156 resultados para P2P


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The Three-Layer distributed mediation architecture, designed by Secure System Architecture laboratory, employed a layered framework of presence, integration, and homogenization mediators. The architecture does not have any central component that may affect the system reliability. A distributed search technique was adapted in the system to increase its reliability. An Enhanced Chord-like algorithm (E-Chord) was designed and deployed in the integration layer. The E-Chord is a skip-list algorithm based on Distributed Hash Table (DHT) which is a distributed but structured architecture. DHT is distributed in the sense that no central unit is required to maintain indexes, and it is structured in the sense that indexes are distributed over the nodes in a systematic manner. Each node maintains three kind of routing information: a frequency list, a successor/predecessor list, and a finger table. None of the nodes in the system maintains all indexes, and each node knows about some other nodes in the system. These nodes, also called composer mediators, were connected in a P2P fashion. ^ A special composer mediator called a global mediator initiates the keyword-based matching decomposition of the request using the E-Chord. It generates an Integrated Data Structure Graph (IDSG) on the fly, creates association and dependency relations between nodes in the IDSG, and then generates a Global IDSG (GIDSG). The GIDSG graph is a plan which guides the global mediator how to integrate data. It is also used to stream data from the mediators in the homogenization layer which connected to the data sources. The connectors start sending the data to the global mediator just after the global mediator creates the GIDSG and just before the global mediator sends the answer to the presence mediator. Using the E-Chord and GIDSG made the mediation system more scalable than using a central global schema repository since all the composers in the integration layer are capable of handling and routing requests. Also, when a composer fails, it would only minimally affect the entire mediation system. ^

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DOB (4‐bromo‐2,5‐dimethoxyamphetamine) is a newly emerging hallucinogenic amphetamine that sparked serious health warnings in Ireland, following its first seizure back in 2003. Known more commonly as “snowball”, this drug is highly potent and may be used as a substitute to ecstasy (MDMA) and lysergic acid diethylamide (LSD). To date, the work carried out on the impurity profiling of DOB is limited in comparison to amphetamine, methamphetamine and MDMA. In this work, the impurity profile of 4‐bromo‐2,5‐dimethoxyphenyl‐2‐propanone (4‐Br‐2,5‐P2P) is explored. This ketone is a direct precursor to DOB. Its more versatile non‐bromo analogue, 2,5‐ dimethoxyphenyl‐2‐propanone (2,5‐P2P) is also examined, as in addition to DOB, it may be used in the synthesis of a range of several other hallucinogenic amphetamines. A number of different routes to both 2,5‐P2P and 4‐Br‐2,5‐P2P were investigated. For each of these routes, the impurities produced were carefully isolated. Following isolation, the impurities were fully characterised (by 1H‐NMR/13C‐NMR spectroscopy, IR, MS), in order to aid structure elucidation. Compounds not easily resolved by flash column chromatography were analysed by LC‐MS and/or independently synthesised for the purpose of attaining reference standards. Adaptation of the well‐known ‘phenylacetic acid route’ to synthesis of both 2,5‐P2P and 4‐Br‐2,5‐P2P, was found to provide low yields of the expected ketone products. Four impurities were isolated during the preparation of both ketones. The yield of one of these impurities (possessing a dibenzylketone core), was greatly influenced by the amount of acetic anhydride reagent used during the reaction. Having carried out the reaction with several different equivalents of acetic anhydride, it was found that formation of the ‘dibenzylketone’ could not be eliminated. This may increase its likelihood of being detected in the final drug product. The ‘Darzens route’, having very recently emerged as a synthetic route to amphetamine and MDMA precursors, was discovered to be a viable route for manufacture of 2,5‐P2P and 4‐Br‐2,5‐P2P. Despite execution of the reaction being more tedious, the route provides superior yields (≈50–60%) to those achieved using the ‘phenylacetic acid route’ (≈35–38%). Incorporation of a bromine atom (at the aromatic 4‐position) is required at some stage during synthesis of DOB. The bromination of many intermediates/starting materials was therefore also examined in detail. Bromination of the acid starting material 2,5‐dimethoxyphenylacetic acid (2,5‐PAA) was found to be clean and high yielding. This was in stark contrast to the bromination of the benzaldehyde starting material, the ketone precursor 2,5‐P2P and the dibenzylketone‐based impurity. Numerous brominated products were isolated from each of these reactions, many of which were novel compounds, and previously unreported as impurities in the literature. The unpredictable/nondescript nature of these brominations is likely to have a significant impact on the impurity profile of illicitly produced DOB.

