Title: Multi-channel scheduling analysis of dynamic data in wireless networks oriented big data

Authors: Jin-Jun Ruan

Addresses: Department of Electronics and Information Engineering, Anhui Business College of Vocational Technology, WuHu 241002, China

Abstract: In order to reduce the running time of dynamic data multi-channel scheduling in wireless networks, a multi-channel scheduling analysis method based on partially observable Markov decision process (POMDP) for dynamic data of wireless networks is proposed. Firstly, the data type and dynamic data transmission process in wireless network are analysed. According to the node's request arrival rate and service rate, the network state transition probability and observation probability are calculated. Load balancing is used as the performance optimisation target of dynamic data multi-channel in wireless network, calculate its performance function. By calculating the observation probability and performance function, the dynamic data multi-channel scheduling analysis for big data wireless networks is finally realised. The experimental results show that the proposed method has high data transmission efficiency and low packet loss rate, and the scheduling operation time is relatively short. The effectiveness of the proposed method is verified.

Keywords: big data; wireless network; dynamic data; multi-channel; scheduling.

DOI: 10.1504/IJIPT.2020.110306

International Journal of Internet Protocol Technology, 2020 Vol.13 No.4, pp.193 - 201

Received: 29 Nov 2018
Accepted: 23 Mar 2019
Published online: 14 Oct 2020 *

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