Distributed and Parallel Algorithm for Computing Betweenness Centrality

  • Mirlayne Campuzano-AlvarezEmail author
  • Adrian Fonseca-Bruzón
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10022)


Today, online social networks have millions of users, and continue growing up. For that reason, the graphs generated from these networks usually do not fit into a single machine’s memory and the time required for its processing is very large. In particular, to compute a centrality measure like betweenness could be expensive on those graphs. To address this challenge, in this paper we present a parallel and distributed algorithm to compute betweenness. Also, we develop a heuristic to reduce the overall time, which accomplish a speedup over 80x in the best of cases.


Online social network Betweenness MPI Distributed computing 


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Copyright information

© Springer International Publishing AG 2016

Authors and Affiliations

  • Mirlayne Campuzano-Alvarez
    • 1
    Email author
  • Adrian Fonseca-Bruzón
    • 1
  1. 1.Center for Pattern Recognition and Data MiningSantiago de CubaCuba

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