APPLICATIONS OF LEARNING AUTOMATA TO ROUTING IN A MULTI-PRIORITY TELEPHONE NETWORK.

B. Akselrod*, G. Langholz

*Corresponding author for this work

Research output: Contribution to conferencePaperpeer-review

1 Scopus citations

Abstract

Traffic and load control in multi-priority telephone networks using advanced routing methods are analyzed using a special-purpose simulation program. Nonadaptive as well as local and centralized adaptive schemes are studied. The grade of service (GOS), probability of preemption (POP), and average number of trunks used per call (AVTRUS) are used as performance criteria and are compared for different load conditions and routing methods. It is shown that centralized adaptive methods are superior to all others.

Original languageEnglish
StatePublished - 1985

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