知识驱动的拥塞控制方法

Jin Wu, K. Djemame
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引用次数: 3

摘要

本文讨论了一种新的网络拥塞控制方法。将人工智能方法应用于网络拥塞控制中,提出了一种新的知识驱动方法来解决网络拥塞控制问题。与传统的拥塞控制方法不同,知识驱动方法侧重于知识的操纵和组织来生成拥塞控制算法。提出了一种基于专家系统的知识组织拥塞控制框架,并讨论了该框架在解决TCP互味友好问题中的应用。结果表明,知识驱动方法具有以下潜力:1)提高现有拥塞控制算法的性能;2)通过构造复杂的拥塞控制器,以简单可靠的方式解决多变和不确定环境下的拥塞控制问题
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A Knowledge Driven Approach to Congestion Control
A new approach for network congestion control is discussed in this paper. By using artificial intelligence methods in network congestion control, a novel knowledge driven approach is introduced to tackle the congestion control problem. Different from conventional approaches, the knowledge driven approach focuses on knowledge manipulation and organisation to generate congestion control algorithms. An expert-system-based congestion control framework used to organise knowledge is proposed, and its application in solving TCP inter-flavour-friendliness problem is discussed. It is to shown that the knowledge driven approach has potentials in: 1) improving the performance of existing congestion control algorithm; 2) tackling congestion control problem in varying and uncertain environments by constructing complex congestion controller in an easy and reliable way
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