When quoting this document, please refer to the following
DOI: 10.4230/DagSemProc.09491.2
URN: urn:nbn:de:0030-drops-24334
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Zhou, Rong ; Hansen, Eric A.

Dynamic State-Space Partitioning in External-Memory Graph Search

09491.ZhouRong.Paper.2433.pdf (0.09 MB)


State-of-the-art external-memory graph search algorithms rely on a hash
function, or equivalently, a state-space projection function, that partitions
the stored nodes of the state-space search graph into groups of nodes that are stored as separate files on disk. The scalability and efficiency of the search depends on properties of the partition: whether the number of unique nodes in a file always fits in RAM, the number of files into which the nodes of the state-space graph are partitioned, and how well the partitioning of the state space captures local structure in the graph. All previous work relies on a static partitioning of the state space. In this paper, we introduce a method for dynamic partitioning of the state-space search graph and show that it leads to substantial improvement of search performance.

BibTeX - Entry

  author =	{Zhou, Rong and Hansen, Eric A.},
  title =	{{Dynamic State-Space Partitioning in External-Memory Graph Search}},
  booktitle =	{Graph Search Engineering},
  pages =	{1--7},
  series =	{Dagstuhl Seminar Proceedings (DagSemProc)},
  ISSN =	{1862-4405},
  year =	{2010},
  volume =	{9491},
  editor =	{Lubos Brim and Stefan Edelkamp and Erik A. Hansen and Peter Sanders},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{},
  URN =		{urn:nbn:de:0030-drops-24334},
  doi =		{10.4230/DagSemProc.09491.2},
  annote =	{Keywords: External-memory graph search, heuristic search}

Keywords: External-memory graph search, heuristic search
Collection: 09491 - Graph Search Engineering
Issue Date: 2010
Date of publication: 02.03.2010

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