A new generalized cellular automata approach to optimization of fast packet switching

Authors:
Dianxun Shuai;Hongbin Zhao
Affiliations:
Department of Computer Science, East China University of Science and Technology, Shanghai 200237, PR China and State Key Laboratory of Intelligence Technology and System, Tsinghua University, Beij ...;Department of Computer Science, East China University of Science and Technology, Shanghai 200237, PR China
Venue:
Computer Networks: The International Journal of Computer and Telecommunications Networking
Year:
2004

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Abstract

The optimization of fast packet switching (FPS) in computer networks is of great significance for improving the network performance. This paper presents a new generalized cellular automata (GCA) approach to effectively solve the FPS optimization problem. In contrast to the Hopfield-type neural network (HNN) and cellular neural network (CNN), the proposed GCA approach is featured by the pyramid architecture that is composed of multigranularity macro-cells, and by the evolutionary dynamics that involves the dynamical feedbacks among macro-cells. The GCA architecture, dynamics, algorithm and properties are discussed in the context of the FPS optimization. The analysis and simulations on the FPS optimization have shown that the GCA approach has advantages over the HNN and CNN methods in terms of the solution quality, optimal ratio, convergence speed, real-time performance, interconnection complexity, and parameter selection.