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.

Peer-to-peer (P2P) applications have seen an enormous success, and recently introduced P2P services have reached tens of millions of users. A feature that significantly contributes to the success of many P2P applications is user anonymity. However, anonymity opens the door to possible misuses and abuses, exploiting the P2P network as a way to spread tampered with resources, including Trojan Horses, viruses, and spam. To address this problem we propose a self-regulating system where the P2P network is used to implement a robust reputation mechanism. Reputation sharing is realized through a distributed polling algorithm by which resource requestors can assess the reliability of a resource offered by a participant before initiating the download. This way, spreading of malicious contents will be reduced and eventually blocked. Our approach can be straightforwardly piggybacked on existing P2P protocols and requires modest modifications to current implementations.

Although peer-to-peer networking applications continue to increase in popularity, there have been few measurement studies of their performance. We present the rst study of the locality of les stored and transferred among peers in Napster and Gnutella over month-long periods. Our analysis indicates that the locality of les is skewed in all four cases and ts well to a logquadratic distribution. This predicts that caches of the most popular songs would increase performance of the system. We also took baseline measurements of le types and sizes for comparison over time with future studies. Not surprisingly, audio les are most popular, however a signi cant fraction of stored data is occupied by videos. Finally, we measured the distribution of time peers in Gnutella were available for downloading. We found that node availability is strongly inuenced by time-of-day eects, and that most user's tend to be available for only very short contiguous lengths of time.

Peer-to-peer information sharing environments are increasingly gaining acceptance on the Internet as they provide an infrastructure in which the desired information can be located and downloaded while preserving the anonymity of both requestors and providers. As recent experience with P2P environments such as Gnutella shows, anonymity opens the door to possible misuses and abuses by resource providers exploiting the network as a way to spread tampered with resources, including malicious programs, such as Trojan Horses and viruses.

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Opportunistic sharing of Internet-connected resources is a low cost method for obtaining access to unprecedented-scale collections of resources. An essential service in any resource-sharing environment is resource discovery: given a description of the resources desired, a resource discovery mechanism returns locations of resources that match the description.

A peer-to-peer(P2P) system consists of a decentralized, distributed network of nodes that is capable of sharing resources and services without centralized supervision. A major functionality in P2P networks is locating resources or services present on remote nodes. Traditional techniques for resource discovery include blind searches among the nodes using query ooding, or, positioning resources strategically to enable rapid lookup using distributed hash tables. In this paper, we propose a mobile agent based referral service that directs resources queries intelligently towards the nodes possessing the resource. The mobile agents adaptively learn paths called trails within the P2P network to enable rapid location of resources. Preliminary results of our algorithm demonstrate that the agent based technique performs favorably with existing P2P resource discovery protocols.

Internet applications such as the HTTP-Web, audio-video streaming and file sharing depend on wide-area data dissemination. Clients of these applications suffer from long delays due to network queuing, bandwidth limitations and adverse effects of bandwidth sharing between different traffic.

Distributed Hash Tables are the core technology on a significant share of system designs for Peer-to-Peer information sharing. Typically, a location mechanism is provided and object identifiers act as keys in the index of object locations. When introducing a search mechanism, where single words are used as keys, the key image cardinality will be driven by the word popularity and most of the present designs will be unable to load balance the index among the nodes. We present two contributions: A design that allows participating nodes to load balance the indexing of popular keys and avoid content hot-spots on single nodes; A distributed mechanism for probabilistic filtering of popular keys (with low search relevance) that paves the way for scalable full content indexing.