Chaotic dynamics for avoiding congestion in the computer network

Authors:
Takayuki Kimura;Tohru Ikeguchi
Affiliations:
Graduate school of Science and Engineering, Saitama University, Saitama, Japan;Graduate school of Science and Engineering, Saitama University, Saitama, Japan
Venue:
IDEAL'06 Proceedings of the 7th international conference on Intelligent Data Engineering and Automated Learning
Year:
2006

Citing 2
Cited 1

Data networks

Data networks
Solving large scale traveling salesman problems by chaotic neurodynamics

Neural Networks

An optimum strategy for dynamic and stochastic packet routing problems by chaotic neurodynamics

Integrated Computer-Aided Engineering - Artificial Neural Networks

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Abstract

We proposed a new algorithm for packet routing problems using chaotic neurodynamics and analyze its statistical behavior. First, we construct a basic neural network which works in the same way as the Dijkstra algorithm that uses information of shortest path lengths from a node to another node in a computer network. When the computer network has a regular topology, the basic routing method works well. However, when the computer network has an irregular topology, it fails to work, because most of packets cannot be transmitted to their destinations due to packet congestion in the computer network. To avoid such an undesirable problem, we extended the basic neural network to employ chaotic neurodynamics. We confirm that our proposed method exhibits good performance for complex networks, such as scale-free networks.