On Constructing Small Worlds in Unstructured Peer-to-Peer Systems

Petrakis, Yannis; Pitoura, Evaggelia

doi:10.1007/978-3-540-30192-9_41

Cited by 8 publications

(6 citation statements)

References 13 publications

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“…Thus, the process of establishing the network by choosing the ''right'' neighbors and defining the mappings is an important problem that can be addressed by ideas from small-world graphs [48,65]. In the same way, the continuous restructuring and evolvement of the network can help to improve query answering [31,59].…”

Section: Discussionmentioning

confidence: 99%

A research agenda for query processing in large-scale peer data management systems

Hose

Roth

Zeitz

et al. 2008

Information Systems

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Section: Discussionmentioning

confidence: 99%

A research agenda for query processing in large-scale peer data management systems

Hose

Roth

Zeitz

et al. 2008

Information Systems

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“…Crespo et al [13] introduced the notion of routing indexes in P2P systems as structures that, given a query, return a list of interesting neighbours (sources) based on a data structure conforming to lists of counts for keyword occurrences in documents. Based on this work, other variants of routing indexes have been proposed, e.g., based on one-dimensional histograms [53], Bloom Filters [54], bit vectors [46], or the QTree. A common feature across these systems is to use a hash function to map string data to a numerical data space.…”

Section: Related Workmentioning

confidence: 99%

Comparing data summaries for processing live queries over Linked Data

et al. 2011

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A growing amount of Linked Data-graph-structured data accessible at sources distributed across the Web-enables advanced data integration and decisionmaking applications. Typical systems operating on Linked Data collect (crawl) and pre-process (index) large amounts of data, and evaluate queries against a centralised repository. Given that crawling and indexing are time-consuming operations, the data in the centralised index may be out of date at query execution time. An ideal query answering system for querying Linked Data live should return current answers in a reasonable amount of time, even on corpora as large as the Web. In such a live query system source selection-determining which sources contribute answers to a query-is a crucial step. In this article we propose to use lightweight data summaries for determining relevant sources during query evaluation. We compare several data structures and hash functions with respect to their suitability for building such summaries, stressing benefits for queries that contain joins and require ranking of results and sources. We elaborate on join variants, join ordering and ranking. We analyse the different approaches theoretically and provide results of an extensive experimental evaluation.

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“…Crespo et al [5] introduced the notion of routing indexes in P2P systems as structures that, given a query, return a list of inter-esting neighbours (sources) based on a data structure conforming to lists of counts for keyword occurrences in documents. Based on this work, other variants of routing indexes have been proposed, e.g., based on one-dimensional histograms [22], Bloom Filters [23], bit vectors [19], or the QTree. A common feature across these systems is to use a hash function to map string data to a numerical data space.…”

Section: Related Workmentioning

confidence: 99%

Data summaries for on-demand queries over linked data

Harth

Hose

Karnstedt

et al. 2010

Proceedings of the 19th International Conference on World Wide Web

156

155

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Typical approaches for querying structured Web Data collect (crawl) and pre-process (index) large amounts of data in a central data repository before allowing for query answering. However, this time-consuming pre-processing phase however leverages the benefits of Linked Data -where structured data is accessible live and up-to-date at distributed Web resources that may change constantly -only to a limited degree, as query results can never be current. An ideal query answering system for Linked Data should return current answers in a reasonable amount of time, even on corpora as large as the Web. Query processors evaluating queries directly on the live sources require knowledge of the contents of data sources. In this paper, we develop and evaluate an approximate index structure summarising graph-structured content of sources adhering to Linked Data principles, provide an algorithm for answering conjunctive queries over Linked Data on the Web exploiting the source summary, and evaluate the system using synthetically generated queries. The experimental results show that our lightweight index structure enables complete and up-to-date query results over Linked Data, while keeping the overhead for querying low and providing a satisfying source ranking at no additional cost.

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On Constructing Small Worlds in Unstructured Peer-to-Peer Systems

Cited by 8 publications

References 13 publications

A research agenda for query processing in large-scale peer data management systems

A research agenda for query processing in large-scale peer data management systems

Comparing data summaries for processing live queries over Linked Data

Data summaries for on-demand queries over linked data

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