Rabab Hayek

Summary management in P2P systems

Sharing huge, massively distributed databases in P2P systems is inherently difficult. As the amount of stored data increases, data localization techniques become no longer sufficient. A practical approach is to rely on compact database summaries rather than raw database records, whose access is costly in large P2P systems. In this paper, we consider summaries that are synthetic, multidimensional views with two main virtues. First, they can be directly queried and used to approximately answer a query without exploring the original data. Second, as semantic indexes, they support locating relevant nodes based on data content. Our main contribution is to define a summary model for P2P systems, and the appropriate algorithms for summary management. Our performance evaluation shows that the cost of query routing is minimized, while incurring a low cost of summary maintenance.

Design of PeerSum: a summary service for P2P applications

Sharing huge databases in distributed systems is inherently difficult. As the amount of stored data increases, data localization techniques become no longer sufficient. A more efficient approach is to rely on compact database summaries rather than raw database records, whose access is costly in large distributed systems. In this paper, we propose PeerSum, a new service for managing summaries over shared data in large P2P and Grid applications. Our summaries are synthetic, multidimensional views with two main virtues. First, they can be directly queried and used to approximately answer a query without exploring the original data. Second, as semantic indexes, they support locating relevant nodes based on data content. Our main contribution is to define a summary model for P2P systems, and the algorithms for summary management. Our performance evaluation shows that the cost of query routing is minimized, while incurring a low cost of summary maintenance.

Data Sharing in P2P Systems

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.

Managing Linguistic Data Summaries in Advanced P2P Applications

As the amount of stored data increases, data localization techniques become no longer sufficient in P2P systems. A practical approach is to rely on compact database summaries rather than raw database records, whose access is costly in large P2P systems. In this chapter, we describe a solution for managing linguistic data summaries in advanced P2P applications which are dealing with semantically rich data. The produced summaries are synthetic, multidimensional views over relational tables. The novelty of this proposal relies on the double summary exploitation in distributed P2P systems. First, as semantic indexes, they support locating relevant nodes based on their data descriptions. Second, due to their intelligibility, these summaries can be directly queried and thus approximately answer a query without the need for exploring original data. The proposed solution consists first in defining a summary model for hierarchical P2P systems. Second, appropriate algorithms for summary creation and maintenance are presented. A query processing mechanism, which relies on summary querying, is then proposed to demonstrate the benefits that might be obtained from summary exploitation.

PeerSum: a summary service for P2P applications

Purpose – The goal of this paper is to contribute to the development of both data localization and description techniques in P2P systems.Design/methodology/approach – The approach consists of introducing a novel indexing technique that relies on linguistic data summarization into the context of P2P systems.Findings – The cost model of the approach, as well as the simulation results have shown that the approach allows the efficient maintenance of data summaries, without incurring high traffic overhead. In addition, the cost of query routing is significantly reduced in the context of summaries.Research limitations/implications – The paper has considered a summary service defined on the APPAs architecture. Future works have to study the extension of this work in order to be generally applicable to any P2P data management system.Practical implications – This paper has mainly studied the quantitative gain that could be obtained in query processing from exploiting data summaries. Future works aim to implement ...

Summary management in unstructured P2P systems

In this paper, we propose managing data summaries in unstructured P2P systems. Our summaries are intelligible views with two main virtues. First, they can be directly queried and used to approximately answer a query. Second, as semantic indexes, they support locating relevant nodes based on data content. The performance evaluation of our proposal shows that the cost of query routing is minimized, while incurring a low cost of summary maintenance.