VoIP talk time modeling and prediction on output link of metro area network

doi:10.3778/j.issn.1002-8331.2009.15.032

Computer Engineering and Applications ›› 2009, Vol. 45 ›› Issue (15): 111-114.DOI: 10.3778/j.issn.1002-8331.2009.15.032

• 网络、通信、安全 • Previous Articles Next Articles

VoIP talk time modeling and prediction on output link of metro area network

CHEN Nan-nan¹,YUAN Xiao-fang^1,2,WANG Dong¹,XIE Gao-gang²,HUANG Jin-chai¹

1.College of Computer and Communication，Hunan University，Changsha 410082，China
2.Institute of Computing Technology，Chinese Academy of Sciences，Beijing 100080，China

Received:2008-03-26 Revised:2008-06-02 Online:2009-05-21 Published:2009-05-21
Contact: CHEN Nan-nan

城域网出口链路VoIP通话时长的建模与预测

陈楠楠¹,袁小坊^1,2,王东¹,谢高岗²,黄金钗¹

1.湖南大学计算机与通信学院，长沙 410082
2.中国科学院计算技术研究所下一代互联网研究中心，北京 100080

通讯作者: 陈楠楠

Abstract

Abstract: IP-based voice packet transmission（VoIP） telephone services are currently being deployed nationwide in MANs.By using VoIP comprehensive statistical data collected with NetTurbo on an ISP WAN link，this paper establishes a model of multiple seasonal autoregressive integrated moving average（ARIMA）（2，1，2）×（2，1，2） 24，and predicts the VoIP talk time on output link of this MAN.Experimentation shows that the average relative error of the model is 8.38%.And using this model to detect the possible time when the VoIP traffic is beyond the threshold，this paper can pre-take measures to ensure the QoS of VoIP.

Key words: metro area network, VoIP talk time, multiple seasonal ARIMA model, prediction, alert

摘要： 基于IP技术的语音分组传输（VoIP）电话业务目前被广泛部署于全国范围内的城域网。通过对某城域出口链路上实际采集的VoIP综合统计数据，针对有季节变动规律的单因素时间序列，推导建立了ARIMA（2，1，2）×（2，1，2）24季节乘积模型，并以此作为预测的基础，进行了该链路VoIP通话时长的预测。实验表明，模型的预测平均误差为8．38%。应用该模型检测将来超越阀值的可能发生时间，可以预先采取措施，保证VoIP的服务质量。

关键词: 城域网, VoIP通话时长, ARIMA季节乘积模型, 预测, 告警

CHEN Nan-nan¹,YUAN Xiao-fang^1,2,WANG Dong¹,XIE Gao-gang²,HUANG Jin-chai¹. VoIP talk time modeling and prediction on output link of metro area network[J]. Computer Engineering and Applications, 2009, 45(15): 111-114.

陈楠楠¹,袁小坊^1,2,王东¹,谢高岗²,黄金钗¹. 城域网出口链路VoIP通话时长的建模与预测[J]. 计算机工程与应用, 2009, 45(15): 111-114.

[1]	HUANG Dongyi, YANG Bing, WU Zihao, KUANG Jiayi, YAN Zeming. Spatio-Temporal Fully Connected Convolutional Neural Networks for Citywide Cellular Prediction [J]. Computer Engineering and Applications, 2021, 57(9): 168-175.
[2]	YANG Li, WU Yi, WEI Debin, PAN Chengsheng. Satellite Network Traffic Prediction Based on Spatiotemporal Correlation [J]. Computer Engineering and Applications, 2021, 57(7): 101-106.
[3]	CHANG Hao, CHEN Xiaolei, ZHANG Aihua, LI Ce, LIN Dongmei. Continuous Blood Pressure Prediction Based on Improved SENet Convolutional Neural Network [J]. Computer Engineering and Applications, 2021, 57(7): 130-135.
[4]	LIU Ziyan, YUAN Lei, ZHU Mingcheng, MA Shanshan, CHEN Linzhouting. YOLOv3 Traffic sign Detection based on SPP and Improved FPN [J]. Computer Engineering and Applications, 2021, 57(7): 164-170.
[5]	ZHANG Rui, WU Boxiong, ZHANG Liyuan, ZHANG Bo. Human Trajectory Prediction Method for Complex Scenes [J]. Computer Engineering and Applications, 2021, 57(6): 138-143.
[6]	YANG Fengyu, HUANG Yaxuan, ZHOU Shijian, ZHENG Wei. Survey of Software Defect Prediction Combined with Multi-metrics [J]. Computer Engineering and Applications, 2021, 57(5): 10-24.
[7]	LI Shuo, LIANG Yi. Prediction Model of Execution Time for Batch Application in Spark [J]. Computer Engineering and Applications, 2021, 57(5): 79-87.
[8]	XU Xianfeng, CAI Lulu, ZHANG Li. Photovoltaic Power Generation Prediction Algorithm Based on MLP and DBN [J]. Computer Engineering and Applications, 2021, 57(3): 266-272.
[9]	ZHENG Jianfeng, WANG Yingming. Research on Efficiency Confidence Interval Prediction Model Based on DEA-BP Neural Network [J]. Computer Engineering and Applications, 2021, 57(3): 273-278.
[10]	AN Weichao, YAN Ting, ZHANG Nan, ZHANG Shan, XIANG Jie, CAO Rui, WANG Bin. Application of Pathological Image Texture Analysis in MSI Prediction of Gastric Cancer [J]. Computer Engineering and Applications, 2021, 57(24): 205-211.
[11]	CHEN Hai, QIAN Fulan, CHEN Jie, ZHAO Shu, ZHANG Yanping. Rating Prediction Model Based on Variational Auto-Encoder [J]. Computer Engineering and Applications, 2021, 57(22): 153-159.
[12]	YI Lingzhi, WANG Shitong, YI Fang, DENG Dong, YI Zhimin, JIANG Peng. Wind Farm Ultra-Short-Term Wind Speed Prediction Based on EEMDSE-ILSTM [J]. Computer Engineering and Applications, 2021, 57(22): 288-294.
[13]	WU Minghui, HOU Lingyan, WANG Chao. Improved Mechanism of Prediction-Oriented Long Short-Term Memory Neural Network [J]. Computer Engineering and Applications, 2021, 57(21): 109-115.
[14]	ZHAO Yu, ZHU Yi, YU Qiao, CHEN Xiaoying. Cross Project Defect Prediction Method Based on Hierarchical Data Screening [J]. Computer Engineering and Applications, 2021, 57(20): 279-286.
[15]	ZHANG Xueting, CHENG Hua, FANG Yiquan. Prediction of Co-authorship Based on Meta-Path and Node Attributes [J]. Computer Engineering and Applications, 2021, 57(2): 164-169.

VoIP talk time modeling and prediction on output link of metro area network

城域网出口链路VoIP通话时长的建模与预测

PDF

Knowledge

Abstract

Cite this article

share this article

References

Related Articles 15

Recommended Articles

Metrics