A multiple input-queued ATM switching fabric based on hopfield neural network cell scheduling | Zendy

Xiong Tao | Zendy; Zhang Bian-Li | Zendy; Chang Sheng-Jiang | Zendy; Jinyuan Shen | Zendy; Yanxin Zhang | Zendy

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A multiple input-queued ATM switching fabric based on hopfield neural network cell scheduling

Author(s) -

Xiong Tao,

Zhang Bian-Li,

Chang Sheng-Jiang,

Jinyuan Shen,

Yanxin Zhang

Publication year - 2005

Publication title -

acta physica sinica

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 0.199

H-Index - 47

ISSN - 1000-3290

DOI - 10.7498/aps.54.2435

Subject(s) - computer science , hol , scheduling (production processes) , artificial neural network , throughput , computer network , mathematical optimization , artificial intelligence , telecommunications , mathematics , programming language , wireless

A multiple input-queued ATM switching fabrics (ASF) for scheduling cell based on Hopfield neural network (HNN) is proposed. This scheme eliminates degeneration of performance due to head-of-line (HOL) blocking. Simulation results show that, compared with the single first in_first out and window input-queued ASF, the pr oposed approach can greatly improve the throughput and reduce the cell delay.

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