Title: An equalisation control method for network big data transmission based on parallel computing

Authors: Jiazhong Lu; Xiaosong Zhang; Xiaolei Liu; Teng Hu; Yu Cao

Addresses: Center for Cyber Security, University of Electronic Science and Technology of China, Chengdu 611731, Chin ' Center for Cyber Security, University of Electronic Science and Technology of China, Chengdu 611731, China ' Center for Cyber Security, University of Electronic Science and Technology of China, Chengdu 611731, China ' Center for Cyber Security, University of Electronic Science and Technology of China, Chengdu 611731, China ' Mathematics and Information Technology Institute, Jiangsu Second Normal College, Jiangsu, Nanjing 210000, China

Abstract: In order to solve the problem of high output bit error rate and poor balance of data transmission of network big data, an equalisation control method for network big data transmission based on parallel computing is proposed in this paper. In the method, firstly, the information flow in the network channel model is reconstructed through the coherent correlation detection method, and then the channel impulse response of network is calculated. Secondly, according to the channel impulse response, big data output channels are improved and scheduled through the link sequential allocation method. Finally, frequency multiplication processing is performed to the big data output channels through the frequency domain expansion method, and adaptive equalisation allocation is performed according to the parallel computing conditions for channel output to achieve channel equalisation. A simulation experiment shows that the method proposed in this paper can provide relatively good channel equalisation in network bit data transmission and relatively strong adaptive allocation ability of output parallel computing, which reduces communication bit error rate of network.

Keywords: network; big data; parallel computing; channel; adaptive allocation; bit error rate.

DOI: 10.1504/IJIPT.2020.105051

International Journal of Internet Protocol Technology, 2020 Vol.13 No.1, pp.32 - 38

Received: 31 Dec 2018
Accepted: 27 Feb 2019

Published online: 11 Feb 2020 *

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