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LHD: optimising linked data query processing using parallelisation

Wang, Xin, Tiropanis, Thanassis and Davis, Hugh C. (2013) LHD: optimising linked data query processing using parallelisation At Linked Data on the Web (LDOW2013), Brazil. 14 May 2013.

Record type: Conference or Workshop Item (Paper)


In the past few years as large volume of Linked Data is being publishing, processing distributed SPARQL queries over the Linked Data cloud is becoming increasingly challenging. The high data traffic cost and response time significantly affect the performance of distributed SPARQL queries as the number of SPARQL end point and the volume of data at each endpoint increase. In this context, parallelisation is promising to fully exploit the potential of connections to SPARQL endpoints and thus improve the efficiency of querying Linked Data. We propose LHD, a distributed SPARQL engine that is built on a highly parallel infrastructure and able to minimise query response time, and we evaluate its performance using a BSBM based environment.

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Published date: 14 May 2013
Venue - Dates: Linked Data on the Web (LDOW2013), Brazil, 2013-05-14 - 2013-05-14
Keywords: sparql, linked data, distributed query processing
Organisations: Web & Internet Science


Local EPrints ID: 350719
PURE UUID: b8a3799d-77a3-4d2e-91bc-488452361ea8
ORCID for Thanassis Tiropanis: ORCID iD
ORCID for Hugh C. Davis: ORCID iD

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Date deposited: 08 Apr 2013 14:47
Last modified: 18 Jul 2017 04:31

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Author: Xin Wang
Author: Hugh C. Davis ORCID iD

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