Exact Convergence of a Parallel Textured Algorithm for Data Network Optimal Routing Problems

Garng Morton Huang, Wen Lin Hsieh

Research output: Contribution to journalArticle

3 Citations (Scopus)

Abstract

In our earlier paper , a textured decomposition based algorithm is developed to solve the optimal routing problem in data networks; a few examples were used to illustrate the speedup advantage and the convergence conditions for the textured algorithm to converge to a global minimum. The speedup advantage is investigated in . However, the theoretical foundation is not provided. In this paper, we provide the foundation. First, we show that for any textured decomposition, the algorithm always converges to a stationary point, which may not be a global minimum. And then, we prove that if the conditions of the exact convergence theorem are satisfied, the textured algorithm will converge to a global minimum.

Original language English 1132-1146 15 IEEE Transactions on Parallel and Distributed Systems 6 11 https://doi.org/10.1109/71.476185 Published - 1 Jan 1995 Yes

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Parallel algorithms
Decomposition

Keywords

• Exact convergence
• Kuhn-Tucker theorem
• optimal routing
• parallel processing
• textured algorithm

ASJC Scopus subject areas

• Signal Processing
• Hardware and Architecture
• Computational Theory and Mathematics

Cite this

In: IEEE Transactions on Parallel and Distributed Systems, Vol. 6, No. 11, 01.01.1995, p. 1132-1146.

Research output: Contribution to journalArticle

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