采用神经网络和屏蔽遗传算法为VP网络动态分配带宽的方法

BANDWIDTH ALLOCATION OF VIRTUAL PATHS USING NEURAL NETWORKS AND MASKED GENETIC ALGORITHS

虚路径 (VP)的概念已成为宽带网络中的关键技术 .提出采用神经网络与屏蔽遗传算法的一种控制算法 ,来为宽带网络的虚路径分配带宽 .该算法能根据各类业务流的到达与服务特性和网络环境 ,采用神经网络来估计VP子网的利用率、并应用遗传算法来自适应地为各 V P子网分配最佳带宽 .由于它是一个带约束的优化问题 ,传统的遗传算法对它不再适用 .作者提出应用屏蔽遗传算法来解决该优化问题 .仿真结果表明了这种动态分配方法的优越性 .

The concept of virtual paths has become the key technology in the band networks. In this paper, a control scheme using neural networks(NN) and masked genetic algorithms(MGA) is proposed and applied to the virtual paths in the band networks. The proposed scheme is capable of estimating utilization of the virtual path's network and selecting adaptively optimal bandwidths of the virtual paths using masked genetic algorithms according to the multirate's traffic characteristics and network environment. As the optimization problem is constrained, traditional genetic algorithms are no longer applicable to this problem. The authors propose the masked genetic algorithms to solve the optimization problem. Simulation results demonstrate the superiority of this kind of dynamic allocation.