A Tensor Based Deep Learning Technique for Intelligent Packet Routing

Bomin Mao, Zubair Md Fadlullah, Fengxiao Tang, Nei Kato, Osamu Akashi, Takeru Inoue, Kimihiro Mizutani

Research output: Chapter in Book/Report/Conference proceedingConference contribution

16 Citations (Scopus)

Abstract

Recently, network operators are confronting the challenge of exploding traffic and more complex network environments due to the increasing number of access terminals having various requirements for delay and package loss rate. However, traditional routing methods based on the maximum or minimum single metric value aim at improving the network quality of only one aspect, which makes them become incapable to deal with the increasingly complicated network traffic. Considering the improvement of deep learning techniques in recent years, in this paper, we propose a smart packet routing strategy with Tensor-based Deep Belief Architectures (TDBAs) that considers multiple parameters of network traffic. For better modeling the data in TDBAs, we use the tensors to represent the units in every layer as well as the weights and biases. The proposed TDBAs can be trained to predict the whole paths for every edge router. Simulation results demonstrate that our proposal outperforms the conventional Open Shortest Path First (OSPF) protocol in terms of overall packet loss rate and average delay per hop.

Original languageEnglish
Title of host publication2017 IEEE Global Communications Conference, GLOBECOM 2017 - Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages1-6
Number of pages6
ISBN (Electronic)9781509050192
DOIs
Publication statusPublished - 2017 Jul 1
Event2017 IEEE Global Communications Conference, GLOBECOM 2017 - Singapore, Singapore
Duration: 2017 Dec 42017 Dec 8

Publication series

Name2017 IEEE Global Communications Conference, GLOBECOM 2017 - Proceedings
Volume2018-January

Other

Other2017 IEEE Global Communications Conference, GLOBECOM 2017
CountrySingapore
CitySingapore
Period17/12/417/12/8

ASJC Scopus subject areas

  • Computer Networks and Communications
  • Hardware and Architecture
  • Safety, Risk, Reliability and Quality

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  • Cite this

    Mao, B., Fadlullah, Z. M., Tang, F., Kato, N., Akashi, O., Inoue, T., & Mizutani, K. (2017). A Tensor Based Deep Learning Technique for Intelligent Packet Routing. In 2017 IEEE Global Communications Conference, GLOBECOM 2017 - Proceedings (pp. 1-6). (2017 IEEE Global Communications Conference, GLOBECOM 2017 - Proceedings; Vol. 2018-January). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/GLOCOM.2017.8254036