Optimal sampling strategies for multiscale models with application to network traffic estimation

V. J. Ribeiro, R. H. Riedi, R. G. Baraniuk

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

Abstract

The paper considers the problem of determining which set of 2p leaf nodes on a binary multiscale tree model of depth N (N < p) gives the best linear minimum mean-squared estimator of the tree root. We find that the best-case and worst-case sampling choices depend on the correlation structure of the tree. This problem arises in Internet traffic estimation, where the goal is to estimate the average traffic rate on a network path based on a limited number of traffic samples.

Original languageEnglish (US)
Title of host publicationProceedings of the 2003 IEEE Workshop on Statistical Signal Processing, SSP 2003
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages138-141
Number of pages4
ISBN (Electronic)0780379977
DOIs
StatePublished - 2003
EventIEEE Workshop on Statistical Signal Processing, SSP 2003 - St. Louis, United States
Duration: Sep 28 2003Oct 1 2003

Publication series

NameIEEE Workshop on Statistical Signal Processing Proceedings
Volume2003-January

Other

OtherIEEE Workshop on Statistical Signal Processing, SSP 2003
CountryUnited States
CitySt. Louis
Period9/28/0310/1/03

Keywords

  • Application software
  • Computer networks
  • Force measurement
  • IP networks
  • Privacy
  • Probes
  • Sampling methods
  • Signal processing
  • Telecommunication traffic
  • Traffic control

ASJC Scopus subject areas

  • Electrical and Electronic Engineering
  • Applied Mathematics
  • Signal Processing
  • Computer Science Applications

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