Anova-informed decision trees for voice applications over manets

Mouna Benaissa, Vincent Lecuire, D. W. McClary, Violet Syrotiuk

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

2 Scopus citations

Abstract

Both real-time multimedia and mobile networks present challenges ripe for new analysis techniques. We examine the applicability of statistical design of experiments and inductive learning theory in the prediction of delay for real-time audio transmissions over mobile ad hoc networks. Utilizing analysis of variance methods and simple decision tree agents, we find both significant factor interaction between traffic load and node mobility as well as a dramatic reduction in error percentage in prediction of end-to-end delay.

Original languageEnglish (US)
Title of host publicationMobile and Wireless
Subtitle of host publicationCommunication Networks - IFIP TC6/WG6.8 Conference on Mobile and Wireless Communication Networks, MWCN 2004
PublisherSpringer New York LLC
Pages143-154
Number of pages12
ISBN (Print)038723148X, 9780387231488
StatePublished - 2005
EventIFIP TC6/WG6.8 Conference on Mobile and Wireless Communication Networks, MWCN 2004 - Paris, France
Duration: Oct 25 2004Oct 27 2004

Publication series

NameIFIP Advances in Information and Communication Technology
Volume162
ISSN (Print)1868-4238

Other

OtherIFIP TC6/WG6.8 Conference on Mobile and Wireless Communication Networks, MWCN 2004
Country/TerritoryFrance
CityParis
Period10/25/0410/27/04

ASJC Scopus subject areas

  • Information Systems
  • Computer Networks and Communications
  • Information Systems and Management

Fingerprint

Dive into the research topics of 'Anova-informed decision trees for voice applications over manets'. Together they form a unique fingerprint.

Cite this