Performance Analysis and Prediction of Double-Server Polling System Based on BP Neural Network

被引：5
|
作者：
YANG Zhijun [1 ,2 ]
MAO Lei [1 ]
GAN Jianhou [3 ]
DING Hongwei [1 ]
机构：
[1] School of Information Science and Technology,Yunnan University
[2] Educational Instruments and Facilities Service Center,Educational Department of Yunnan Province
[3] Key Laboratory of Education Informalization for Nationalities of Ministry of Education,Yunnan Normal University
来源：
Chinese Journal of Electronics | 2020年 / 29卷 / 06期
基金：
中国国家自然科学基金;
关键词：
D O I：
暂无
中图分类号：
TP368.5 [服务器、工作站]; TP183 [人工神经网络与计算];
学科分类号：
081104 ; 0812 ; 081201 ; 0835 ; 1405 ;
摘要：
To solve the poor performance of the single-server polling system in high traffic and the complex analysis of the multi-server polling system,a synchronous double-server polling system is proposed,and its performance is analyzed using a Backpropagation(BP) neural network prediction algorithm.Experimental data are processed and analyzed,and a three-layer multiinput single-output BP network model is constructed to predict the performance of the polling system under different arrival rates of information packets.In the prediction stage,first,the data are processed and the average queue length under different information arrival rates is used to form a sequence.Subsequently,a multiinput single-output BP neural network is constructed for prediction.Experimental results show that the algorithm can accurately predict the performance of the double-server polling system,thereby facilitating research regarding polling systems.
引用
收藏
页码：1046 / 1053
页数：8
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