Omega Network-Based ATM Switch with Neural Network-Controlled Bypass Queueing and Multiplexing

Young Keun Park, Vladimir Cherkasky, Gyungho Lee

Research output: Contribution to journalArticle

8 Citations (Scopus)

Abstract

Multistage interconnection networks (MIN's) have long been studied for use in switching networks. Since they have a unique path between source and destination and the intermediate nodes of the paths are shared, internal blocking can cause very poor throughput. This paper proposes a high throughput ATM switch consisting of an Omega network with a new form of input queues called bypass queues. We also improve the switch throughput by partitioning the input buffers into disjoint buffer sets and multiplexing several sets of nonblocking cells within a time slot, assuming that the routing switch operates only a couple of times faster than the transmission rate. A neural network model is presented as a controller for cell scheduling and multiplexing in the switch. Our simulation results under uniform traffic show that the proposed approach achieves almost 100% of potential switch throughput.

Original languageEnglish
Pages (from-to)1471-1480
Number of pages10
JournalIEEE Journal on Selected Areas in Communications
Volume12
Issue number9
DOIs
Publication statusPublished - 1994 Dec
Externally publishedYes

ASJC Scopus subject areas

  • Computer Networks and Communications
  • Electrical and Electronic Engineering

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