2026-09-19T02:12:17Zhttps://ecommons.cornell.edu/server/oai/requestoai:ecommons.cornell.edu:1813/306842026-05-14T13:50:38Zcom_1813_35col_1813_47
Lopez Oliveros, Luis
Resnick, Sidney Ira
Jarrow, Robert A.
Samorodnitsky, Gennady
2012-12-17T13:50:55Z
2016-12-30T06:47:00Z
2011-08-31
https://hdl.handle.net/1813/30684
7955495
A session is a cluster of packets that represents end-user activity in data networks, e.g. surfing the web, transferring files, streaming media, Internet-calling. We study three problems of sessions. The first problem examines why for real sessions the distribution of the number of bytes or number of packets per unit time traveling through a network node is approximately Gaussian, despite previous theoretical results say it may also be stable L´ vy. The second and third problems study four key session e features: size or number of bytes transmitted, duration, average transfer rate, and initiation time. We focus on marginal distributions of size, duration and rate, dependence structure between the marginals, and distribution of the difference between consecutive initiation times. We group sessions according to peak transfer rate in the second problem, and network application in the third problem. The ultimate goal is to teach computers how to mimic network sessions and understand network end-user behavior.
en_US
Modeling End-User Behavior In Data Networks
dissertation or thesis
application/pdf
Statistics
Cornell University
Doctor of Philosophy
Ph. D., Statistics
Publication
Cornell Theses and Dissertations
Lopez Oliveros, Luis
5893a6ea-7af3-41d7-abc6-04bcd26ab5df
open.access
open.access
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<Abstract>A session is a cluster of packets that represents end-user activity in data networks, e.g. surfing the web, transferring files, streaming media, Internet-calling. We study three problems of sessions. The first problem examines why for real sessions the distribution of the number of bytes or number of packets per unit time traveling through a network node is approximately Gaussian, despite previous theoretical results say it may also be stable L´ vy. The second and third problems study four key session e features: size or number of bytes transmitted, duration, average transfer rate, and initiation time. We focus on marginal distributions of size, duration and rate, dependence structure between the marginals, and distribution of the difference between consecutive initiation times. We group sessions according to peak transfer rate in the second problem, and network application in the third problem. The ultimate goal is to teach computers how to mimic network sessions and understand network end-user behavior.</Abstract>
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