Graph Wavelets for Spatial Traffic Analysis

Abstract

A number of problems in network operations and engineering call for new methods of traffic analysis. While most existing traffic analysis methods are fundamentally temporal, there is a clear need for the analysis of traffic across multiple network links--that is, for spatial traffic analysis. In this paper we give examples of problems that can be addressed via spatial traffic analysis. We then propose a formal approach to spatial traffic analysis based on the wavelet transform. Our approach (graph wavelets) generalizes the traditional wavelet transform so that it can be applied to data elements connected via an arbitrary graph topology. We explore the necessary and desirable properties of this approach and consider some of its possible realizations. We then apply graph wavelets to measurements from an operating network. Our results show that graph wavelets are very useful for our motivating problems; for example, they can be used to form highly summarized views of an entire network's traffic load, to gain insight into a network's global traffic response to a link failure, and to localize the extent of a failure event within the network.

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Document Details

Document Type
Technical Report
Publication Date
Jul 15, 2002
Accession Number
ADA442573

Entities

People

  • Eric D. Kolaczyk
  • Mark Crovella

Organizations

  • Boston University

Tags

Communities of Interest

  • Energy and Power Technologies

DTIC Thesaurus Topics

  • Algorithms
  • Anomaly Detection
  • Change Detection
  • Computer Science
  • Computer Vision
  • Data Analysis
  • Denial Of Service Attack
  • Detection
  • Engineering
  • Engineers
  • Image Processing
  • Information Operations
  • Integrals
  • Network Topology
  • Standards
  • Topology
  • Wavelet Transforms

Fields of Study

  • Computer science

Readers

  • Distributed Systems and Data Platform Development
  • Image Processing and Computer Vision.
  • Neural Network Machine Learning.