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On Trade-Offs in External-Memory Diameter-Approximation

  • Ulrich Meyer
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5124)

Abstract

Computing diameters of huge graphs is a key challenge in complex network analysis. However, since exact diameter computation is computationally too costly, one typically relies on approximations. In fact, already a single BFS run rooted at an arbitrary vertex yields a factor two approximation. Unfortunately, in external-memory, even a simple graph traversal like BFS may cause an unacceptable amount of I/O-operations. Therefore, we investigate alternative approaches with worst-case guarantees on both I/O-complexity and approximation factor.

Keywords

Short Path Span Tree Undirected Graph Input Graph Master Node 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2008

Authors and Affiliations

  • Ulrich Meyer
    • 1
  1. 1.Institute for Computer ScienceJ.W. Goethe UniversityFrankfurt/MainGermany

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