Peer-to-peer (P2P) file sharing accounts for an astonishing volume of current Internet tra#c. This paper probes deeply into modern P2P file sharing systems and the forces that drive them. By doing so, we seek to increase our understanding of P2P file sharing workloads and their implications for future multimedia workloads. Our research uses a three-tiered approach. First, we analyze a 200-day trace of over 20 terabytes of Kazaa P2P tra#c collected at the University of Washington. Second, we develop a model of multimedia workloads that lets us isolate, vary, and explore the impact of key system parameters. Our model, which we parameterize with statistics from our trace, lets us confirm various hypotheses about file-sharing behavior observed in the trace. Third, we explore the potential impact of localityawareness in Kazaa.

This paper examines graph-theoretic properties of existing peer-to-peer architectures and proposes a new infrastructure based on optimal-diameter de Bruijn graphs. Since generalized de Bruijn graphs possess very short average routing distances and high resilience to node failure, they are well suited for structured peer-to-peer networks. Using the example of Chord, CAN, and de Bruijn, we first study routing performance, graph expansion, and clustering properties of each graph. We then examine bisection width, path overlap, and several other properties that affect routing and resilience of peer-to-peer networks. Having confirmed that de Bruijn graphs offer the best diameter and highest connectivity among the existing peer-to-peer structures, we offer a very simple incremental building process that preserves optimal properties of de Bruijn graphs under uniform user joins/departures. We call the combined peer-to-peer architecture

Balancing peer-to-peer graphs, including zone-size distributions, has recently become an important topic of peer-topeer (P2P) research [1], [2], [6], [19], [31], [36]. To bring analytical understanding into the various peer-join mechanisms, we study how zone-balancing decisions made during the initial sampling of the peer space a#ect the resulting zone sizes and derive several asymptotic results for the maximum and minimum zone sizes that hold with high probability.

Balancing of structured peer-to-peer graphs, including their zone sizes, has recently become an important topic of distributed hash table (DHT) research. To bring analytical understanding into the various peer-join mechanisms based on consistent hashing, we study how zone-balancing decisions made during the initial sampling of the peer space affect the resulting zone sizes and derive several asymptotic bounds for the maximum and minimum zone sizes that hold with high probability. Several of our results contradict those of prior work and shed new light on the theoretical performance limitations of consistent hashing. We use simulations to verify our models and compare the performance of the various methods using the example of recently proposed de

Abstract. In Peer to Peer (P2P) systems, peers can join and leave the network whenever they want. Such “freedom ” causes unpredictable network environment which leads to the most complex design challenge of a p2p protocol: how to make p2p service available under churn? What is more, where is the extreme of a system’s resistibility to high churn? A careful evaluation of some typical peer-to-peer networks will contribute a lot to choosing, using and designing a certain kind of protocol in special applications. In this paper we analyze the performance of Chord [1], Tapestry [2], Kelips [3], Kademlia [4] and Koorde [5], then find out the crash point [6] of each network based on the simulation experiment. Finally, we propose a novel way to help nodes survive under high churn.

Abstract. A fundamental problem that confronts structured peer-topeer system that use DHT technologies to map data onto nodes is the performance of the network under the circumstance that a large percentage of nodes join and fail frequently and simultaneously. A careful examination of some typical peer-to-peer networks will contribute a lot to choosing and using certain kind of topology in special applications. This paper analyzes the performance of Chord [7] and Koorde [2], and find out the crash point of each network through the simulation experiment. 1

Numerous proposals exist for load balancing in peer-to-peer (p2p) networks. Some focus on namespace balancing, making the distance between nodes as uniform as possible. This technique works well under ideal conditions, but not under those found empirically. Instead, researchers have found heavy-tailed query distributions (skew), high rates of node join and leave (churn), and wide variation in node network and storage capacity (heterogeneity) . Other approaches tackle these less-than-ideal conditions, but give up on important security properties. We propose an algorithm that both facilitates good performance and does not dilute security. Our algorithm, kChoices, achieves load balance by greedily matching nodes' target workloads with actual applied workloads through limited sampling, and limits any fundamental decrease in security by basing each nodes' set of potential identifiers on a single certificate. Our algorithm compares favorably to four others in trace-driven simulations. We have implemented our algorithm and found that it improved aggregate throughput by 20% in a widely heterogeneous system in our experiments.

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Characterizing user churn has become an important topic in studying P2P networks, both in theoretical analysis and system design. Recent work [26] has shown that direct sampling of user lifetimes may lead to certain bias (arising from missed peers and round-off inconsistencies) and proposed a technique that estimates lifetimes based on sampled residuals. In this paper, however, we show that under non-stationary arrivals, which are often present in real systems, residual-based sampling does not correctly reconstruct user lifetimes and suffers a varying degree of bias, which in some cases makes estimation completely impossible. We overcome this problem using two contributions: a novel non-stationary ON/OFF churn model and an unbiased randomized residual sampling technique for measuring user lifetimes. The former allows correlation between ON/OFF periods of the same user and exhibits different join rates during the day. The latter spreads sampling points uniformly during the day and uses a novel estimator to reconstruct the underlying lifetime distribution. We finish the paper with experimental measurements of Gnutella and discussing reduction in overhead compared to direct sampling methods.