Rapid model parameteration from traffic measurement. Lan, K. & Heidemann, J. ACM Transactions on Modeling and Computer Simulations, 12(3):201–229, July, 2002. ![Rapid model parameteration from traffic measurement [link]](https://bibbase.org/img/filetypes/link.svg "link")
Paper abstract bibtex The utility of simulations and analysis heavily relies on good models of network traffic. While network traffic constantly changing over time, existing approaches typically take years from collecting trace, analyzing the data to finally generating and implementing models. In this paper, we describe approaches and tools that support rapid parameterization of traffic models from live network measurements. Rather than treating measured traffic as a time-series of statistics, we utilize the traces to estimate end-user behavior and network conditions to generate application-level simulation models. We also show multi-scaling analytic techniques are helpful for debugging and validating the model. To demonstrate our approaches, we develop structural source-level models for web and FTP traffic and evaluate their accuracy by comparing the outputs of simulation against the original trace. We also compare our work with existing traffic generation tool and show our approach is more flexible in capturing the heterogeneity of traffic. Finally, we automate and integrate the process from trace analysis to model validation for easy model parameterization from new data.
@Article{Lan02c,
author = "Kun-Chan Lan and John Heidemann",
title = "Rapid model parameteration from traffic measurement",
journal = "ACM Transactions on Modeling and Computer Simulations",
year = 2002,
sortdate = "2002-07-01",
project = "ant, saman",
jsubject = "traffic_modeling",
volume = 12,
number = 3,
month = jul,
pages = "201--229",
jlocation = "johnh: folder: xxx",
jlocation = "johnh: pafile",
keywords = "ramp, model parameterization",
url = "https://ant.isi.edu/%7ejohnh/PAPERS/Lan02c.html",
pdfurl = "https://ant.isi.edu/%7ejohnh/PAPERS/Lan02c.pdf",
otherurl = "http://portal.acm.org/citation.cfm?id=643117&coll=portal&dl=ACM&CFID=12087341&CFTOKEN=69397981",
myorganization = "USC/Information Sciences Institute",
copyrightholder = "Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. To copy otherwise, to republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. ",
abstract = "
The utility of simulations and analysis heavily relies on good models
of network traffic. While network traffic constantly changing over
time, existing approaches typically take years from collecting trace,
analyzing the data to finally generating and implementing models. In
this paper, we describe approaches and tools that support rapid
parameterization of traffic models from live network
measurements. Rather than treating measured traffic as a time-series
of statistics, we utilize the traces to estimate end-user behavior and
network conditions to generate application-level simulation models. We
also show multi-scaling analytic techniques are helpful for debugging
and validating the model. To demonstrate our approaches, we develop
structural source-level models for web and FTP traffic and evaluate
their accuracy by comparing the outputs of simulation against the
original trace. We also compare our work with existing traffic
generation tool and show our approach is more flexible in capturing
the heterogeneity of traffic. Finally, we automate and integrate the
process from trace analysis to model validation for easy model
parameterization from new data.
",
}
Downloads: 0
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To copy otherwise, to republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. ","abstract":"The utility of simulations and analysis heavily relies on good models of network traffic. While network traffic constantly changing over time, existing approaches typically take years from collecting trace, analyzing the data to finally generating and implementing models. In this paper, we describe approaches and tools that support rapid parameterization of traffic models from live network measurements. Rather than treating measured traffic as a time-series of statistics, we utilize the traces to estimate end-user behavior and network conditions to generate application-level simulation models. We also show multi-scaling analytic techniques are helpful for debugging and validating the model. To demonstrate our approaches, we develop structural source-level models for web and FTP traffic and evaluate their accuracy by comparing the outputs of simulation against the original trace. We also compare our work with existing traffic generation tool and show our approach is more flexible in capturing the heterogeneity of traffic. Finally, we automate and integrate the process from trace analysis to model validation for easy model parameterization from new data. ","bibtex":"@Article{Lan02c,\n\tauthor = \t\"Kun-Chan Lan and John Heidemann\",\n\ttitle = \t\"Rapid model parameteration from traffic measurement\",\n\tjournal = \t\"ACM Transactions on Modeling and Computer Simulations\",\n\tyear = \t\t2002,\n\tsortdate = \t\t\"2002-07-01\",\n\tproject = \"ant, saman\",\n\tjsubject = \"traffic_modeling\",\n\tvolume =\t12,\n\tnumber =\t3,\n\tmonth =\t\tjul,\n\tpages =\t\t\"201--229\",\n\tjlocation =\t\"johnh: folder: xxx\",\n\tjlocation =\t\"johnh: pafile\",\n\tkeywords =\t\"ramp, model parameterization\",\n\turl =\t\t\"https://ant.isi.edu/%7ejohnh/PAPERS/Lan02c.html\",\n\tpdfurl =\t\"https://ant.isi.edu/%7ejohnh/PAPERS/Lan02c.pdf\",\n\totherurl = \"http://portal.acm.org/citation.cfm?id=643117&coll=portal&dl=ACM&CFID=12087341&CFTOKEN=69397981\",\n\tmyorganization =\t\"USC/Information Sciences Institute\",\n\tcopyrightholder = \"Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. To copy otherwise, to republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. \",\n\tabstract = \"\nThe utility of simulations and analysis heavily relies on good models\nof network traffic. While network traffic constantly changing over\ntime, existing approaches typically take years from collecting trace,\nanalyzing the data to finally generating and implementing models. In\nthis paper, we describe approaches and tools that support rapid\nparameterization of traffic models from live network\nmeasurements. Rather than treating measured traffic as a time-series\nof statistics, we utilize the traces to estimate end-user behavior and\nnetwork conditions to generate application-level simulation models. We\nalso show multi-scaling analytic techniques are helpful for debugging\nand validating the model. To demonstrate our approaches, we develop\nstructural source-level models for web and FTP traffic and evaluate\ntheir accuracy by comparing the outputs of simulation against the\noriginal trace. We also compare our work with existing traffic\ngeneration tool and show our approach is more flexible in capturing\nthe heterogeneity of traffic. Finally, we automate and integrate the\nprocess from trace analysis to model validation for easy model\nparameterization from new data.\n\",\n}\n\n","author_short":["Lan, K.","Heidemann, J."],"bibbaseid":"lan-heidemann-rapidmodelparameterationfromtrafficmeasurement-2002","role":"author","urls":{"Paper":"https://ant.isi.edu/%7ejohnh/PAPERS/Lan02c.html"},"keyword":["ramp","model parameterization"],"metadata":{"authorlinks":{}}},"bibtype":"article","biburl":"https://bibbase.org/f/dHevizJoWEhWowz8q/johnh-2023-2.bib","dataSources":["YLyu3mj3xsBeoqiHK","fLZcDgNSoSuatv6aX","fxEParwu2ZfurScPY","7nuQvtHTqKrLmgu99"],"keywords":["ramp","model parameterization"],"search_terms":["rapid","model","parameteration","traffic","measurement","lan","heidemann"],"title":"Rapid model parameteration from traffic measurement","year":2002}