DocumentCode :
3410456
Title :
Cloud-based Connected Component Algorithm
Author :
Wu, Bin ; Du, YaHong
Author_Institution :
Sch. of Comput. Sci., Beijing Univ. of Posts & Telecommun., Beijing, China
Volume :
3
fYear :
2010
fDate :
23-24 Oct. 2010
Firstpage :
122
Lastpage :
126
Abstract :
The connected component of an undirected graph plays an important part in graph theory. It is straightforward to compute the connected components of a graph in linear time using either breadth-first search or depth-first search. However when confronted with large scale data, both of the two algorithms are hard to execute. In this paper, we introduce a recently proposed community detection technique by label propagation discussed. And based on the label propagation algorithm (LPA), we propose a method to compute the connected components of an undirected graph. The method is on top of cluster system with the help of MapReduce, and implemented to fully utilize MapReduce execution mechanism, namely the “map-reduce” process. Moreover, considering how our algorithm can be applied in further “cloud” service, we employ several large scale datasets to demonstrate the efficiency and scalability of our solutions.
Keywords :
Internet; data mining; graph theory; tree searching; MapReduce; breadth first search; cloud based connected component algorithm; cluster system; community detection technique; depth first search; graph theory; label propagation algorithm; large scale dataset; undirected graph; Algorithm design and analysis; Clouds; Clustering algorithms; Communities; Computer science; Data mining; Runtime; LPA; MapReduce; connected component; graph mining;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Artificial Intelligence and Computational Intelligence (AICI), 2010 International Conference on
Conference_Location :
Sanya
Print_ISBN :
978-1-4244-8432-4
Type :
conf
DOI :
10.1109/AICI.2010.360
Filename :
5656247
Link To Document :
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