Mobile device-level data modeling through high utilization mobile applications

Junghyo Lee, Patrick Seeling

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

2 Scopus citations

Abstract

In this paper, we present a mobile-device level approach to estimating the network data (traffic) that is generated over time. While efforts oftentimes utilize complex approaches, our model captures the main characteristics in the time and data domains of a high utilization application class as Hidden Markov Model while modeling the remaining applications' characteristics in form of a simple background process. We find that our approach is capable of matching the average amounts of data behavior of the source dataset (with a reduction in overall variability of the simulated produced traffic as drawback) and is thus suitable for high level capacity evaluations.

Original languageEnglish
Title of host publication2014 IEEE 11th Consumer Communications and Networking Conference, CCNC 2014
PublisherIEEE Computer Society
Pages513-514
Number of pages2
ISBN (Print)9781479923557
DOIs
StatePublished - 2014
Event2014 IEEE 11th Consumer Communications and Networking Conference, CCNC 2014 - Las Vegas, NV, United States
Duration: Jan 10 2014Jan 13 2014

Publication series

Name2014 IEEE 11th Consumer Communications and Networking Conference, CCNC 2014

Conference

Conference2014 IEEE 11th Consumer Communications and Networking Conference, CCNC 2014
Country/TerritoryUnited States
CityLas Vegas, NV
Period01/10/1401/13/14

Keywords

  • Data communication
  • Mobile communication
  • Simulation
  • User modeling

Fingerprint

Dive into the research topics of 'Mobile device-level data modeling through high utilization mobile applications'. Together they form a unique fingerprint.

Cite this