Distributed computer architectures labeled “peer-to-peer ” are designed for the sharing of computer resources (content, storage, CPU cycles) by direct exchange, rather than requiring the intermediation or support of a centralized server or authority. Peer-to-peer architectures are characterized by their ability to adapt to failures and

During recent years, peer-to-peer (P2P) file-sharing systems have evolved in many ways to accommodate growing numbers of participating peers. In particular, new features have changed the properties of the unstructured overlay topology formed by these peers. Despite their importance, little is known about the characteristics of these topologies and their dynamics in modern file-sharing applications. This paper presents a detailed characterization of P2P overlay topologies and their dynamics, focusing on the modern Gnutella network. Using our fast and accurate P2P crawler, we capture a complete snapshot of the Gnutella network with more than one million peers in just a few minutes. Leveraging more than 18,000 recent overlay snapshots, we characterize the graph-related properties of individual overlay snapshots and overlay dynamics across hundreds of back-to-back snapshots. We show how inaccuracy in snapshots can lead to erroneous conclusions—such as a power-law degree distribution. Our results reveal that while the Gnutella network has dramatically grown and changed in many ways, it still exhibits the clustering and short path lengths of a small world network. Furthermore, its overlay topology is highly resilient to random peer departure and even systematic attacks. More interestingly, overlay dynamics lead to an “onion-like ” biased connectivity among peers where each peer is more likely connected to peers with higher uptime. Therefore, long-lived peers form a stable core that ensures reachability among peers despite overlay dynamics. 1

Abstract. Overlay topology plays an important role in P2P systems. Topology serves as a basis for achieving functions such as routing, searching and information dissemination, and it has a major impact on their efficiency, cost and robustness. Furthermore, the solution to problems such as sorting and clustering of nodes can also be interpreted as a topology. In this paper we propose a generic protocol, T-Man, for constructing and maintaining a large class of topologies. In the proposed framework, a topology is defined with the help of a ranking function. The nodes participating in the protocol can use this ranking function to order any set of other nodes according to preference for choosing them as a neighbor. This simple abstraction makes it possible to control the self-organization process of topologies in a straightforward, intuitive and flexible manner. At the same time, the T-Man protocol involves only local communication to increase the quality of the current set of neighbors of each node. We show that this bottom-up approach results in fast convergence and high robustness in dynamic environments. The protocol can be applied as a standalone solution as well as a component for recovery or bootstrapping of other protocols. 1

Query processing in traditional information management systems has moved from an exact match model to more flexible paradigms allowing cooperative retrieval by aggregating the database objects' degree of match for each different query predicate and returning the best matching objects only. In peer-to-peer systems such strategies are even more important, given the potentially large number of peers, which may contribute to the results. Yet current peer-to-peer research has barely started to investigate such approaches. In this paper we will discuss the benefits of best match/top-k queries in the context of distributed peer-to-peer information infrastructures and show how to extend the limited query processing in current peer-to-peer networks by allowing the distributed processing of top-k queries, while maintaining a minimum of data traffic. Relying on a super-peer backbone organized in the HyperCuP topology we will show how to use local indexes for optimizing the necessary query routing and how to process intermediate results in inner network nodes at the earliest possible point in time cutting down the necessary data traffic within the network. Our algorithm is based on dynamically collected query statistics only, no continuous index update processes are necessary, allowing it to scale easily to large numbers of peers, as well as dynamic additions/deletions of peers. We will show our approach to always deliver correct result sets and to be optimal in terms of necessary object accesses and data traffic. Finally, we present simulation results for both static and dynamic network environments.

In a Peer-To-Peer (P2P) system, autonomous computers pool their resources (e.g., les, storage, compute cycles) in order to inexpensively handle tasks that would normally require large costly servers. The scale of these systems, their \open nature", and the lack of centralized control pose dicult performance and security challenges. Much research has recently focused on tackling some of these challenges

Both in terms of number of participating users and in traffic volume, KaZaA is one of the most important applications in the Internet today. Nevertheless, because KaZaA is proprietary and uses encryption, little is understood about KaZaA’s overlay structure and dynamics, its messaging protocol, and its index management. We have built two measurement apparatus- the KaZaA Sniffing Platform and the KaZaA Probing Tool- to unravel many of the mysteries behind KaZaA. We deploy the apparatus to study KaZaA’s overlay structure and dynamics, its neighbor selection, its use of dynamic port numbers to circumvent firewalls, and its index management. Although this study does not fully solve the KaZaA puzzle, it nevertheless leads to a coherent description of KaZaA and its overlay. Furthermore, we leverage the measurement results to set forth a number of key principles for the design of a successful unstructured P2P overlay. The measurement results and resulting design principles in this paper should be useful for future architects of P2P overlay networks as well as for engineers managing ISPs. 1 1

A major problem in today's information-driven world is that sharing heterogeneous, semantically rich data is incredibly difficult. Piazza is a peer data management system that enables sharing heterogeneous data in a distributed and scalable way. Piazza assumes the participants to be interested in sharing data, and willing to define pairwise mappings between their schemas. Then, users formulate queries over their preferred schema, and a query answering system expands recursively any mappings relevant to the query, retrieving data from other peers. In this paper, we provide a brief overview of the Piazza project including our work on developing mapping languages and query reformulation algorithms, assisting the users in defining mappings, indexing, and enforcing access control over shared data.

The huge popularity of recent peer-to-peer (P2P) file sharing systems has been mainly driven by the scalability of their architectures and the flexibility of their search facilities. Such systems are usually designed as unstructured P2P networks, because they impose few constraints on topology and data placement and support highly versatile search mechanisms. A major limitation of unstructured P2P networks lies, however, in the inefficiency of their search algorithms, which are usually based on simple flooding schemes.

When joining information provider peers to a peer-to-peer network, an arbitrary distribution is sub-optimal. In fact, clustering peers by their characteristics, enhances search and integration significantly. Currently super-peer networks, such as the Edutella network, provide no sophisticated means for such a "semantic clustering" of peers. We introduce the concept of semantic overlay clusters (SOC) for super-peer networks enabling a controlled distribution of peers to clusters. In contrast to the recently announced semantic overlay network approach designed for flat, pure peer-to-peer topologies and for limited meta data sets, such as simple filenames, we allow a clustering of complex heterogeneous schemes known from relational databases and use advantages of super-peer networks, such as efficient search and broadcast of messages. Our approach is based on predefined policies defined by human experts. Based on such policies a fully decentralized broadcast- and matching approach distributes the peers automatically to super-peers. Thus we are able to automatize the integration of information sources in super-peer networks and reduce flooding of the network with messages.

We describe a simple but effective traffic model that can be used to understand the effects of denial-of-service (DoS) attacks based on query floods in Gnutella networks. We run simulations based on the model to analyze how different choices of network topology and application level load balancing policies can minimize the effect of these types of DoS attacks. In addition, we also study how damage caused by query floods is distributed throughout the network, and how application-level policies can localize the damage.