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


연구 분야: Artificial Intelligence



학회: 2024 4th International Conference on Neural Networks, Information and Communication Engineering (NNICE)


초록

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.


Author Profile
Yue Liu

Key Laboratory of Trustworthy Distributed Computing and Service Beijing University of Posts and Telecommunications Beijing China

Andorra
Author Profile
Xiaoyong Li

Key Laboratory of Trustworthy Distributed Computing and Service Beijing University of Posts and Telecommunications Beijing China

Andorra
Author Profile
Xiaotian Si

Key Laboratory of Trustworthy Distributed Computing and Service Beijing University of Posts and Telecommunications Beijing China

Andorra

📄 논문 정보

발행 연도 2024년
인용수 120
출판 국가 Andorra
사이트 IEEE
좋아요 수 0

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