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 publicationIEEE Workshop on Statistical Signal Processing Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages138-141
Number of pages4
Volume2003-January
ISBN (Print)0780379977
DOIs
StatePublished - 2003
EventIEEE Workshop on Statistical Signal Processing, SSP 2003 - St. Louis, United States
Duration: Sep 28 2003Oct 1 2003

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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