3,890 research outputs found
Oyster – Sharing and Re-using Ontologies in a Peer-to-Peer Community
In this paper, we present Oyster, a Peer-to-Peer system for
exchanging ontology metadata among communities in the
Semantic Web. Oyster exploits semantic web techniques in data
representation, query formulation and query result presentation to provide an online solution for sharing ontologies, thus assisting researchers in re-using existing ontologies
Expertise-based peer selection in Peer-to-Peer networks
Peer-to-Peer systems have proven to be an effective way of sharing data. Modern protocols are able to efficiently route a message to a given peer. However, determining the destination peer in the first place is not always trivial. We propose a a message to a given peer. However, determining the destination peer in the first place is not always trivial. We propose a model in which peers advertise their expertise in the Peer-to-Peer network. The knowledge about the expertise of other peers forms a semantic topology. Based on the semantic similarity between the subject of a query and the expertise of other peers, a peer can select appropriate peers to forward queries to, instead of broadcasting the query or sending it to a random set of peers. To calculate our semantic similarity measure, we make the simplifying assumption that the peers share the same ontology. We evaluate the model in a bibliographic scenario, where peers share bibliographic descriptions of publications among each other. In simulation experiments complemented with a real-world field experiment, we show how expertise-based peer selection improves the performance of a Peer-to-Peer system with respect to precision, recall and the number of messages
The state of peer-to-peer network simulators
Networking research often relies on simulation in order to test and evaluate new ideas. An important requirement of this process is that results must be reproducible so that other researchers can replicate, validate and extend existing work. We look at the landscape of simulators for research in peer-to-peer (P2P) networks by conducting a survey of a combined total of over 280 papers from before and after 2007 (the year of the last survey in this area), and comment on the large quantity of research using bespoke, closed-source simulators. We propose a set of criteria that P2P simulators should meet, and poll the P2P research community for their agreement. We aim to drive the community towards performing their experiments on simulators that allow for others to validate their results
A Secure and User Privacy-Preserving Searching Protocol for Peer-to-Peer Networks
File sharing peer-to-peer networks have become quite popular of late as a new paradigm for information exchange among large number of users in the Internet. However, these networks suffer from several problems such as fake content distribution, free riding, whitewashing, poor search scalability, lack of a robust trust model and absence of user privacy protection mechanism. In this paper, a secure and efficient searching scheme for peer-to-peer networks has been proposed that utilizes topology adaptation by constructing an overlay of trusted peers where the neighbors are selected based on their trust ratings and content similarities. While increasing the search efficiency by intelligently exploiting the formation of semantic community structures among the trustworthy peers, the scheme provides a highly reliable module for protecting the privacy of the users and data in the network. Simulation results have demonstrated that the proposed scheme provides efficient searching to good peers while penalizing the malicious peers by increasing their search times
Porqpine: a peer-to-peer search engine
In this paper, we present a fully distributed and collaborative search
engine for web pages: Porqpine. This system uses a novel query-based model
and collaborative filtering techniques in order to obtain user-customized
results. All knowledge about users and profiles is stored in each user
node?s application. Overall the system is a multi-agent system that runs on
the computers of the user community. The nodes interact in a peer-to-peer
fashion in order to create a real distributed search engine where
information is completely distributed among all the nodes in the network.
Moreover, the system preserves the privacy of user queries and results by
maintaining the anonymity of the queries? consumers and results? producers.
The knowledge required by the system to work is implicitly caught through
the monitoring of users actions, not only within the system?s interface but
also within one of the most popular web browsers. Thus, users are not
required to explicitly feed knowledge about their interests into the system
since this process is done automatically. In this manner, users obtain the
benefits of a personalized search engine just by installing the application
on their computer. Porqpine does not intend to shun completely conventional
centralized search engines but to complement them by issuing more accurate
and personalized results.Postprint (published version
- …