基于并行BP神经网络的路由查找算法

摘要

结合Bloom-filter算法和并行反向传播神经网络,提出了一种新的基于并行神经网络的路由查找算法(BFBP).该算法满足路由查找的需求,只需学习路由条目的网络ID,且易于扩展到IPv6地址查询.研究结果表明,相比于已有的神经网络路由查找方法,该算法需要学习的条目数平均减少了520倍,提高了学习效率,为神经网络应用于路由查找创造了有利条件.%A new routing lookup algorithm based on Bloom-filter algorithm and parallel back-propagation neural networks (BFBP) was proposed. The algorithm could meet the challenges of routing lookup and just had to learn the network ID moreover, it was equally attractive for IPv6. The results show that compared to other routing lookup methods based on neural network, BFBP algorithm reduces the average number of items which neural network has to learn by 520 times, improves learning efficiency of neural networks, and creates favorable conditions for the application of neural network in the area of routing lookup.