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{"title":"Semi-Empirical Description and Projections of Internet Traffic Trends Using a Hyperbolic Compound Annual Growth Rate","authors":"Steven K. Korotky","doi":"10.1002/bltj.21625","DOIUrl":null,"url":null,"abstract":"<p>For the purpose of projecting future macroscopic Internet traffic, we have analyzed historical U.S. and global Internet traffic volumes previously reported for 1990 to the present. The empirical long-term traffic trends are characterized by growth rates that have generally been decreasing over time, and so are not adequately described as exponential growth. Based on regression analyses, we also conclude that the decreasing growth rates are not well represented by the saturation characteristic of the logistic function alone. However, we find the observed traffic data are well reproduced over ranges spanning more than six orders of magnitude of traffic volume and a period of 17 years by a hyperbolic dependence of the compound annual growth rate on time. Using a semi-empirical hyperbolic function to model the growth rate we have carried out linearized regression analyses of a combination of historical and near-term traffic forecasts to project macroscopic Internet traffic to 2020 for several geo-economic regions, market segments, and application categories. In contrast to the decade of 2000–2010 when global Internet traffic grew more than 100-fold, the projections indicate that over the decade 2010–2020 the global wireline Internet traffic will grow approximately 16 times larger to approach 250 exabytes per month and the global mobile Internet traffic will grow approximately 150 times larger to approach 40 exabytes per month. The projections also indicate that over the decade the compound annual growth rate of global wireline Internet traffic will decrease from approximately 45 percent to 25 percent per year and the growth rate of global mobility Internet traffic will decrease from approximately 170 percent to 30 percent per year. By considering both the historical trends and near-term forecasts, our analyses and projections call attention to those traffic categories for which estimates of future Internet traffic may carry lesser or greater uncertainty. © 2013 Alcatel-Lucent.</p>","PeriodicalId":55592,"journal":{"name":"Bell Labs Technical Journal","volume":"18 3","pages":"5-21"},"PeriodicalIF":0.0000,"publicationDate":"2013-11-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1002/bltj.21625","citationCount":"36","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Bell Labs Technical Journal","FirstCategoryId":"1085","ListUrlMain":"https://onlinelibrary.wiley.com/doi/10.1002/bltj.21625","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"Engineering","Score":null,"Total":0}
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Abstract
For the purpose of projecting future macroscopic Internet traffic, we have analyzed historical U.S. and global Internet traffic volumes previously reported for 1990 to the present. The empirical long-term traffic trends are characterized by growth rates that have generally been decreasing over time, and so are not adequately described as exponential growth. Based on regression analyses, we also conclude that the decreasing growth rates are not well represented by the saturation characteristic of the logistic function alone. However, we find the observed traffic data are well reproduced over ranges spanning more than six orders of magnitude of traffic volume and a period of 17 years by a hyperbolic dependence of the compound annual growth rate on time. Using a semi-empirical hyperbolic function to model the growth rate we have carried out linearized regression analyses of a combination of historical and near-term traffic forecasts to project macroscopic Internet traffic to 2020 for several geo-economic regions, market segments, and application categories. In contrast to the decade of 2000–2010 when global Internet traffic grew more than 100-fold, the projections indicate that over the decade 2010–2020 the global wireline Internet traffic will grow approximately 16 times larger to approach 250 exabytes per month and the global mobile Internet traffic will grow approximately 150 times larger to approach 40 exabytes per month. The projections also indicate that over the decade the compound annual growth rate of global wireline Internet traffic will decrease from approximately 45 percent to 25 percent per year and the growth rate of global mobility Internet traffic will decrease from approximately 170 percent to 30 percent per year. By considering both the historical trends and near-term forecasts, our analyses and projections call attention to those traffic categories for which estimates of future Internet traffic may carry lesser or greater uncertainty. © 2013 Alcatel-Lucent.
使用双曲线复合年增长率的互联网流量趋势的半经验描述和预测
为了预测未来宏观互联网流量,我们分析了1990年至今美国和全球互联网流量的历史报告。经验性的长期流量趋势的特点是增长率通常随着时间的推移而下降,因此不能充分地描述为指数增长。基于回归分析,我们还得出结论,增长率的下降并不能很好地代表逻辑函数的饱和特征。然而,我们发现观测到的交通数据在超过6个数量级的交通量和17年的时间段内,通过复合年增长率对时间的双曲线依赖性,可以很好地再现。使用半经验双曲线函数来模拟增长率,我们对历史和近期流量预测的组合进行了线性回归分析,以预测到2020年几个地缘经济区域、细分市场和应用类别的宏观互联网流量。与2000-2010年全球互联网流量增长超过100倍的十年相比,预测表明,在2010-2020年的十年中,全球有线互联网流量将增长约16倍,达到每月250艾字节,全球移动互联网流量将增长约150倍,达到每月40艾字节。该预测还表明,在未来十年中,全球有线互联网流量的复合年增长率将从每年约45%下降到25%,全球移动互联网流量的增长率将从每年约170%下降到30%。通过考虑历史趋势和近期预测,我们的分析和预测提醒人们注意那些流量类别,对未来互联网流量的估计可能会有更少或更大的不确定性。©2013阿尔卡特朗讯
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