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
{"title":"Modeling Internet Traffic Generations Based on Individual Users and Activities for Telecommunication Applications","authors":"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","doi":"10.33697/AJUR.2016.028","DOIUrl":null,"url":null,"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.","PeriodicalId":22986,"journal":{"name":"The Journal of Undergraduate Research","volume":"20 1","pages":"53"},"PeriodicalIF":0.0000,"publicationDate":"2016-08-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"The Journal of Undergraduate Research","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.33697/AJUR.2016.028","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
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.