iTri: Index-based triangle listing in massive graphs

Triangle listing is a basic operator when dealing with many graph problems. However, in-memory algorithms do not work well with recently developed massive graphs such as social networks because these graphs cannot be accommodated in the memory. Thus, external memory-based algorithms have been propos...

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Veröffentlicht in:Information sciences Jg. 336; S. 1 - 20
Hauptverfasser: Rasel, Mostofa Kamal, Han, Yongkoo, Kim, Jinseung, Park, Kisung, Tu, Nguyen Anh, Lee, Young-Koo
Format: Journal Article
Sprache:Englisch
Veröffentlicht: Elsevier Inc 01.04.2016
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ISSN:0020-0255, 1872-6291
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Abstract Triangle listing is a basic operator when dealing with many graph problems. However, in-memory algorithms do not work well with recently developed massive graphs such as social networks because these graphs cannot be accommodated in the memory. Thus, external memory-based algorithms have been proposed recently, but these approaches still require frequent multiple scans of the whole graph on the disk and large volumes of calculations are performed that involve the whole graph during every iteration. In this study, we propose a novel index-based method for listing triangles in massive graphs. First, we present new notions for the vertex range index and potential cone vertex index. Next, we propose an index join-based triangle listing algorithm. Our method accesses the indexed data asynchronously and joins them to list triangles using a multi-threaded parallel processing technique. Based on experiments, we demonstrate that our algorithm outperforms the state-of-the-art solution methods by three to eight times in terms of the wall clock time.
AbstractList Triangle listing is a basic operator when dealing with many graph problems. However, in-memory algorithms do not work well with recently developed massive graphs such as social networks because these graphs cannot be accommodated in the memory. Thus, external memory-based algorithms have been proposed recently, but these approaches still require frequent multiple scans of the whole graph on the disk and large volumes of calculations are performed that involve the whole graph during every iteration. In this study, we propose a novel index-based method for listing triangles in massive graphs. First, we present new notions for the vertex range index and potential cone vertex index. Next, we propose an index join-based triangle listing algorithm. Our method accesses the indexed data asynchronously and joins them to list triangles using a multi-threaded parallel processing technique. Based on experiments, we demonstrate that our algorithm outperforms the state-of-the-art solution methods by three to eight times in terms of the wall clock time.
Author Park, Kisung
Rasel, Mostofa Kamal
Han, Yongkoo
Kim, Jinseung
Tu, Nguyen Anh
Lee, Young-Koo
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Keywords Graph indexing
CPU parallelism
Triangle listing
I/O-efficient algorithm
Graph mining
Language English
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Snippet Triangle listing is a basic operator when dealing with many graph problems. However, in-memory algorithms do not work well with recently developed massive...
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SubjectTerms Algorithms
Clocks
CPU parallelism
Graph indexing
Graph mining
Graphs
I/O-efficient algorithm
Mathematical analysis
Social networks
State of the art
Triangle listing
Triangles
Walls
Title iTri: Index-based triangle listing in massive graphs
URI https://dx.doi.org/10.1016/j.ins.2015.12.006
https://www.proquest.com/docview/1786154817
Volume 336
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