The Use of End-to-End Multicast Measurements for Characterizing Internal Network Behavior

Abstract

This is the Final Technical Report for MINC: Multicast-based Inference of Network-internal Characteristics. The primary aim of the MINC project was to develop a statistical foundation on which to develop and evaluate end-to-end based tools for inferring internal network behavior. The project accomplished two goals. First, a series of techniques based on maximum likelihood estimation was developed to infer link-level loss and delay behavior, and internal topological structure based on end-to-end multicast and unicast observations. Briefly, these techniques exploit the correlation inherent in multicast-based measurements to produce accurate estimates. Second, measurement software required to produce the necessary observations and a web-based analysis and visualization tool were developed and made available to the community. The measurement software can be included in any multicast application as well as used on the National Internet Measurement Infrastructure. The analysis/visualization tool allows the user to obtain and visualize time varying loss rate estimates.

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Document Details

Document Type
Technical Report
Publication Date
Aug 01, 2002
Accession Number
ADA406846

Entities

People

  • Don Towsley

Organizations

  • University of Massachusetts Amherst

Tags

Communities of Interest

  • Energy and Power Technologies

DTIC Thesaurus Topics

  • Bayesian Networks
  • Computational Science
  • Computer Networks
  • Computer Science
  • Data Science
  • Electronic Mail
  • Ergodic Processes
  • Information Science
  • Infrastructure
  • Maximum Likelihood Estimation
  • Measurement
  • Network Protocols
  • Network Science
  • Random Variables
  • Statistical Analysis
  • Stochastic Processes
  • Transport Protocols

Fields of Study

  • Computer science

Readers

  • Computational Modeling and Simulation
  • Computer Networking

Technology Areas

  • AI & ML
  • AI & ML - Bayesian Inference