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  Efficient computation of implicit representations of sparse graphs (revised version)

Arikati, S. R., Maheshwari, A., & Zaroliagis, C.(1995). Efficient computation of implicit representations of sparse graphs (revised version) (MPI-I-1995-1-013). Saarbrücken: Max-Planck-Institut für Informatik.

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MPI-I-95-1-013.pdf (Any fulltext), 209KB
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Arikati, Srinivasa R.1, Author           
Maheshwari, Anil1, Author           
Zaroliagis, Christos1, Author           
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1Algorithms and Complexity, MPI for Informatics, Max Planck Society, ou_24019              

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 Abstract: The problem of finding an implicit representation for a graph such that vertex adjacency can be tested quickly is fundamental to all graph algorithms. In particular, it is possible to represent sparse graphs on $n$ vertices using $O(n)$ space such that vertex adjacency is tested in $O(1)$ time. We show here how to construct such a representation efficiently by providing simple and optimal algorithms, both in a sequential and a parallel setting. Our sequential algorithm runs in $O(n)$ time. The parallel algorithm runs in $O(\log n)$ time using $O(n/{\log n})$ CRCW PRAM processors, or in $O(\log n\log^*n)$ time using $O(n/\log n\log^*n)$ EREW PRAM processors. Previous results for this problem are based on matroid partitioning and thus have a high complexity.

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Language(s): eng - English
 Dates: 1995
 Publication Status: Issued
 Pages: 16 p.
 Publishing info: Saarbrücken : Max-Planck-Institut für Informatik
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 Identifiers: URI: http://domino.mpi-inf.mpg.de/internet/reports.nsf/NumberView/1995-1-013
Report Nr.: MPI-I-1995-1-013
BibTex Citekey: ArikatiMaheshwariZaroliagis95
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Title: Research Report / Max-Planck-Institut für Informatik
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