We introduce collaborative tagging and faceted search on structured P2P systems. Since a trivial and brute force mapping of an entire folksonomy over a DHT-based system may reduce scalability, we propose an approximated graph maintenance approach. Evaluations on real data coming from Last.fm prove that such strategies reduce vocabulary noise (i.e., representation's overfitting phenomena) and hotspots issues.
A p2p infrastructure for tagging systems () is proposed in @cite_9 ; in particular, the authors design a scheme to maintain feature vectors for characterization of users and resource of a tagging environment on a DHT. Feature vectors may be useful for calculating the similarity between users or for constructing algorithms for ranked retrieval.
@cite_9
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The field of structured P2P systems has seen fast growth upon the introduction of Distributed Hash Tables (DHTs) in the early 2000s. The first proposals, including Chord, Pastry, Tapestry, were gradually improved to cope with scalability, locality and security issues. By utilizing the processing and bandwidth resources of end users, the P2P approach enables high performance of data distribution which is hard to achieve with traditional client-server architectures. The P2P computing community is also being actively utilized for software updates to the Internet, P2PSIP VoIP, video-on-demand, and distributed backups. The recent introduction of the identifier-locator split proposal for future Internet architectures poses another important application for DHTs, namely mapping between host permanent identity and changing IP address. The growing complexity and scale of modern P2P systems requires the introduction of hierarchy and intelligence in routing of requests. Structured Peer-to-Peer Systems covers fundamental issues in organization, optimization, and tradeoffs of present large-scale structured P2P systems, as well as, provides principles, analytical models, and simulation methods applicable in designing future systems. Part I presents the state-of-the-art of structured P2P systems, popular DHT topologies and protocols, and the design challenges for efficient P2P network topology organization, routing, scalability, and security. Part II shows that local strategies with limited knowledge per peer provide the highest scalability level subject to reasonable performance and security constraints. Although the strategies are local, their efficiency is due to elements of hierarchical organization, which appear in many DHT designs that traditionally are considered as flat ones. Part III describes methods to gradually enhance the local view limit when a peer is capable to operate with larger knowledge, still partial, about the entire system. These methods were formed in the evolution of hierarchical organization from flat DHT networks to hierarchical DHT architectures, look-ahead routing, and topology-aware ranking. Part IV highlights some known P2P-based experimental systems and commercial applications in the modern Internet. The discussion clarifies the importance of P2P technology for building present and future Internet systems. Emerging social network applications for sharing and collaboration need a way to publish and search a big amount of social objects. Currently, social applications allow the association of a set of user defined keywords, named tags, when publishing these objects, in order to allow searching for them later using a subset of these tags. Commercial systems and recent research community proposals preclude a wide Internet deployment due to the emergence of scalability and hot spot problems in the nodes. We propose T-DHT, an innovative hybrid unstructured-structured DHT based approach, to cope with these high demanding requirements, in a fully scalable, distributed and balanced way. The storage process allows attaching a set of user tags to the stored object and takes at most O(Log(N)) node hops. The tag information attached to the object is stored in a compact way into the node links using a bloom filter, in order to be used later in the search process. The search process allows searching for previously stored objects by means of a tag conjunction and also takes at most O(Log(N)) node hops. The search process is based on DHT typical search combined with an unstructured search algorithm using the tag information previously stored into bloom filters of node links. The simulation results show T-DHT performs in a fully balanced and scalable way, without generating typical hot spot problems even if unbalanced distributions of popular tags are used. Although T-DHT has been devised to build a scalable infrastructure for social applications, it can be applied to solve the more general Peer-to-Peer keyword search problems. In this paper, we address the problem of designing a scalable, accurate query processor for peer-to-peer filesharing and similar distributed keyword search systems. Using a globally-distributed monitoring infrastructure, we perform an extensive study of the Gnutella filesharing network, characterizing its topology, data and query workloads. We observe that Gnutella's query processing approach performs well for popular content, but quite poorly for rare items with few replicas. We then consider an alternate approach based on Distributed Hash Tables (DHTs). We describe our implementation of PIERSearch, a DHT-based system, and propose a hybrid system where Gnutella is used to locate popular items, and PIERSearch for handling rare items. We develop an analytical model of the two approaches, and use it in concert with our Gnutella traces to study the trade-off between query recall and system overhead of the hybrid system. We evaluate a variety of localized schemes for identifying items that are rare and worth handling via the DHT. Lastly, we show in a live deployment on fifty nodes on two continents that it nicely complements Gnutella in its ability to handle rare items. Distributed hash table (DHT) systems are an important class of peer-to-peer routing infrastructures. They enable scalable wide-area storage and retrieval of information, and will support the rapid development of a wide variety of Internet-scale applications ranging from naming systems and file systems to application-layer multicast. DHT systems essentially build an overlay network, but a path on the overlay between any two nodes can be significantly different from the unicast path between those two nodes on the underlying network. As such, the lookup latency in these systems can be quite high and can adversely impact the performance of applications built on top of such systems.In this paper, we discuss a random sampling technique that incrementally improves lookup latency in DHT systems. Our sampling can be implemented using information gleaned from lookups traversing the overlay network. For this reason, we call our approach lookup-parasitic random sampling (LPRS). LPRS is fast, incurs little network overhead, and requires relatively few modifications to existing DHT systems.For idealized versions of DHT systems like Chord, Tapestry and Pastry, we analytically prove that LPRS can result in lookup latencies proportional to the average unicast latency of the network, provided the underlying physical topology has a power-law latency expansion. We then validate this analysis by implementing LPRS in the Chord simulator. Our simulations reveal that LPRS-Chord exhibits a qualitatively better latency scaling behavior relative to unmodified Chord.Finally, we provide evidence which suggests that the Internet router-level topology resembles power-law latency expansion. This finding implies that LPRS has significant practical applicability as a general latency reduction technique for many DHT systems. This finding is also of independent interest since it might inform the design of latency-sensitive topology models for the Internet.