Data sharing in DHT based P2P systems

International audienceThe evolution of peer-to-peer (P2P) systems triggered the building of large scale distributed applications. The main application domain is data sharing across a very large number of highly autonomous participants. Building such data sharing systems is particularly challenging because of the "extreme" characteristics of P2P infrastructures: massive distribution, high churn rate, no global control, potentially untrusted participants... This article focuses on declarative querying support, query optimization and data privacy on a major class of P2P systems, that based on Distributed Hash Table (P2P DHT). The usual approaches and the algorithms used by classic distributed systems and databases forproviding data privacy and querying services are not well suited to P2P DHT systems. A considerable amount of work was required to adapt them for the new challenges such systems present. This paper describes the most important solutions found. It also identies important future research trends in data management in P2P DHT systems

Statistical structures for internet-scale data management

Efficient query processing in traditional database management systems relies on statistics on base data. For centralized systems, there is a rich body of research results on such statistics, from simple aggregates to more elaborate synopses such as sketches and histograms. For Internet-scale distributed systems, on the other hand, statistics management still poses major challenges. With the work in this paper we aim to endow peer-to-peer data management over structured overlays with the power associated with such statistical information, with emphasis on meeting the scalability challenge. To this end, we first contribute efficient, accurate, and decentralized algorithms that can compute key aggregates such as Count, CountDistinct, Sum, and Average. We show how to construct several types of histograms, such as simple Equi-Width, Average-Shifted Equi-Width, and Equi-Depth histograms. We present a full-fledged open-source implementation of these tools for distributed statistical synopses, and report on a comprehensive experimental performance evaluation, evaluating our contributions in terms of efficiency, accuracy, and scalability

Answering Tag-Term Keyword Queries over XML Documents in DHT Networks

Abstract. The emergence of Peer-to-Peer (P2P) computing model and the popularity of Extensible Markup Language (XML) as the web data format have fueled the extensive research on retrieving XML data in P2P networks. In this paper, we developed an efficient and effective keyword search framework that can support tag-term keyword queries in Distributed Hash Table (DHT) networks. We employed a concise Bloom-Filter data structure to index XML meta-data in the DHT repository. We also developed an effective algorithm that supports tag-term keyword queries over our Bloom-Filter encoded XML meta-data in the DHT network. We conducted extensive experiments to demonstrate the efficiency of indexing scheme, the effectiveness of our keyword query algorithm and the system scalability of our framework

Data Sharing in P2P Systems

To appear in Springer's "Handbook of P2P Networking"In this chapter, we survey P2P data sharing systems. All along, we focus on the evolution from simple file-sharing systems, with limited functionalities, to Peer Data Management Systems (PDMS) that support advanced applications with more sophisticated data management techniques. Advanced P2P applications are dealing with semantically rich data (e.g. XML documents, relational tables), using a high-level SQL-like query language. We start our survey with an overview over the existing P2P network architectures, and the associated routing protocols. Then, we discuss data indexing techniques based on their distribution degree and the semantics they can capture from the underlying data. We also discuss schema management techniques which allow integrating heterogeneous data. We conclude by discussing the techniques proposed for processing complex queries (e.g. range and join queries). Complex query facilities are necessary for advanced applications which require a high level of search expressiveness. This last part shows the lack of querying techniques that allow for an approximate query answering

Query processing in P2P systems

Peer-to-peer (P2P) computing offers new opportunities for building highly distributed data systems. Unlike client-server computing, P2P is a very dynamic environment where peers can join and leave the network at any time. This yields important advantages such as operation without central coordination, peers autonomy, and scale up to large number of peers. However, providing high-level data management services is difficult. Most techniques designed in distributed database systems which statically exploit schema and network information no longer apply. New techniques are needed which should be decentralized, dynamic and self-adaptive. In this paper, we survey the techniques which have been developed for query processing in P2P systems. We first give an overview of the existing P2P networks, and com-pare their properties from the perspective of data management. Then, we discuss the ap-proaches which are used for schema mapping. Then, we describe the algorithms which have been proposed for query routing. In particular, we focus on query routing in unstructured net-works and DHTs. Finally, we present the techniques which have been proposed for processing complex queries, e.g. top-k queries, in P2P systems, in particular in DHTs