Asymptotically optimal probabilistic embedding algorithms for supporting tree structured computations in hypercubes

Asymptotically optimal probabilistic embedding algorithms for supporting tree structured computations in hypercubes

We show two asymptotically optimal probabilistic tree embedding algorithms in hypercubes with constant dilation. These algorithms are slight extension of the random walk algorithm. The first algorithm allows a tree node to have a stay option during each step of a random walk. The second algorithm pe...

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Hauptverfasser: Keqin Li, Dorband, J.E.
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Sprache:eng
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Computer science
Concurrent computing
Embedded computing
Heuristic algorithms
HTML
Hypercubes
Mathematics
NASA
Uniform resource locators
World Wide Web
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Dorband, J.E.
description We show two asymptotically optimal probabilistic tree embedding algorithms in hypercubes with constant dilation. These algorithms are slight extension of the random walk algorithm. The first algorithm allows a tree node to have a stay option during each step of a random walk. The second algorithm permits varying length of random walks. Numerical data are given to demonstrate performance improvement.
doi_str_mv 10.1109/FMPC.1999.750603
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subjects Computer science
Concurrent computing
Embedded computing
Heuristic algorithms
HTML
Hypercubes
Mathematics
NASA
Uniform resource locators
World Wide Web
title Asymptotically optimal probabilistic embedding algorithms for supporting tree structured computations in hypercubes
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