Autonomous smart routing for network QoS

E. Gelenbe, M. Gellman, R. Lent, Peixiang Liu, Pu Su
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引用次数: 84

Abstract

We present an autonomous adaptive quality of service (QoS) driven network system called a "cognitive packet network" (CPN), which adaptively selects paths so as to offer best effort QoS to the end users based on user defined QoS. CPN uses neural network based reinforcement learning to make routing decisions separately at each node. Measurements on an experimental test-bed are provided to show how the system responds to the choice of QoS goals. We also discuss and evaluate an extension of CPN that uses a genetic algorithm to generate and maintain paths from previously discovered information by matching their "fitness" with respect to the desired QoS.
面向网络QoS的自主智能路由
提出了一种自主自适应服务质量驱动的网络系统,称为“认知分组网络”(CPN),该网络在用户自定义QoS的基础上自适应地选择路径,从而为最终用户提供最优QoS。CPN使用基于神经网络的强化学习在每个节点分别做出路由决策。提供了实验测试平台上的测量结果,以显示系统如何响应QoS目标的选择。我们还讨论和评估了CPN的扩展,该扩展使用遗传算法从先前发现的信息中生成和维护路径,通过将它们的“适应度”与期望的QoS相匹配。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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