IoT Computing Collaboration and Data-Aware Routing Algorithm for Edge Computing and DL

Author:

Li Bo1ORCID,Tang JinHong2ORCID,Yang Zhihe1ORCID,Jiang Qing3ORCID,Wei Jingyang4ORCID

Affiliation:

1. School of Electronic Infomation Engineering, ShangHai DianJi University, ShangHai 200240, P. R. China

2. JiangXi Industry Polytechnic College, Nanchang 330096, P. R. China

3. Faculty of Electronic and Information Engineering, West Anhui University, Lu’an 237012, P. R. China

4. Jiangxi Siyuan Technology Co., Ltd., NanChang 330000, P. R. China

Abstract

With the development of mobile edge computing and neural network Deep Learning (DL), more and more scholars are studying the combination of the two. This paper mainly studies the application of mobile edge computing and neural network DL in IoT computing collaboration and data-aware routing algorithms. Therefore, this paper proposes the deployment options of MEC technology and ETSIMEC in mobile edge computing, combining mobile edge computing with DL, designs an optimization algorithm based on Markov decision process and feature expression learning, and then analyzes and optimizes IoT computing and VANET routing algorithm. In order to have a clearer direction for the optimization algorithm, this paper also designs the edge computing model training and experiment comparison, the DL algorithm comparison experiment, and the routing algorithm simulation experiment and performance analysis. Combined with the experimental results, it is optimized and compared with traditional IoT computing and routing algorithms. Finally, it is concluded that the computing efficiency of IoT computing based on edge computing and DL designed in this paper is 21.33% higher than that of traditional IoT computing. The efficiency of the routing algorithm based on edge computing and DL designed in this paper is 9.29% higher than that of the traditional routing algorithm.

Publisher

World Scientific Pub Co Pte Ltd

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