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In this paper, we describe a decentralized privacy-preserving protocol for securely casting trust ratings in distributed reputation systems. Our protocol allows n participants to cast their votes in a way that preserves the privacy of individual values against both internal and external attacks. The protocol is coupled with an extensive theoretical analysis in which we formally prove that our protocol is resistant to collusion against as many as n-1 corrupted nodes in the semi-honest model. The behavior of our protocol is tested in a real P2P network by measuring its communication delay and processing overhead. The experimental results uncover the advantages of our protocol over previous works in the area; without sacrificing security, our decentralized protocol is shown to be almost one order of magnitude faster than the previous best protocol for providing anonymous feedback.

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We consider the problem of resource selection in clustered Peer-to-Peer Information Retrieval (P2P IR) networks with cooperative peers. The clustered P2P IR framework presents a significant departure from general P2P IR architectures by employing clustering to ensure content coherence between resources at the resource selection layer, without disturbing document allocation. We propose that such a property could be leveraged in resource selection by adapting well-studied and popular inverted lists for centralized document retrieval. Accordingly, we propose the Inverted PeerCluster Index (IPI), an approach that adapts the inverted lists, in a straightforward manner, for resource selection in clustered P2P IR. IPI also encompasses a strikingly simple peer-specific scoring mechanism that exploits the said index for resource selection. Through an extensive empirical analysis on P2P IR testbeds, we establish that IPI competes well with the sophisticated state-of-the-art methods in virtually every parameter of interest for the resource selection task, in the context of clustered P2P IR.

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Conventional web search engines are centralised in that a single entity crawls and indexes the documents selected for future retrieval, and the relevance models used to determine which documents are relevant to a given user query. As a result, these search engines suffer from several technical drawbacks such as handling scale, timeliness and reliability, in addition to ethical concerns such as commercial manipulation and information censorship. Alleviating the need to rely entirely on a single entity, Peer-to-Peer (P2P) Information Retrieval (IR) has been proposed as a solution, as it distributes the functional components of a web search engine – from crawling and indexing documents, to query processing – across the network of users (or, peers) who use the search engine. This strategy for constructing an IR system poses several efficiency and effectiveness challenges which have been identified in past work. Accordingly, this thesis makes several contributions towards advancing the state of the art in P2P-IR effectiveness by improving the query processing and relevance scoring aspects of a P2P web search. Federated search systems are a form of distributed information retrieval model that route the user’s information need, formulated as a query, to distributed resources and merge the retrieved result lists into a final list. P2P-IR networks are one form of federated search in routing queries and merging result among participating peers. The query is propagated through disseminated nodes to hit the peers that are most likely to contain relevant documents, then the retrieved result lists are merged at different points along the path from the relevant peers to the query initializer (or namely, customer). However, query routing in P2P-IR networks is considered as one of the major challenges and critical part in P2P-IR networks; as the relevant peers might be lost in low-quality peer selection while executing the query routing, and inevitably lead to less effective retrieval results. This motivates this thesis to study and propose query routing techniques to improve retrieval quality in such networks. Cluster-based semi-structured P2P-IR networks exploit the cluster hypothesis to organise the peers into similar semantic clusters where each such semantic cluster is managed by super-peers. In this thesis, I construct three semi-structured P2P-IR models and examine their retrieval effectiveness. I also leverage the cluster centroids at the super-peer level as content representations gathered from cooperative peers to propose a query routing approach called Inverted PeerCluster Index (IPI) that simulates the conventional inverted index of the centralised corpus to organise the statistics of peers’ terms. The results show a competitive retrieval quality in comparison to baseline approaches. Furthermore, I study the applicability of using the conventional Information Retrieval models as peer selection approaches where each peer can be considered as a big document of documents. The experimental evaluation shows comparative and significant results and explains that document retrieval methods are very effective for peer selection that brings back the analogy between documents and peers. Additionally, Learning to Rank (LtR) algorithms are exploited to build a learned classifier for peer ranking at the super-peer level. The experiments show significant results with state-of-the-art resource selection methods and competitive results to corresponding classification-based approaches. Finally, I propose reputation-based query routing approaches that exploit the idea of providing feedback on a specific item in the social community networks and manage it for future decision-making. The system monitors users’ behaviours when they click or download documents from the final ranked list as implicit feedback and mines the given information to build a reputation-based data structure. The data structure is used to score peers and then rank them for query routing. I conduct a set of experiments to cover various scenarios including noisy feedback information (i.e, providing positive feedback on non-relevant documents) to examine the robustness of reputation-based approaches. The empirical evaluation shows significant results in almost all measurement metrics with approximate improvement more than 56% compared to baseline approaches. Thus, based on the results, if one were to choose one technique, reputation-based approaches are clearly the natural choices which also can be deployed on any P2P network.