北京邮电大学学报

  • EI核心期刊

北京邮电大学学报 ›› 1999, Vol. 22 ›› Issue (2): 16-20.

• 学术论文 • 上一篇    下一篇

状变动态选路的神经网络算法

忻展红, 张海军   

  1. 北京邮电大学管理与人文学院, 北京 100876
  • 收稿日期:1998-07-14 出版日期:1999-03-10

State-Dependent Routing with a Neural Networks Algorithm

Xin Zhanhong, Zhang Haijun   

  1. School of Management and Humanities, Beijing University of Posts and Telecommunications, Beijing 100876
  • Received:1998-07-14 Online:1999-03-10

摘要: 吸收一些电路交换网动态选路算法的优点, 提出了基于神经网络Hopfield模型的状变实时选路算法.该模型全面集成了网管中心监控的话务数据、网路状态和电路保留策略, 在对中继线群阻塞概率短期预测的基础上优化全网动态路由.模型的设计尽量接近实际, 又充分考虑硬件的可实现性.计算机模拟结果表明, 该算法明显优于传统的固定路由选路法, 为神经网络在动态选路中应用提出了一种解决方案.

关键词: 神经网络, 优化算法, 动态选路

Abstract: A state-dependent routing algorithm based on Hopfield's neural networks model is given, which takes advantage of other dynamic routing methods for the circuitswitched network. The model fully integrates the traffic data, network states and circuits reservation policy monitored by the network management center, and optimizes dynamic routes for the whole network on the bases of short period forecasting of trunk congestion probabilities. The design of the model is ascloser to the real world as possible, and also takes the hardware realization into consideration. Computer simulations show that the algorithm is much better than the classical fixed routing methods, therefore the model could be a solutionfor the applications of neural networks to the dynamic routing.

Key words: neural networks, optimization algorithm, dynamic routing

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