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Can API-RCP achieve max-min fair bandwidth allocation in a multi-bottleneck network?

机译:API-RCP是否可以在多瓶颈网络中实现最大-最小公平带宽分配?

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Theoretical analysis and experiments have shown that TCP can become oscillatory and prone to instability in high bandwidth-delay-product networks. XCP was proposed to overcome these shortcomings by advertising an explicit window adjustment from the routers to the sources. However, XCP may under-utilize the bandwidth in a multi-bottleneck network and cause some flows to receive an arbitrarily small fraction of their max-min fair rates. Using solid control theoretical analysis and design, API-RCP has solved this potential problem of XCP successfully. Why API-RCP can achieve max-min fair bandwidth allocation and full link utilization in steady state in multi-bottleneck networks? To address this question, we made a simple theoretical analysis and then verify it by OPNETreg simulations. We also propose a controller design scheme to optimize the system performance with minimum control errors. We demonstrate the improved performance through comparison between API-RCP and TCP/RED in a multi-bottleneck network.
机译:理论分析和实验表明,在高带宽延迟乘积网络中,TCP可能会出现振荡并易于不稳定。提出了XCP来解决这些缺点,方法是通告从路由器到源的显式窗口调整。但是,XCP可能无法充分利用多瓶颈网络中的带宽,并导致某些流接收其最大-最小公平速率的任意一小部分。 API-RCP通过固体控制理论分析和设计,成功解决了XCP的这一潜在问题。为什么在多瓶颈网络中,API-RCP可以在稳态下实现最大-最小公平带宽分配和完整链路利用率?为了解决这个问题,我们进行了简单的理论分析,然后通过OPNET reg 仿真对其进行了验证。我们还提出了一种控制器设计方案,以最小的控制误差优化系统性能。通过比较多瓶颈网络中的API-RCP和TCP / RED,我们展示了改进的性能。

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