• 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