10 research outputs found

    Efficient and Flexible Search in Large Scale Distributed Systems

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    Peer-to-peer (P2P) technology has triggered a wide range of distributed systems beyond simple file-sharing. Distributed XML databases, distributed computing, server-less web publishing and networked resource/service sharing are only a few to name. Despite of the diversity in applications, these systems share a common problem regarding searching and discovery of information. This commonality stems from the transitory nodes population and volatile information content in the participating nodes. In such dynamic environment, users are not expected to have the exact information about the available objects in the system. Rather queries are based on partial information, which requires the search mechanism to be flexible. On the other hand, to scale with network size the search mechanism is required to be bandwidth efficient. Since the advent of P2P technology experts from industry and academia have proposed a number of search techniques - none of which is able to provide satisfactory solution to the conflicting requirements of search efficiency and flexibility. Structured search techniques, mostly Distributed Hash Table (DHT)-based, are bandwidth efficient while semi(un)-structured techniques are flexible. But, neither achieves both ends. This thesis defines the Distributed Pattern Matching (DPM) problem. The DPM problem is to discover a pattern (\ie bit-vector) using any subset of its 1-bits, under the assumption that the patterns are distributed across a large population of networked nodes. Search problem in many distributed systems can be reduced to the DPM problem. This thesis also presents two distinct search mechanisms, named Distributed Pattern Matching System (DPMS) and Plexus, for solving the DPM problem. DPMS is a semi-structured, hierarchical architecture aiming to discover a predefined number of matches by visiting a small number of nodes. Plexus, on the other hand, is a structured search mechanism based on the theory of Error Correcting Code (ECC). The design goal behind Plexus is to discover all the matches by visiting a reasonable number of nodes

    Enabling Internet-Scale Publish/Subscribe In Overlay Networks

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    As the amount of data in todays Internet is growing larger, users are exposed to too much information, which becomes increasingly more difficult to comprehend. Publish/subscribe systems leverage this problem by providing loosely-coupled communications between producers and consumers of data in a network. Data consumers, i.e., subscribers, are provided with a subscription mechanism, to express their interests in a subset of data, in order to be notified only when some data that matches their subscription is generated by the producers, i.e., publishers. Most publish/subscribe systems today, are based on the client/server architectural model. However, to provide the publish/subscribe service in large scale, companies either have to invest huge amount of money for over-provisioning the resources, or are prone to frequent service failures. Peer-to-peer overlay networks are attractive alternative solutions for building Internet-scale publish/subscribe systems. However, scalability comes with a cost: a published message often needs to traverse a large number of uninterested (unsubscribed) nodes before reaching all its subscribers. We refer to this undesirable traffic, as relay overhead. Without careful considerations, the relay overhead might sharply increase resource consumption for the relay nodes (in terms of bandwidth transmission cost, CPU, etc) and could ultimately lead to rapid deterioration of the system’s performance once the relay nodes start dropping the messages or choose to permanently abandon the system. To mitigate this problem, some solutions use unbounded number of connections per node, while some other limit the expressiveness of the subscription scheme. In this thesis work, we introduce two systems called Vitis and Vinifera, for topic-based and content-based publish/subscribe models, respectively. Both these systems are gossip-based and significantly decrease the relay overhead. We utilize novel techniques to cluster together nodes that exhibit similar subscriptions. In the topic-based model, distinct clusters for each topic are constructed, while clusters in the content-based model are fuzzy and do not have explicit boundaries. We augment these clustered overlays by links that facilitate routing in the network. We construct a hybrid system by injecting structure into an otherwise unstructured network. The resulting structures resemble navigable small-world networks, which spans along clusters of nodes that have similar subscriptions. The properties of such overlays make them an ideal platform for efficient data dissemination in large-scale systems. The systems requires only a bounded node degree and as we show, through simulations, they scale well with the number of nodes and subscriptions and remain efficient under highly complex subscription patterns, high publication rates, and even in the presence of failures in the network. We also compare both systems against some state-of-the-art publish/subscribe systems. Our measurements show that both Vitis and Vinifera significantly outperform their counterparts on various subscription and churn scenarios, under both synthetic workloads and real-world traces

    Performance and Security Improvements for Tor: A Survey

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    Tor [Dingledine et al. 2004] is the most widely used anonymity network today, serving millions of users on a daily basis using a growing number of volunteer-run routers. Since its deployment in 2003, there have been more than three dozen proposals that aim to improve its performance, security, and unobservability. Given the significance of this research area, our goal is to provide the reader with the state of current research directions and challenges in anonymous communication systems, focusing on the Tor network.We shed light on the design weaknesses and challenges facing the network and point out unresolved issues

