Analysis of large-scale experimental data from wireless networks

Stephen A. Seidel, Michael T. Mehari, Charles Colbourn, Eli De Poorter, Ingrid Moerman, Violet Syrotiuk

Research output: Chapter in Book/Report/Conference proceedingConference contribution

6 Scopus citations

Abstract

The experimental design and subsequent analysis of the data collected from experimentation are tightly coupled. This paper considers techniques for the analysis of data collected from experimentation based on a locating array. Because locating arrays can be highly unbalanced, new analysis techniques are required. In order to cope with noise in the measured performance data, a search is conducted to identify the significant parameters and interactions that impact the data. A novel 'heavy hitters' bounded breadth-first search (BFS) tree algorithm is proposed for analysis. It is used to validate data collected from large-scale experimentation with a physical wireless network testbed and a wireless network simulator, varying 24 and 75 parameters, respectively.

Original languageEnglish (US)
Title of host publicationINFOCOM 2018 - IEEE Conference on Computer Communications Workshops
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages535-540
Number of pages6
ISBN (Electronic)9781538659793
DOIs
StatePublished - Jul 6 2018
Event2018 IEEE Conference on Computer Communications Workshops, INFOCOM 2018 - Honolulu, United States
Duration: Apr 15 2018Apr 19 2018

Other

Other2018 IEEE Conference on Computer Communications Workshops, INFOCOM 2018
CountryUnited States
CityHonolulu
Period4/15/184/19/18

ASJC Scopus subject areas

  • Control and Optimization
  • Artificial Intelligence
  • Computer Networks and Communications

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  • Cite this

    Seidel, S. A., Mehari, M. T., Colbourn, C., De Poorter, E., Moerman, I., & Syrotiuk, V. (2018). Analysis of large-scale experimental data from wireless networks. In INFOCOM 2018 - IEEE Conference on Computer Communications Workshops (pp. 535-540). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/INFCOMW.2018.8407023