classes/coppe-redes-2008/biblio/fasttrack-measurement.pdf

The FastTrack overlay: A measurement study

P2P file-sharing systems are susceptible to pollution attacks, whereby corrupted copies of content are aggressively introduced into the system. Recent research indicates that pollution is extensive in several file sharing systems. In this paper we propose an efficient measurement methodology for identifying the sources of pollution and estimating the levels of polluted content. The methodology can be used to efficiently blacklist polluters, evaluate the success of a pollution campaign, to reduce wasted bandwidth due to the transmission of polluted content, and to remove the noise from content measurement data. The proposed methodology is efficient in that it does not involve the downloading and analysis of binary content, which would be expensive in bandwidth and in computation/human resources. The methodology is based on harvesting metadata from the file sharing system and then processing off-line the harvested meta-data. We apply the technique to the FastTrack/Kazaa file-sharing network. Analyzing the false positives and false negatives, we conclude that the methodology is efficient and accurate.

/pdf/efficient-blacklisting-and-pollution-level-estimation-in-p2p-2cruo9u9ev.pdf

Jian Liang

Papers

A Measurement Study of a Large-Scale P2P IPTV System

Insights into PPLive: A Measurement Study of a Large-Scale P2P IPTV System

The Index Poisoning Attack in P2P File Sharing Systems

The FastTrack overlay: A measurement study

Efficient blacklisting and pollution-level estimation in p2p file-sharing systems