DocumentCode
695485
Title
Triangle counting in networks using a multi-level branching technique
Author
Jungeun Kim ; Minseo Kang ; Sungsu Lim ; Jae-Gil Lee
Author_Institution
Dept. of Knowledge Service Eng., KAIST, Daejeon, South Korea
fYear
2015
fDate
9-11 Feb. 2015
Firstpage
47
Lastpage
50
Abstract
Counting triangles in networks is a fundamental problem in network science. In addition, because we are forced to manage very large real-world networks, current triangle counting algorithms naturally require a distributed computing system. In this paper, we propose a distributed triangle counting algorithm based on both the vertex-centric and node-iterator models and using the multi-level branching technique. Multi-level branching is a method that constructs an ordered graph structure based on levels. This method not only facilitates an efficient triangle counting process, but also guarantees the computational integrity of each split in the distributed triangle counting process. First, we describe a level-based triangle counting algorithm based on both the vertex-centric model and the node-iterator algorithm. Then, we develop a distributed implementation of the proposed algorithm using GraphChi. The main advantages of the proposed algorithm are that the execution is simple yet effective, and thus its parallelization is efficient. Experiments on real-world networks verify its performance, particularly, its near-linear parallelization scalability.
Keywords
distributed algorithms; graph theory; network theory (graphs); GraphChi; computational integrity; distributed implementation; distributed triangle counting algorithm; level-based triangle counting algorithm; multilevel branching technique; near-linear parallelization scalability; network science; node-iterator models; ordered graph structure; performance verification; real-world networks; vertex-centric models; very-large real-world network management; Approximation algorithms; Approximation methods; Communities; Computational modeling; Level set; Parallel algorithms; Scalability; large-scale networks; multi-level branching; parallelization; triangle counting;
fLanguage
English
Publisher
ieee
Conference_Titel
Big Data and Smart Computing (BigComp), 2015 International Conference on
Conference_Location
Jeju
Type
conf
DOI
10.1109/35021BIGCOMP.2015.7072849
Filename
7072849
Link To Document