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Asymptotically optimal randomized tree embedding in static networks

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1 Author(s)
Keqin Li ; Dept. of Math. & Comput. Sci., State Univ. of New York, New Paltz, NY, USA

The problem of dynamic tree embedding in static networks is studied. The authors provide a unified framework for studying the performance of randomized tree embedding algorithms which allow a newly created tree node to take a random walk of a short distance to reach a processor nearby. In particular, they propose simple randomized algorithms on several most common and important static networks, including d-dimensional meshes, d-dimensional tori, and hypercubes. It is shown that these algorithms, which have a small constant dilation, are asymptotically optimal. The analysis technique is based on random walks on static networks. Hence, analytical expressions for expected load on all the processors are available

Published in:

Parallel Processing Symposium, 1998. IPPS/SPDP 1998. Proceedings of the First Merged International ... and Symposium on Parallel and Distributed Processing 1998

Date of Conference:

30 Mar-3 Apr 1998