Social Based Layouts for the Increase of Locality in Graph Operations

Graphs provide a natural data representation for analyzing the relationships among entities in many application areas. Since the analysis algorithms perform memory intensive operations, it is important that the graph layout is adapted to take advantage of the memory hierarchy. Here, we propose layou...

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Bibliographic Details
Published inDatabase Systems for Advanced Applications pp. 558 - 569
Main Authors Prat-Pérez, Arnau, Dominguez-Sal, David, Larriba-Pey, Josep L.
Format Book Chapter
LanguageEnglish
Published Berlin, Heidelberg Springer Berlin Heidelberg 2011
SeriesLecture Notes in Computer Science
Subjects
community detection
graph mining
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ISBN9783642201486
3642201482
ISSN0302-9743
1611-3349
DOI10.1007/978-3-642-20149-3_40

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Summary:Graphs provide a natural data representation for analyzing the relationships among entities in many application areas. Since the analysis algorithms perform memory intensive operations, it is important that the graph layout is adapted to take advantage of the memory hierarchy. Here, we propose layout strategies based on community detection to improve the in-memory data locality of generic graph algorithms. We conclude that the detection of communities in a graph provides a layout strategy that improves the performance of graph algorithms consistently over other state of the art strategies.
Bibliography:The members of DAMA-UPC thank the Ministry of Science and Innovation of Spain and Generalitat de Catalunya, for grant numbers TIN2009-14560-C03-03 and GRC-1087 respectively.
ISBN:9783642201486
3642201482
ISSN:0302-9743
1611-3349
DOI:10.1007/978-3-642-20149-3_40