提出了一种适用于波分复用光网络的模糊最小相对容量损失路由模型及算法。该算法能够基于不完全的网络状态信息作出路由判断,从而减少对整个网络状态信息的需求。在此算法中,我们提出了层状态信息处理规则和模糊化的网络状态信息模型,使得该路由算法具有一定的动态资源预测的能力,并深入探讨了模糊最小相对容量损失的路由选择及性能优化原则。通过仿真试验表明,我们提出的基于层状态信息处理规则的模糊最小相对容量损失路由算法的性能与基于全网状态信息下的耗尽算法EA(exhaustive algorithm)和最小阻塞算法LCP(1east-congested-path)非常接近。当网络负载较重时,在单位信息量下的网络阻塞性能要优于EA和LCP路由。这说明与其他己知算法相比,模糊最小相对容量损失路由算法更适用于不完全状态信息下的负载较重的网络路由。
To keep the state information of the network up-to-date,we describe a fuzzy relative capacity lose(FRCL) routing algorithm based on hierarchical information. Simulation shows that the blocking probability using FRCL is very near to that by using the least-congested path routing(LCP) algorithm based on global information. Under heavy traffic load,the FRCL algorithm is superior to the exhaustive algorithm(EA) and the LCP algorithm with unit information cost. Thus,the FRCL algorithm provides better routing when based on incomplete information, particularly under heavy traffic load.