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The modeling and simulation of a network controller based on router queue-size predictions

机译:基于路由器队列大小预测的网络控制器的建模和仿真

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While the current routing and congestion control algorithms in use today are often adequate for networks with relatively static topology and relatively lax quality of service (QoS) requirements, these algorithms may not be sufficient for military networks where a strict level of QoS is required in order to achieve mission objectives. Current technology limits a network's ability to adapt to changes and interactions, and this often results in sub-optimal performance. This article develops a network controller that uses outbound router queue size predictions to optimize computer networks. These queue size predictions are made possible through the use of Kalman filters to detect network congestion. The premise is that intelligent agents can use such predictions to form context-aware, cognitive processes to managing network communication. The system shows great promise when modeled and simulated using the NS2 network simulation platform.
机译:尽管当今使用的当前路由和拥塞控制算法通常足以满足拓扑相对静态且服务质量(QoS)要求相对宽松的网络,但对于需要严格QoS等级的军用网络,这些算法可能还不够实现任务目标。当前的技术限制了网络适应变化和交互的能力,这常常导致性能欠佳。本文开发了一种网络控制器,该控制器使用出站路由器队列大小预测来优化计算机网络。通过使用卡尔曼滤波器来检测网络拥塞,可以实现这些队列大小的预测。前提是智能代理可以使用此类预测来形成上下文感知的认知过程来管理网络通信。当使用NS2网络仿真平台进行建模和仿真时,该系统显示出巨大的希望。

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