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