Internet Protocol (IP) Network Measurement, Characterization, Modeling, and Control for Self-Managed Networks

Abstract

IP network technology cannot continue on an ever-increasing course of technological complexity and yet require the kind of human intervention that is necessary today for network management. Networks must be self-managing. This can only be done by a system of measurement that copes with the dynamics of packet movement. This system must process the packet-level measurements into variables that characterize network behaviors, which then form the basis for control algorithms that react to the variables. Such packet level measurements can lead to characterization and control at the application layer, at the transport layer, at the network layer (including overlay networking), and in some cases at the link layer. The research documented in this report used tools of statistics, data mining and machine learning to (1) determine network variables derivable from the measurements that characterize network behavior; (2) develop models of the critical network variables that characterize performance, usage, security, and early onset of problems; and (3) develop automated control methods based on the variables.

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Document Details

Document Type
Technical Report
Publication Date
Sep 01, 2005
Accession Number
ADA439560

Entities

People

  • Bowei Xi
  • Hui Chen
  • Jin Cao
  • William S. Cleveland

Organizations

  • Purdue University

Tags

Communities of Interest

  • Energy and Power Technologies
  • Materials and Manufacturing Processes

DTIC Thesaurus Topics

  • Algorithms
  • Communication Systems
  • Computer Networks
  • Control Systems
  • Data Mining
  • Information Science
  • Internet
  • Machine Learning
  • Measurement
  • Network Protocols
  • Network Science
  • Operating Systems
  • Packet Loss
  • Statistical Analysis
  • Statistics
  • Transport Protocols
  • Voice Over Internet Protocol

Fields of Study

  • Computer science

Readers

  • Computer Networking
  • Distributed Systems and Data Platform Development
  • Systems Analysis and Design

Technology Areas

  • AI & ML
  • AI & ML - Bayesian Inference