    Semantic search and composition in unstructured peer-to-peer networks

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    This dissertation focuses on several research questions in the area of semantic search and composition in unstructured peer-to-peer (P2P) networks. Going beyond the state of the art, the proposed semantic-based search strategy S2P2P offers a novel path-suggestion based query routing mechanism, providing a reasonable tradeoff between search performance and network traffic overhead. In addition, the first semantic-based data replication scheme DSDR is proposed. It enables peers to use semantic information to select replica numbers and target peers to address predicted future demands. With DSDR, k-random search can achieve better precision and recall than it can with a near-optimal non-semantic replication strategy. Further, this thesis introduces a functional automatic semantic service composition method, SPSC. Distinctively, it enables peers to jointly compose complex workflows with high cumulative recall but low network traffic overhead, using heuristic-based bidirectional haining and service memorization mechanisms. Its query branching method helps to handle dead-ends in a pruned search space. SPSC is proved to be sound and a lower bound of is completeness is given. Finally, this thesis presents iRep3D for semantic-index based 3D scene selection in P2P search. Its efficient retrieval scales to answer hybrid queries involving conceptual, functional and geometric aspects. iRep3D outperforms previous representative efforts in terms of search precision and efficiency.Diese Dissertation bearbeitet Forschungsfragen zur semantischen Suche und Komposition in unstrukturierten Peer-to-Peer Netzen(P2P). Die semantische Suchstrategie S2P2P verwendet eine neuartige Methode zur Anfrageweiterleitung basierend auf Pfadvorschlägen, welche den Stand der Wissenschaft übertrifft. Sie bietet angemessene Balance zwischen Suchleistung und Kommunikationsbelastung im Netzwerk. Außerdem wird das erste semantische System zur Datenreplikation genannt DSDR vorgestellt, welche semantische Informationen berücksichtigt vorhergesagten zukünftigen Bedarf optimal im P2P zu decken. Hierdurch erzielt k-random-Suche bessere Präzision und Ausbeute als mit nahezu optimaler nicht-semantischer Replikation. SPSC, ein automatisches Verfahren zur funktional korrekten Komposition semantischer Dienste, ermöglicht es Peers, gemeinsam komplexe Ablaufpläne zu komponieren. Mechanismen zur heuristischen bidirektionalen Verkettung und Rückstellung von Diensten ermöglichen hohe Ausbeute bei geringer Belastung des Netzes. Eine Methode zur Anfrageverzweigung vermeidet das Feststecken in Sackgassen im beschnittenen Suchraum. Beweise zur Korrektheit und unteren Schranke der Vollständigkeit von SPSC sind gegeben. iRep3D ist ein neuer semantischer Selektionsmechanismus für 3D-Modelle in P2P. iRep3D beantwortet effizient hybride Anfragen unter Berücksichtigung konzeptioneller, funktionaler und geometrischer Aspekte. Der Ansatz übertrifft vorherige Arbeiten bezüglich Präzision und Effizienz

