Towards P2P XML Database Technology

To ease the development of data-intensive P2P applications, we envision a P2P XML Database Management System (P2P XDBMS) that acts as a database middle-ware, providing a uniform database abstraction on top of a dynamic set of distributed data sources. In this PhD work, we research which features such a database abstraction should offer and how it can be realised efficiently by extending and combining existing XML databases with P2P technologies. The first step in this research is a distributed database extension called XRPC. Our planned future work builds upon this, adding P2P abstractions to all main database functionalities (query processing, transactions and data storage)

Integrating XQuery and P2P in MonetDB/XQuery*

MonetDB/XQuery* is a fully functional publicly available XML DBMS that has been extended with distributed and P2P data management functionality. Our (minimal) XQuery language extension XRPC adds the concept of RPC to XQuery, and exploits the set-at-a-time database processing model to optimize the networking cost through a technique called Bulk RPC. We describe our approach to include the services offered by diverse P2P network structures (such as DHTs), in a way that avoids any further intrusion in the XQuery language and semantics, and show how this, similarly to Bulk RPC, will lead to further query optimization opportunities where the XDBMS interacts with the underlying P2P network. We also discuss some P2P data management applications were MonetDB/XQuery* is being used (an in-home small scenario and a wide-area collaborative application). As this research is work-in-progress, we outline some research questions on our path towards defining and realizing P2P XDBMS technology

An Efficient Architecture for Information Retrieval in P2P Context Using Hypergraph

Peer-to-peer (P2P) Data-sharing systems now generate a significant portion of Internet traffic. P2P systems have emerged as an accepted way to share enormous volumes of data. Needs for widely distributed information systems supporting virtual organizations have given rise to a new category of P2P systems called schema-based. In such systems each peer is a database management system in itself, ex-posing its own schema. In such a setting, the main objective is the efficient search across peer databases by processing each incoming query without overly consuming bandwidth. The usability of these systems depends on successful techniques to find and retrieve data; however, efficient and effective routing of content-based queries is an emerging problem in P2P networks. This work was attended as an attempt to motivate the use of mining algorithms in the P2P context may improve the significantly the efficiency of such methods. Our proposed method based respectively on combination of clustering with hypergraphs. We use ECCLAT to build approximate clustering and discovering meaningful clusters with slight overlapping. We use an algorithm MTMINER to extract all minimal transversals of a hypergraph (clusters) for query routing. The set of clusters improves the robustness in queries routing mechanism and scalability in P2P Network. We compare the performance of our method with the baseline one considering the queries routing problem. Our experimental results prove that our proposed methods generate impressive levels of performance and scalability with with respect to important criteria such as response time, precision and recall.Comment: 2o pages, 8 figure

The ViP2P Platform: XML Views in P2P

The growing volumes of XML data sources on the Web or produced by enterprises, organizations etc. raise many performance challenges for data management applications. In this work, we are concerned with the distributed, peer-to-peer management of large corpora of XML documents, based on distributed hash table (or DHT, in short) overlay networks. We present ViP2P (standing for Views in Peer-to-Peer), a distributed platform for sharing XML documents based on a structured P2P network infrastructure (DHT). At the core of ViP2P stand distributed materialized XML views, defined by arbitrary XML queries, filled in with data published anywhere in the network, and exploited to efficiently answer queries issued by any network peer. ViP2P allows user queries to be evaluated over XML documents published by peers in two modes. First, a long-running subscription mode, when a query can be registered in the system and receive answers incrementally when and if published data matches the query. Second, queries can also be asked in an ad-hoc, snapshot mode, where results are required immediately and must be computed based on the results of other long-running, subscription queries. ViP2P innovates over other similar DHT-based XML sharing platforms by using a very expressive structured XML query language. This expressivity leads to a very flexible distribution of XML content in the ViP2P network, and to efficient snapshot query execution. ViP2P has been tested in real deployments of hundreds of computers. We present the platform architecture, its internal algorithms, and demonstrate its efficiency and scalability through a set of experiments. Our experimental results outgrow by orders of magnitude similar competitor systems in terms of data volumes, network size and data dissemination throughput.Comment: RR-7812 (2011

Peer Data Management

Peer Data Management (PDM) deals with the management of structured data in unstructured peer-to-peer (P2P) networks. Each peer can store data locally and define relationships between its data and the data provided by other peers. Queries posed to any of the peers are then answered by also considering the information implied by those mappings. The overall goal of PDM is to provide semantically well-founded integration and exchange of heterogeneous and distributed data sources. Unlike traditional data integration systems, peer data management systems (PDMSs) thereby allow for full autonomy of each member and need no central coordinator. The promise of such systems is to provide flexible data integration and exchange at low setup and maintenance costs. However, building such systems raises many challenges. Beside the obvious scalability problem, choosing an appropriate semantics that can deal with arbitrary, even cyclic topologies, data inconsistencies, or updates while at the same time allowing for tractable reasoning has been an area of active research in the last decade. In this survey we provide an overview of the different approaches suggested in the literature to tackle these problems, focusing on appropriate semantics for query answering and data exchange rather than on implementation specific problems

