Applied Learning Networks (ALN)

Abstract

Applied Learning Networks (ALN) demonstrates that a network protocol can learn to improve its performance over time, showing how to incorporate learning methods into a general class of network protocols. ALN applies accumulated experience with previous network connections to help tune future network connections. ALN provides demonstration of non-trivial learning in complex communication protocols. It also provides proof that learning results in task specific performance enhancements.

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Document Details

Document Type
Technical Report
Publication Date
Jan 01, 2007
Accession Number
ADA462328

Entities

People

  • Feili Hou
  • Joseph Bannister
  • Joseph Touch
  • Venkata Pingali
  • Wei-min Shen

Organizations

  • University of Southern California

Tags

Communities of Interest

  • Human Systems
  • Space

DTIC Thesaurus Topics

  • Accuracy
  • Air Force Research Laboratories
  • Bayesian Networks
  • Control Systems
  • Data Analysis
  • Governments
  • Information Processing
  • Information Science
  • Instrumentation
  • Machine Learning
  • Models
  • Network Protocols
  • Neural Networks
  • Operating Systems
  • Probability
  • Probability Distributions
  • Transport Protocols

Fields of Study

  • Computer science

Readers

  • Computer Networking
  • Neural Network Machine Learning.
  • Semiconductor Device Technology