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

Young Keun Park; Vladimir Cherkasky; Gyungho Lee

doi:10.1109/49.339914

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

Young Keun Park, Vladimir Cherkasky, Gyungho Lee

Research output: Contribution to journal › Article › peer-review

10 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 language	English
Pages (from-to)	1471-1480
Number of pages	10
Journal	IEEE Journal on Selected Areas in Communications
Volume	12
Issue number	9
DOIs	https://doi.org/10.1109/49.339914
Publication status	Published - 1994 Dec

Bibliographical note

Funding Information:
Manuscript received September 10, 1993; revised June 10, 1994. This work was supported in part by Samsung Electronics Ltd. The authors are with the Department of Electrical Engineering, University of Minnesota, Minneapolis, MN 55455 USA. IEEE Log Number 9405928.

ASJC Scopus subject areas

Computer Networks and Communications
Electrical and Electronic Engineering

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10.1109/49.339914

Cite this

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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.",

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N2 - 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.

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

Abstract

Bibliographical note

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