Applying Hopfield neural network to QoS routing in communication network |
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Authors: | Li Wang Jin-yuan Shen Sheng-jiang Chang and Yan-xin Zhang |
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Affiliation: | (1) College of Information Engineering, Zhengzhou University, 450052 Zhengzhou, P. R. China;(2) Institute of Modern Optics, Nankai University, 300071 Tianjin, P. R. China |
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Abstract: | The main goal of routing solutions is to satisfy the requirements of the Quality of Service (QoS) for every admitted connection
as well as to achieve a global efficiency in resource utilization. In this paper proposes a solution based on Hopfield neural
network (HNN) to deal with one of representative routing problems in uni-cast routing, i. e. the multi-constrained (MC) routing
problem. Computer simulation shows that we can obtain the optimal path very rapidly with our new Lyapunov energy functions.
This work is supported by National Natural Science Foundation of China (No. 60277022), Outstanding Youth Foundation of Henan
Province, Natural Science Foundation of Tianjin (No. 023800811), the Research Fund for the Doctoral Program of Higher education
(No.20030055022). The Project-sponsored by SRF for ROCS, SEM. |
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Keywords: | CLC number" target="_blank">CLC number TN929 14 |
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