Centralized Resource Description Framework (RDF) repositories have limitations both in their failure tolerance and in their scalability. Existing Peer-to-Peer (P2P) RDF repositories either cannot guarantee to find query results, even if these results exist in the network, or require up-front definition of RDF schemas and designation of super peers. We present a scalable distributed RDF repository ("RDFPeers") that stores each triple at three places in a multi-attribute addressable network by applying globally known hash functions to its subject, predicate, and object. Thus, all nodes know which node is responsible for storing triple values they are looking for, and both exact-match and range queries can be efficiently routed to those nodes. RDFPeers has no single point of failure nor elevated peers, and does not require the prior definition of RDF schemas. Queries are guaranteed to find matched triples in the network if the triples exist. In RDFPeers, both the number of neighbors per node and the number of routing hops for inserting RDF triples and for resolving most queries are logarithmic to the number of nodes in the network. We further performed experiments that show that the triple-storing load in RDFPeers differs by less than an order of magnitude between the most and the least loaded nodes for real-world RDF data.

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.

This paper describes a novel approach for obtaining semantic interoperability among data sources in a bottom-up, semi-automatic manner without relying on pre-existing, global semantic models. We assume that large amounts of data exist that have been organized and annotated according to local schemas. Seeing semantics as a form of agreement, our approach enables the participating data sources to incrementally develop global agreement in an evolutionary and completely decentralized process that solely relies on pair-wise, local interactions: Participants provide translations between schemas they are interested in and can learn about other translations by routing queries (gossiping). In previous work we relied on the realistic assumption that such translations would be provided manually only. In contrast to that, we assume in this paper that only some translations exist and generate random translations for reaching overall sematic agreement automatically. To support the participants in assessing the semantic quality of the achieved agreements we develop a formal framework that takes into account both syntactic and semantic criteria. The assessment process is incremental and the quality ratings are adjusted along with the operation of the system. Ultimately, this process results in global agreement, i.e., the semantics that all participants understand.

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.

Researchers have recently begun to develop and investigate policy languages to describe trust and security requirements on the Semantic Web. Such policies will be one component of a run-time system that can negotiate to establish trust on the Semantic Web. In this paper, we show how to express different kinds of access control policies and control their use at run time using PeerTrust, a new approach to trust establishment. We show how to use distributed logic programs as the basis for PeerTrust’s simple yet expressive policy and trust negotiation language, built upon the rule layer of the Semantic Web layer cake. We describe the PeerTrust language based upon distributed logic programs, and compare it to other approaches to implementing policies and trust negotiation. Through examples, we show how PeerTrust can be used to support delegation, policy protection and negotiation strategies in the ELENA distributed eLearning environment. Finally, we discuss related work and identify areas for further research.

A semantic link peer-to-peer (P2P) network specifies and manages semantic relationships between peers ’ data schemas and can be used as the semantic layer of a scalable Knowledge Grid. The proposed approach consists of an automatic semantic link discovery method, a tool for building and maintaining P2P semantic link networks (P2PSLNs), a semantic-based peer similarity measurement for efficient query routing, and the schema mapping algorithms for query reformulation and heterogeneous data integration. The proposed approach has three important aspects. First, it uses semantic links to enrich the relationships between peers ’ data schemas. Second, it considers not only nodes but also the XML structure in measuring the similarity between schemas to efficiently and accurately forward queries to relevant peers. Third, it copes with semantic and structural heterogeneity and data inconsistency so that peers can exchange and translate heterogeneous information within a uniform view.

The Semantic Web is based on XML and RDF as its fundamental standards for exchanging and storing information on the World Wide Web. Event-condition-action (ECA) rules are a natural candidate for supporting reactive functionality on XML or RDF repositories. In this paper we describe a language for ECA rules on XML and a prototype implementation of this language. We also discuss some preliminary ideas regarding a language for ECA rules operating on a graph/triple representation of RDF, and we describe the architecture of a distributed deployment of such RDF ECA rules.

Peer-to-Peer systems are a new paradigm for information sharing and some systems have successfully been deployed. It has been argued that current Peer-to-Peer systems suffer from the lack of semantics. The SWAP project (Semantic Web and Peer-to-Peer) 1 aims at overcoming this problem by combining the Peer-to-Peer paradigm with Semantic Web technologies. In this paper, we propose a data model for encoding semantic information that combines features of ontologies (concept hierarchies, relational structures) with a flexible description and rating model that allows us to handle heterogeneous and even contradictory views on the domain of interest. We discuss the role of this model in the SWAP environment and describe the model as well as its application.

Peer-to-peer (P2P) networks have become an important infrastructure during the last years. Using P2P networks for distributed information systems allows us to shift the focus from centrally organized to distributed information systems where all peers can provide and have access to information. In previous

Databases have employed a schema-based approach to store and retrieve structured data for decades. For peer-to-peer (P2P) networks, similar approaches are just beginning to emerge, also motivated by the fact, that sending (atomic) queries to the appropriate peers clearly fails for queries which need data from more than one peer to be executed. While quite a few database techniques can be re-used in this new context, a P2P data management infrastructure poses additional challenges which have to be solved before schema-based P2P networks become as common as schema-based databases. Because of the dynamic nature of P2P networks, we can neither assume global knowledge about data distribution, nor are static topologies and static query plans suitable for these networks. Unlike in traditional distributed database systems, we cannot assume a complete schema instance but rather work with a distributed schema which directs query processing tasks from one node to one or more neighboring nodes.