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Performance Evaluation
Volume 60, Issues 1-4, May 2005, Pages 141-163
Performance Modeling and Evaluation of High-Performance Parallel and Distributed Systems
 
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doi:10.1016/j.peva.2004.10.014    
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Copyright © 2004 Elsevier B.V. All rights reserved.

Design and analysis of asymptotically optimal randomized tree embedding algorithms in static networks

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Keqin LiCorresponding Author Contact Information, E-mail The Corresponding Author

Department of Computer Science, State University of New York, New Paltz, New York 12561, USA


Available online 7 December 2004.

Abstract

The problem of dynamic tree embedding in static networks is studied in this paper. We 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 short distance to reach a processor nearby. In particular, we 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 small constant dilation, are asymptotically optimal for embedding healthy trees. Our analysis technique is based on random walks on static networks. Hence, analytical expressions for expected load on all the processors are available.

Keywords: Asymptotic performance; Dynamic load distribution; Hypercube; Mesh; Randomized tree embedding; Static network; Torus

Article Outline

1. Introduction
2. Randomized tree embedding algorithms
3. Random walks
4. Asymptotic optimality
5. Linear arrays
6. Meshes
7. d-Dimensional meshes
8. d-dimensional tori
9. Hypercubes
10. Dilation-View the MathML source embedding
11. Final remarks
Acknowledgements
References
Vitae








Corresponding Author Contact InformationTel.: +1 845 257 3534; fax: +1 845 257 3996.

Performance Evaluation
Volume 60, Issues 1-4, May 2005, Pages 141-163
Performance Modeling and Evaluation of High-Performance Parallel and Distributed Systems
 
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