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 widelydeployed 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 sharing/distribution systems, and exploring new aspects of churn.

Abstract-End-to-end congestion control mechanisms have been critical to the robustness and stability of the Internet. Most of today's Internet traffic is TCP, and we expect this to remain so in the future. Thus, having "TCP-friendly" behavior is crucial for new applications. However, the emergence of non-congestion-controlled realtime applications threatens unfairness to competing TCP traffic and possible congestion collapse.We present an end-to-end TCP-friendly Rate Adaptation Protocol (RAP), which employs an additive-increase, multiplicativedecrease (AIMD) algorithm. It is well suited for unicast playback of realtime streams and other semi-reliable rate-based applications. Its primary goal is to be fair and TCP-friendly while separating network congestion control from application-level reliability.We evaluate RAP through extensive simulation, and conclude that bandwidth is usually evenly shared between TCP and RAP traffic. Unfairness to TCP traffic is directly determined by how TCP diverges from the AIMD algorithm. Basic RAP behaves in a TCPfriendly fashion in a wide range of likely conditions, but we also devised a fine-grain rate adaptation mechanism to extend this range further. Finally, we show that deploying RED queue management can result in an ideal fairness between TCP and RAP traffic.

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Abstract-Existing approaches to P2P streaming can be divided into two general classes: (i) tree-based approaches use pushbased content delivery over multiple tree-shaped overlays, and (ii) mesh-based approaches use swarming content delivery over a randomly connected mesh. Previous studies have often focused on a particular P2P streaming mechanism and no comparison between these two classes has been conducted. In this paper, we compare and contrast the performance of representative protocols from each class using simulations. We identify the similarities and differences between these two approaches. Furthermore, we separately examine the behavior of content delivery and overlay construction mechanisms for both approaches in static and dynamic scenarios. Our results indicate that the meshbased approach consistently exhibits a superior performance over the tree-based approach. We also show that the main factors attributing in the inferior performance of the tree-based approach are (i) the static mapping of content to a particular tree, and (ii) the placement of each peer as an internal node in one tree and as a leaf in all other trees. I. INTRODUCTIONUsing Peer-to-Peer overlay has become an increasingly popular approach for streaming live media over the Internet due to its potential scalability and ease of deployment. This approach is generally referred to as P2P streaming. In P2P streaming, participating end-systems (or peers) actively contribute their resources (mainly outgoing bandwidth) by forwarding their available content to their connected peers. Since the aggregate available resources in this approach organically grow with the user population, this approach can potentially scale with the number of participating peers in a session.Existing approaches for live P2P streaming can be generally divided into two classes: tree-based approaches and meshbased approaches. The tree-based P2P streaming approach expands on the idea of end-system multicast [1] by organizing participating peers into multiple diverse trees. Then, each description of a Multiple Description Coded (MDC) content is pushed through a separate tree [2], [3]. The mesh-based P2P streaming approach is inspired by file swarming mechanisms (such as BitTorrent) where participating peers form a randomly connected mesh and employ a swarming content delivery mechanism over a recent window of content [4]. However, the limited availability of new content in live streaming coupled with the notion of "quality" for the delivered stream (i.e., number of descriptions) introduce new dimensions in the design and evaluations of mesh-based P2P streaming. Most of the previous studies on P2P streaming have focused on a particular mechanism and evaluated certain aspects of its

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