License
when quoting this document, please refer to the following
URN: urn:nbn:de:0030-drops-24334
URL: http://drops.dagstuhl.de/opus/volltexte/2010/2433/

Zhou, Rong ; Hansen, Eric A.

Dynamic State-Space Partitioning in External-Memory Graph Search

pdf-format:
Dokument 1.pdf (94 KB)


Abstract

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

@InProceedings{zhou_et_al:DSP:2010:2433,
  author =	{Rong Zhou and Eric A. Hansen},
  title =	{Dynamic State-Space Partitioning in External-Memory Graph Search},
  booktitle =	{Graph Search Engineering},
  year =	{2010},
  editor =	{Lubos Brim and Stefan Edelkamp and Erik A. Hansen and Peter Sanders},
  number =	{09491},
  series =	{Dagstuhl Seminar Proceedings},
  ISSN =	{1862-4405},
  publisher =	{Schloss Dagstuhl - Leibniz-Zentrum fuer Informatik, Germany},
  address =	{Dagstuhl, Germany},
  URL =		{http://drops.dagstuhl.de/opus/volltexte/2010/2433},
  annote =	{Keywords: External-memory graph search, heuristic search}
}

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


DROPS-Home | Fulltext Search | Imprint Published by LZI