We describe an efficient peer-to-peer information retrieval system, pSearch, that supports state-of-the-art content- and semantic-based full-text searches. pSearch avoids the scalability problem of existing systems that employ centralized indexing, or index/query flooding. It also avoids the nondeterminism that is exhibited by heuristic-based approaches. In pSearch, documents in the network are organized around their vector representations (based on modern document ranking algorithms) such that the search space for a given query is organized around related documents, achieving both eciency and accuracy.

Recent peer-to-peer (P2P) networks, represented by CAN, Chord, and Pastry, offer an administration-free and faulttolerant application-level overlay network. For these systems to function efficiently, they must make effective use of the underlying network topology. Existing

Distributed hash table (DHT)-based overlay networks, represented by Pastry, CAN, and Chord, offer an administration-free and fault-tolerant application-level overlay network. While elegant from a theoretical perspective, these systems have some disadvantages. First, they rely on applicationlevel routing, which may be inefficient with respect to network delays and bandwidth consumption. Second, they typically construct a homogeneously structured overlay even though nodes in these networks usually have varying physical connectivity and packet-forwarding capacities. In this

It was noted in recent years that the Internet structure resembles a star with a highly connected core and long stretched tendrils. In this work we present a new quantity, the Internet geometric curvature, that captures the above observation by a single number. We embed the Internet distance metric in a hyperbolic space with an optimal curvature and achieve an accuracy better than achieved before for the Euclidean space. This proves our hypothesis regarding the internet curvature. We demonstrate the strength of our embedding with two applications: selecting the closest server and building an application level multicast tree.

In this paper, we first describe the concept of data overlay, which is a mechanism to implement arbitrary data structure on top of any structured P2P DHT. With this abstraction, we developed a highly scalable, efficient and robust infrastructure, called SOMO, to perform resource management for P2P DHT. It does so by gathering and disseminating system metadata in O(logN) time with a selforganizing and self-healing data overlay. Our preliminary results of using SOMO to balance routing traffic with node capacities in a prefix-based overlay have demonstrated the utility of data overlay as well as the potential of SOMO.

We advocate the need for integrating semantic information into a file system. We demonstrate the benefits of this in Sedar, a deep archival file system. Sedar is the first archival file system that integrates semantic storage and retrieval capabilities. In addition, Sedar introduces several novel features: the notion of semantic-hashing to reduce the storage consumption that is robust against misalignment of documents; virtual snapshots of the namespace, and conceptual deletions of files and directories. Sedar exposes a semantic catalogue that allows other semanticbased tools (e.g., visualization and statistical analysis) to be built. It uses a decentralized P2P storage utility enabling horizontal scalability.

Peer-to-peer overlay networks offer a convenient way to host an infrastructure that can scale to the size of the Internet and yet stay manageable. These overlays are essentially self-organizing distributed hash tables (DHT. the dynamic nature of the system, however, poses serious challenges of data reliability. Furthermore, in order to see wider adoption, it is time to design support for generic replication mechanisms capable of handling arbitrary update requests -- most of the existing proposals are deep archival systems in nature.

Due to the overwhelming amount of information on the Internet, it is becoming increasingly difficult for people to find relevant information in a timely fashion. Information filtering and dissemination systems allow user to register persistent queries called user profiles. They detect new contents, match them against the profiles, and continuously notify users when relevant information becomes available. Existing systems, however, either are not scalable

Abstract—Estimating distances in the Internet has been studied in the recent years due to its ability to improve the performance of many applications, e.g., in the peer-to-peer realm. One scalable approach to estimate distances between nodes is to embed the nodes in some dimensional geometric space and to use the pair distances in this space as the estimate for the real distances. Several algorithms were suggested in the past to do this in low dimensional Euclidean spaces. It was noted in recent years that the Internet structure has a highly connected core and long stretched tendrils, and that most of the routing paths between nodes in the tendrils pass through the core. Therefore, we suggest in this work, to embed the Internet distance metric in a hyperbolic space where routes are bent toward the center. We found that if the curvature, that defines the extend of the bending, is selected in the adequate range, the accuracy of Internet distance embedding can be improved. We demonstrate the strength of our hyperbolic embedding with two applications: selecting the closest server and building an application level multicast tree. For the latter, we present a distributed algorithm for building geometric multicast trees that achieve good trade-offs between delay (stretch) and load (stress). We also present a new efficient centralized embedding algorithm that enables the accurate embedding of short distances, something that have never been done before. I.

This paper presents a novel peer-to-peer system that is particularly well suited to support context-aware computing. The system, called GeoPeer, combines the advantages of general purpose peer-to-peer systems with the suitability of geographical routing for supporting location-constrained queries and information dissemination. To achieve this goal, GeoPeer incorporates sophisticated mechanisms to establish long-range contacts that permit to achieve a small network diameter. These mechanisms take explicitly into account the unbalanced distribution of nodes in the geographical space.