Cavalieri S, Di Stefano A, Mirabella O
Istituto di Informatica e Telecommunicazioni, Facolta di Ingegneria, Universita di Catania, Italy.
Int J Neural Syst. 1993 Sep;4(3):269-89. doi: 10.1142/s0129065793000225.
In this paper, the authors adopt a neural approach to deal with the problem of routing in a packet switching network. The aim is to define a routing strategy which will combine the advantages of both the centralized and the distributed approaches. The neural approach presented is based on the idea of inserting a neural network (N/N) into each node in the computer network which will be responsible for computing the route between its node and the immediately adjacent one. Two distributed routing solutions are presented in the paper based on an optimizing network and a mapping network. The routing obtainable and the implementation resources needed for the two approaches are evaluated. Finally, the performance offered by the neural strategies proposed is compared with that offered by classical distributed and centralized routing solutions. As a parameter of merit, the effect of overloading caused by the additional traffic present in each solution is used.
在本文中,作者采用一种神经网络方法来处理分组交换网络中的路由问题。目的是定义一种路由策略,该策略将结合集中式和分布式方法的优点。所提出的神经网络方法基于这样一种思想,即在计算机网络的每个节点中插入一个神经网络(N/N),该神经网络将负责计算其节点与紧邻节点之间的路由。本文基于一个优化网络和一个映射网络提出了两种分布式路由解决方案。评估了这两种方法可获得的路由以及所需的实现资源。最后,将所提出的神经网络策略的性能与经典分布式和集中式路由解决方案的性能进行了比较。作为一个性能指标参数,使用了每种解决方案中由额外流量导致的过载影响。