SBIR Phase I: Fast Flow Control in High Speed Communications Networks

SBIR 第一阶段：高速通信网络中的快速流量控制

• 批准号: 9660335
• 负责人: ChiMan Kwan
• 金额: $ 7.46万
• 依托单位: Intelligent Automation, Inc
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 1997
• 资助国家: 美国
• 起止时间: 1997-01-01 至 1997-06-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=9660335&HistoricalAwards=false
• 关键词: SBIR; Phase; Fast; Flow; Control

*** 9660335 Kwan This Small Business Innovation Research Phase I project describes a new approach to flow control in high speed communication networks which can significantly reduce the packet delays. In many networks, even the traffic is routed optimally, there are situations where the total traffic into the network is much larger than the network can handle. If no control strategies are present to limit the traffic into the network, queue sizes at bottleneck links will grow and packet delays will increase which may violate some maximum delay specifications for voice and video signals. The flow control problem is first treated as a fluid-flow dynamic system with time delay. Based on the model, we propose a flow controller that can generate some predictive information about the future queue length in the system. This predictive information is crucial to the success of the flow control scheme since it guarantees that the time delay of packets will not go unstable. Thus the maximum time delay performance criterion can be assured. In addition, the new flow control method can also maintain certain throughput of the system which is very important in applications such as video distribution. A new type of neural network called Fuzzy CMAC (Cerebellar Model Arithmetic Computer) is also proposed to predict the total information delay and the channel disturbance. The outputs of the Fuzzy CMAC will be passed to the flow controller to enhance the performance even further. The new flow control method can guarantee the maximum packet delay criterion and can also maintain a desired minimum throughput of the system which is very important in applications such as video distribution. Another advantage is that the controller is very easy to implement. The proposed algorithm should find many applications in broadband ISDN and ATM networks. ***

* 9660335关 这个小型企业创新研究第一阶段项目描述了一种新的方法，在高速通信网络中的流量控制，可以显着减少数据包延迟。在许多网络中，即使流量被最佳地路由，也存在进入网络的总流量远远大于网络可以处理的情况。如果没有控制策略来限制进入网络的流量，则瓶颈链路处的队列大小将增长，并且分组延迟将增加，这可能违反语音和视频信号的某些最大延迟规范。流量控制问题首先被视为一个具有时滞的流体流动动态系统。基于该模型，我们提出了一个流量控制器，可以产生一些预测信息的未来队列长度在系统中。这种预测信息对于流控制方案的成功至关重要，因为它保证了分组的时间延迟不会变得不稳定。从而保证了最大时延性能指标。此外，新的流量控制方法还可以保持一定的系统吞吐量，这在视频分发等应用中是非常重要的。提出了一种新的神经网络--模糊小脑模型算术计算机（CMAC），用于预测总的信息延迟和信道干扰。模糊CMAC的输出将被传递到流量控制器，以进一步提高性能。 新的流量控制方法可以保证最大的包延迟标准，也可以保持所需的最小吞吐量的系统，这是非常重要的应用，如视频分发。 另一个优点是控制器非常容易实现。 该算法在宽带ISDN和ATM网络中有广泛的应用。 ***