A Neural Network and Bloom Filter-Based Name Search Method in Named Data Networking

Abstract

In a new network architecture like NDN, designing an efficient name lookup method has always been a valuable challenge. The paper studies the name lookup technology based on the Bloom filter and BPNN neural network mapping model in named data networking. In the part of the hybrid model based on the Bloom filter and BPNN, the paper proposes the fusion idea of the Bloom filter and BPNN, and provides a detailed introduction to the construction process of the hybrid model. At the same time, in order to improve the memory utilization of traditional Bloom filters, this article proposes a way to use neural networks to enhance it, and proved its effectiveness through experiments.