A neural network approach to ABR flow control in ATM networks is proposed.
本文提出AT M网络中abr业务流量控制的一种基于神经网络方法。
The EFCI-based ABR flow control scheme is a very simple scheme, and is adopted in many ATM switches.
基于EFCI的ABR流量控制方案简单、易行，在AT M交换机中被大量采用。
Flow control of ABR service is the main concert of this thesis.
A BR业务的流量控制是本文讨论的主题。
In the ATM network, ABR service USES a rate-based flow control mechanism.
AT M网络中abr服务采用基于速率的流量控制机制。
Flow control of ABR service is identified by ATM forum as a rate-based close-looped feedback mechanism, which makes ABR service the only one whose rate can be controlled among the five services.
对于ABR业务，AT M论坛最终确定其流量及拥塞控制是一种基于速率的闭环反馈控制机制，这使得A BR成为五种业务中唯一一种速率可控的业务。
This paper proposes an approach to design a rate based flow control mechanism in order to regulate the Available Bit Rate (ABR) traffic and effectively control congestion of the networks.
对此，本文提出一种方法来设计基于速率的流量控制机制以便调节ABR服务并有效地控制网络拥塞。
The main contributions of this paper are as follows:Firstly, the binary ABR congestion control model is deduced based on the flow theory.
首先，基于流体流理论建立了单瓶颈节点的二进制ABR流的网络模型。
The main contributions of this paper are as follows:Firstly, the binary ABR congestion control model is deduced based on the flow theory.
首先，基于流体流理论建立了单瓶颈节点的二进制ABR流的网络模型。
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