Data replication and update propagation in XML P2P data management systems

XML P2P data management systems are P2P systems that use XML as the underlying data format shared between peers in the network. These systems aim to bring the benefits of XML and P2P systems to the distributed data management field. However, P2P systems are known for their lack of central control and high degree of autonomy. Peers may leave the network at any time at will, increasing the risk of data loss. Despite this, most research in XML P2P systems focus on novel and efficient XML indexing and retrieval techniques. Mechanisms for ensuring data availability in XML P2P systems has received comparatively little attention. This project attempts to address this issue. We design an XML P2P data management framework to improve data availability. This framework includes mechanisms for wide-spread data replication, replica location and update propagation. It allows XML documents to be broken down into fragments. By doing so, we aim to reduce the cost of replicating data by distributing smaller XML fragments throughout the network rather than entire documents. To tackle the data replication problem, we propose a suite of selection and placement algorithms that may be interchanged to form a particular replication strategy. To support the placement of replicas anywhere in the network, we use a Fragment Location Catalogue, a global index that maintains the locations of replicas. We also propose a lazy update propagation algorithm to propagate updates to replicas. Experiments show that the data replication algorithms improve data availability in our experimental network environment. We also find that breaking XML documents into smaller pieces and replicating those instead of whole XML documents considerably reduces the replication cost, but at the price of some loss in data availability. For the update propagation tests, we find that the probability that queries return up-to-date results increases, but improvements to the algorithm are necessary to handle environments with high update rates

Méthode de découverte de sources de données tenant compte de la sémantique en environnement de grille de données

Les applications grilles de données de nos jours partagent un nombre gigantesque de sources de données en un environnement instable où une source de données peut à tout moment joindre ou quitter le système. Ces sources de données sont hétérogènes, autonomes et distribuées à grande échelle. Dans cet environnement, la découverte efficace des sources de données pertinentes pour l'exécution de requêtes est un défi. Les premiers travaux sur la découverte de sources de données se sont basés sur une recherche par mots clés. Ces solutions ne sont pas satisfaisantes puisqu'elles ne tiennent pas compte des problèmes de l'hétérogénéité sémantique des sources de données. Ainsi, d'autres solutions proposent un schéma global ou une ontologie globale. Cependant, la conception d'un tel schéma ou d'une telle ontologie est une tâche complexe à cause du nombre de sources de données. D'autres solutions optent pour l'usage de correspondances entre les schémas des sources de données ou en s'appuyant sur des ontologies de domaine et en établissant des relations de 'mapping' entre ces dernières. Toutes ces solutions imposent une topologie fixe soit pour les correspondances soit pour les relations de 'mapping'. Cependant, la définition de relations de 'mapping' entre ontologies de domaine est une tâche ardue et imposer une topologie fixe est un inconvénient majeur. Dans cette perspective, nous proposons dans cette thèse une méthode de découverte de sources de données prenant en compte les problèmes liés à l'hétérogénéité sémantique en environnement instable et à grande échelle. Pour cela, nous associons une Organisation Virtuelle (OV) et une ontologie de domaine à chaque domaine et nous nous basons sur les relations de 'mappings' existantes entre ces ontologies. Nous n'imposons aucune hypothèse sur la topologie des relations de 'mapping' mis à part que le graphe qu'elles forment soit connexe. Nous définissons un système d'adressage permettant un accès permanent de n'importe quelle OV vers une autre malgré la dynamicité des pairs. Nous présentons également une méthode de maintenance dite 'paresseuse' afin de limiter le nombre de messages nécessaires à la maintenance du système d'adressage lors de la connexion ou de la déconnexion de pairs. Pour étudier la faisabilité ainsi que la viabilité de nos propositions, nous effectuons une évaluation des performances.Nowadays, data grid applications look to share a huge number of data sources in an unstable environment where a data source may join or leave the system at any time. These data sources are highly heterogeneous because they are independently developed and managed and geographically scattered. In this environment, efficient discovery of relevant data sources for query execution is a complex problem due to the source heterogeneity, large scale environment and system instability. First works on data source discovery are based on a keyword search. These initial solutions are not sufficient because they do not take into account problem of semantic heterogeneity of data sources. Thus, the community has proposed other solutions to consider semantic aspects. A first solution consists in using a global schema or global ontology. However, the conception of such scheme or such ontology is a complex task due to the number of data sources. Other solutions have been proposed providing mappings between data source schemas or based on domain ontologies and establishing mapping relations between them. All these solutions impose a fixed topology for connections as well as mapping relationships. However, the definition of mapping relations between domain ontologies is a difficult task and imposing a fixed topology is a major inconvenience. In this perspective, we propose in this thesis a method for discovering data sources taking into account semantic heterogeneity problems in unstable and large scale environment. For that purpose, we associate a Virtual Organisation (VO) and a domain ontology to each domain and we rely on relationship mappings between existing ontologies. We do not impose any hypothesis on the relationship mapping topology, except that they form connected graph. We define an addressing system for permanent access from any OVi to another OVj despite peers' dynamicity (with i inégalité j). We also present a method of maintenance called 'lazy' to limit the number of messages required to maintain the addressing system during the connection or disconnection of peers. To study the feasibility as well as the viability of our proposals, we make a performance evaluation