Machine learning-based approach to load balancing in computer networks

Research output: Contribution to journalArticle

9 Citations (Scopus)

Abstract

This paper presents an AI-based approach to load balancing in computer networks; the load redistribution in the network is controlled by a rule-based expert system. Our experiments have shown that changes in the workload structure impose the necessity of automated modifications of the rules in the knowledge base. These modifications are made by means of a machine learning subsystem that is incremental and capable of forgetting pieces of knowledge that have become obsolete. This paper can be understood as a brief report on a real-world application of Michalski's idea of flexible concepts.

Original languageEnglish
Pages (from-to)389-400
Number of pages12
JournalCybernetics and Systems
Volume23
Issue number3-4
StatePublished - May 1 1992
Externally publishedYes

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Computer networks
Expert systems
Resource allocation
Learning systems
Experiments

ASJC Scopus subject areas

  • Human-Computer Interaction
  • Control and Systems Engineering

Cite this

Machine learning-based approach to load balancing in computer networks. / Kubat, Miroslav.

In: Cybernetics and Systems, Vol. 23, No. 3-4, 01.05.1992, p. 389-400.

Research output: Contribution to journalArticle

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