Open AccessA multiple input-queued ATM switching fabric based on hopfield neural network cell scheduling
Author(s) -
Tao Xiong,
Zhang Bian-Li,
Shengjiang Chang,
Jing Shen,
Yanxin Zhang
Publication year - 2005
Publication title -
wuli xuebao
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.