I/O-efficient Hierarchical Diameter Approximation

  • Deepak Ajwani
  • Ulrich Meyer
  • David Veith
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7501)


Computing diameters of huge graphs is a key challenge in complex network analysis. As long as the graphs fit into main memory, diameters can be efficiently approximated (and frequently even exactly determined) using heuristics that apply a limited number of BFS traversals. If the input graphs have to be kept and processed on external storage, even a single BFS run may cause an unacceptable amount of time-consuming I/O-operations.

Meyer [17] proposed the first parameterized diameter approximation algorithm with fewer I/Os than that required for exact BFS traversal. In this paper we derive hierarchical extensions of this randomized approach and experimentally compare their trade-offs between actually achieved running times and approximation ratios. We show that the hierarchical approach is frequently capable of producing surprisingly good diameter approximations in shorter time than BFS. We also provide theoretical and practical insights into worst-case input classes.


Main Memory Approximation Ratio Input Graph External Memory Graph Class 
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 2012

Authors and Affiliations

  • Deepak Ajwani
    • 1
  • Ulrich Meyer
    • 2
  • David Veith
    • 2
  1. 1.Centre for Unified ComputingUniversity College CorkCorkIreland
  2. 2.Institut für InformatikGoethe-Universität FrankfurtFrankfurt am MainGermany

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