Solving the Delay Constrained Multicast Routing Problem Using the Transiently Chaotic Neural Network

Authors:
Wen Liu;Lipo Wang
Affiliations:
College of Information Engineering, Xiangtan University, Xiangtan, Hunan, China, School of Electrical and Electronic Engineering, Nanyang Technology University, Block S1, 50 Nanyang Avenue, 639798 ...;College of Information Engineering, Xiangtan University, Xiangtan, Hunan, China, School of Electrical and Electronic Engineering, Nanyang Technology University, Block S1, 50 Nanyang Avenue, 639798 ...
Venue:
ISNN '07 Proceedings of the 4th international symposium on Neural Networks: Part II--Advances in Neural Networks
Year:
2007

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Abstract

Delay constrained multicast routing (DCMR) aims to construct a minimum-cost tree with end-to-end delay constraints. This routing problem is becoming more and more important to multimedia applications which are delay-sensitive and require real time communications. We solve the DCMR problem by the transiently chaotic neural network (TCNN) of Chen and Aihara. Simulation results show that the TCNN is more capable of reaching global optima compared with the Hopfield neural network (HNN).