    Semantic search and composition in unstructured peer-to-peer networks

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    This dissertation focuses on several research questions in the area of semantic search and composition in unstructured peer-to-peer (P2P) networks. Going beyond the state of the art, the proposed semantic-based search strategy S2P2P offers a novel path-suggestion based query routing mechanism, providing a reasonable tradeoff between search performance and network traffic overhead. In addition, the first semantic-based data replication scheme DSDR is proposed. It enables peers to use semantic information to select replica numbers and target peers to address predicted future demands. With DSDR, k-random search can achieve better precision and recall than it can with a near-optimal non-semantic replication strategy. Further, this thesis introduces a functional automatic semantic service composition method, SPSC. Distinctively, it enables peers to jointly compose complex workflows with high cumulative recall but low network traffic overhead, using heuristic-based bidirectional haining and service memorization mechanisms. Its query branching method helps to handle dead-ends in a pruned search space. SPSC is proved to be sound and a lower bound of is completeness is given. Finally, this thesis presents iRep3D for semantic-index based 3D scene selection in P2P search. Its efficient retrieval scales to answer hybrid queries involving conceptual, functional and geometric aspects. iRep3D outperforms previous representative efforts in terms of search precision and efficiency.Diese Dissertation bearbeitet Forschungsfragen zur semantischen Suche und Komposition in unstrukturierten Peer-to-Peer Netzen(P2P). Die semantische Suchstrategie S2P2P verwendet eine neuartige Methode zur Anfrageweiterleitung basierend auf Pfadvorschlägen, welche den Stand der Wissenschaft übertrifft. Sie bietet angemessene Balance zwischen Suchleistung und Kommunikationsbelastung im Netzwerk. Außerdem wird das erste semantische System zur Datenreplikation genannt DSDR vorgestellt, welche semantische Informationen berücksichtigt vorhergesagten zukünftigen Bedarf optimal im P2P zu decken. Hierdurch erzielt k-random-Suche bessere Präzision und Ausbeute als mit nahezu optimaler nicht-semantischer Replikation. SPSC, ein automatisches Verfahren zur funktional korrekten Komposition semantischer Dienste, ermöglicht es Peers, gemeinsam komplexe Ablaufpläne zu komponieren. Mechanismen zur heuristischen bidirektionalen Verkettung und Rückstellung von Diensten ermöglichen hohe Ausbeute bei geringer Belastung des Netzes. Eine Methode zur Anfrageverzweigung vermeidet das Feststecken in Sackgassen im beschnittenen Suchraum. Beweise zur Korrektheit und unteren Schranke der Vollständigkeit von SPSC sind gegeben. iRep3D ist ein neuer semantischer Selektionsmechanismus für 3D-Modelle in P2P. iRep3D beantwortet effizient hybride Anfragen unter Berücksichtigung konzeptioneller, funktionaler und geometrischer Aspekte. Der Ansatz übertrifft vorherige Arbeiten bezüglich Präzision und Effizienz

    Novel Analytical Modelling-based Simulation of Worm Propagation in Unstructured Peer-to-Peer Networks

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    Millions of users world-wide are sharing content using Peer-to-Peer (P2P) networks, such as Skype and Bit Torrent. While such new innovations undoubtedly bring benefits, there are nevertheless some associated threats. One of the main hazards is that P2P worms can penetrate the network, even from a single node and then spread rapidly. Understanding the propagation process of such worms has always been a challenge for researchers. Different techniques, such as simulations and analytical models, have been adopted in the literature. While simulations provide results for specific input parameter values, analytical models are rather more general and potentially cover the whole spectrum of given parameter values. Many attempts have been made to model the worm propagation process in P2P networks. However, the reported analytical models to-date have failed to cover the whole spectrum of all relevant parameters and have therefore resulted in high false-positives. This consequently affects the immunization and mitigation strategies that are adopted to cope with an outbreak of worms. The first key contribution of this thesis is the development of a susceptible, exposed, infectious, and Recovered (SEIR) analytical model for the worm propagation process in a P2P network, taking into account different factors such as the configuration diversity of nodes, user behaviour and the infection time-lag. These factors have not been considered in an integrated form previously and have been either ignored or partially addressed in state-of-the-art analytical models. Our proposed SEIR analytical model holistically integrates, for the first time, these key factors in order to capture a more realistic representation of the whole worm propagation process. The second key contribution is the extension of the proposed SEIR model to the mobile M-SEIR model by investigating and incorporating the role of node mobility, the size of the worm and the bandwidth of wireless links in the worm propagation process in mobile P2P networks. The model was designed to be flexible and applicable to both wired and wireless nodes. The third contribution is the exploitation of a promising modelling paradigm, Agent-based Modelling (ABM), in the P2P worm modelling context. Specifically, to exploit the synergies between ABM and P2P, an integrated ABM-Based worm propagation model has been built and trialled in this research for the first time. The introduced model combines the implementation of common, complex P2P protocols, such as Gnutella and GIA, along with the aforementioned analytical models. Moreover, a comparative evaluation between ABM and conventional modelling tools has been carried out, to demonstrate the key benefits of ease of real-time analysis and visualisation. As a fourth contribution, the research was further extended by utilizing the proposed SEIR model to examine and evaluate a real-world data set on one of the most recent worms, namely, the Conficker worm. Verification of the model was achieved using ABM and conventional tools and by then comparing the results on the same data set with those derived from developed benchmark models. Finally, the research concludes that the worm propagation process is to a great extent affected by different factors such as configuration diversity, user-behaviour, the infection time lag and the mobility of nodes. It was found that the infection propagation values derived from state-of-the-art mathematical models are hypothetical and do not actually reflect real-world values. In summary, our comparative research study has shown that infection propagation can be reduced due to the natural immunity against worms that can be provided by a holistic exploitation of the range of factors proposed in this work
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