Modeling Internet Traffic Generations Based on Individual Users and Activities for Telecommunication Applications

S. Stoudt, Pamela Badian-Pessot, Blanche Ngo Mahop, Erika Earley, J. Menter, Yadira Flores, Danielle Williams, Weijia Zhang, Liza Maharjan, Yixin Bao, L. Rosenbauer, Van Nguyen, V. Mendiratta, N. Tania
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引用次数: 1

Abstract

ABSTRACT A traffic generation model is a stochastic model of the data flow in a communication network. These models are useful during the development of telecommunication technologies and for analyzing the performance and capacity of various protocols, algorithms, and network topologies. We present here two modeling approaches for simulating internet traffic. In our models, we simulate the length and interarrival times of individual packets, the discrete unit of data transfer over the internet. Our first modeling approach is based on fitting data to known theoretical distributions. The second method utilizes empirical copulae and is completely data driven. Our models were based on internet traffic data generated by different individuals performing specific tasks (e.g. web-browsing, video streaming, and online gaming). When combined, these models can be used to simulate internet traffic from multiple individuals performing typical tasks.
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电信应用中基于个人用户和活动的互联网流量生成建模
流量生成模型是通信网络中数据流的随机模型。这些模型在电信技术的开发和分析各种协议、算法和网络拓扑的性能和容量时非常有用。我们在这里提出了两种模拟互联网流量的建模方法。在我们的模型中,我们模拟了单个数据包的长度和间隔到达时间,数据包是互联网上数据传输的离散单元。我们的第一种建模方法是基于对已知理论分布的拟合数据。第二种方法利用经验公式,完全是数据驱动的。我们的模型基于不同个体执行特定任务(如网页浏览、视频流和在线游戏)所产生的互联网流量数据。当这些模型结合在一起时,可以用来模拟来自多个执行典型任务的个人的互联网流量。
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