Using spline-extrapolation in the research of self-similar traffic characteristics

Author:

Strelkovskaya Irina1,Solovskaya Irina2

Affiliation:

1. A.S. Popov Odessa National Academy of Telecommunications , Department of Higher Mathematics

2. Department of Switching Systems , Odessa , Ukraine , Kuznechnaya str.

Abstract

Abstract The problem of predicting self-similar traffic is considered, the solution of which modeling of self-similar traffic was performed using the Simulink software package in MATLAB environment. For the simulation, the queuing system WB/M/1/K with Weibull distribution was used. The use of the spline-extrapolation method made it possible to predict self-similar traffic outside the considered period of time on which packet data transmission is considered. Extrapolation of traffic for short-term and long-term forecasts is considered. Comparison of the results of the prediction of self-similar traffic using various spline functions has shown that the accuracy of the forecast can be improved through the use of cubic splines. A method is proposed for estimating the error of traffic prediction for each variant of traffic forecasting using linear, cubic splines. The results of the research will allow you to perform effective traffic management with the support of quality characteristics, by providing the required parameters of network hardware and software in order to avoid overloads in the network.

Publisher

Walter de Gruyter GmbH

Reference18 articles.

1. [1] 3GPP Study on Scenarios Requirements for Next Generation Access Technologies, ETSI TR 38.913, V14.3.0, 2017.

2. [2] D. Evans, The Internet of Things, How the Next Evolution of the Internet Is Changing Everything, White Paper: Cisco, 2011.

3. [3] V. V. Krylov and S. S. Samohvalova, Theory of telegraphic its applications, BXV-Petersburg, 2005.

4. [4] O. I. Sheluhin, A. V. Osin, and S. M. Smolskii, Self-Similarity Fractals, Telecommunication Applications, Phismatlit, 2008.10.1002/9780470062098

5. [5] F. C. Pereira, C. Antoniou, J. A. Fargas, and M. Ben-Akiva, “A Metamodel for Estimating Error Bounds in Real-Time Traffic Prediction Systems”, IEEE Transportation on Intelligent Transportation Systems, vol. 15, no. 3, pp. 1310–1322, 2014, DOI: 10.1109/TITS.2014.2300103, 2014.10.1109/TITS.2014.23001032014

Cited by 12 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Chaotic characteristic analysis and prediction of bottleneck-delay time series under the Internet macro-topology;The European Physical Journal Plus;2024-06-06

2. Distributed denial of service attack prediction: Challenges, open issues and opportunities;Computer Networks;2023-02

3. Improving the Accuracy of User Location in the Wi-Fi Network Using Complex Spline-Functions;Progress in Advanced Information and Communication Technology and Systems;2022-11-18

4. Detection and prediction of DDoS cyber attacks using spline functions;2022 IEEE 16th International Conference on Advanced Trends in Radioelectronics, Telecommunications and Computer Engineering (TCSET);2022-02-22

5. Fingerprinting/indoor positioning using complex planar splines;Journal of Electrical Engineering;2021-12-01

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3