基于窗口的AIMD拥塞控制的收敛性和最佳缓冲区大小
Convergence and Optimal Buffer Sizing for Window Based AIMD Congestion Control
摘要：
研究了AIMD（Additive Increase Multiplicative Decrease）拥塞控制与带丢弃尾缓冲区的瓶颈路由器之间的相互作用。我们认为，在确定性混合模型的框架内的问题。首先，我们证明了AIMD拥塞控制和瓶颈路由器之间的相互作用的混合模型总是收敛到一个循环的行为。我们描述了周期。得到了在同一周期内拥塞窗口不发生多次跳跃的充要条件。然后，我们提出了一个分析框架的路由器缓冲区大小的最佳选择。我们制定的最佳路由器缓冲区大小的问题作为一个多准则的优化问题，其中拉格朗日函数对应的平均有效吞吐量和队列中的平均延迟的线性组合。优化问题的解决方案提供了进一步的证据，缓冲区的大小应该减少流量聚合的存在。我们的分析结果证实了Simulink和NS仿真器进行的仿真。
英文摘要：
We study the interaction between the AIMD (Additive Increase Multiplicative Decrease) congestion control and a bottleneck router with Drop Tail buffer. We consider the problem in the framework of deterministic hybrid models. First, we show that the hybrid model of the interaction between the AIMD congestion control and bottleneck router always converges to a cyclic behavior. We characterize the cycles. Necessary and sufficient conditions for the absence of multiple jumps of congestion window in the same cycle are obtained. Then, we propose an analytical framework for the optimal choice of the router buffer size. We formulate the problem of the optimal router buffer size as a multi-criteria optimization problem, in which the Lagrange function corresponds to a linear combination of the average goodput and the average delay in the queue. The solution to the optimization problem provides further evidence that the buffer size should be reduced in the presence of traffic aggregation. Our analytical results are confirmed by simulations performed with Simulink and the NS simulator.
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