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Statistical analysis and modeling of Internet VoIP traffic for network engineering

机译：用于网络工程的Internet VoIP流量的统计分析和建模

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Network engineering for quality-of-service (QoS) of Internet voice communication (VoIP) can benefit substantially from simulation study of the VoIP packet traffic on a network of routers. This requires accurate statistical models for the packet arrivals to the network from a gateway. The arrival point process is the superposition, or statistical multiplexing, of the arrival processes of packets of individual calls. The packets of each call form a transient point process with on-intervals of transmission and off-intervals of silence. This article presents the development and validation of models for the multiplexed process based on statistical analyses of VoIP traffic from the Global Crossing (GBLX) international network: 48 hr of VoIP arrival times and headers of 1.315 billion packets from 332018 calls. Statistical models and methods involve point processes and their superposition; time series autocorrelations and power spectra; long-range dependence; random effects and hierarchical modeling; bootstrapping; robust estimation; modeling independence and identical distribution; and visualization methods for model building. The result is two models validated by the analyses that can generate accurate synthetic multiplexed packet traffic. One is a semi-empirical model: empirical data are a part of the model. The second is a mathematical model: the components are parametric statistical models. This is the first comprehensive modeling of VoIP traffic based on data from a service provider carrying a full range of VoIP applications. The models can be used for simulation of any IP network architecture, wireline or wireless, because the modeling is for the IP-inbound traffic to an IP network. This is achieved because the GBLX data, collected on an IP link, are very close to their properties when they entered the GBLX network.
机译：Internet语音通信（VoIP）的服务质量（QoS）的网络工程可以从路由器网络上VoIP数据包流量的仿真研究中受益匪浅。这需要用于从网关到达网络的数据包的准确统计模型。到达点过程是各个呼叫的数据包到达过程的叠加或统计复用。每个呼叫的数据包形成一个瞬态点过程，具有传输的接通间隔和静音的断开间隔。本文基于对来自全球跨界（GBLX）国际网络的VoIP流量的统计分析，介绍了用于多路复用过程的模型的开发和验证：48小时的VoIP到达时间和来自332018个呼叫的13.15亿个数据包的报头。统计模型和方法涉及点过程及其叠加。时间序列自相关和功率谱;长期依赖随机效应和分层建模;自举稳健估计;建模独立且分布相同;以及用于模型构建的可视化方法。结果是通过分析验证的两个模型，可以生成准确的合成多路复用数据包流量。一个是半经验模型：经验数据是模型的一部分。第二个是数学模型：组件是参数统计模型。这是基于来自服务提供商的数据的VoIP流量的第一个全面建模，该服务提供商携带了各种VoIP应用程序。这些模型可用于模拟任何IP网络体系结构（有线或无线），因为建模是针对到IP网络的IP入站流量。之所以能够实现这一目标，是因为IP链路上收集的GBLX数据进入GBLX网络时非常接近其属性。

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