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D-TCP: Dynamic TCP congestion control algorithm for next generation mobile networks

机译:D-TCP:下一代移动网络的动态TCP拥塞控制算法

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In the past few decades, many Transmission Control Protocol (TCP) congestion control algorithms have been investigated to meet the growing network demands and to enhance the performance of TCP in lossy or high-bandwidth-delay-product (high-BDP) networks. However, it is still challenging to implement a dynamic congestion control algorithm for wide range of diverse mobile users, network conditions and applications. This paper explores avenues for enhancement of TCP congestion control algorithm for next generation mobile networks by dynamically learning the available bandwidth and deriving the Congestion Control Factor N. N is used to Adaptive Increase/Adaptive Decrease (AIAD) the Congestion Window (CWND) dynamically instead of using the traditional approach that is Additive Increase/ Multiplicative Decrease (AIMD) paradigm. Once there is congestion, our proposed algorithm will not allow the CWND to decrease multiplicatively or steeply. After dropping to a certain level (lower than legacy), we try to take the CWND to previous state adaptively with the help of calculated bandwidth (based on learning). This in turn helps to efficiently control the CWND for better network utilization especially in case of lossy and high-BDP conditions. As soon as it reaches the original state, it remains stable for longer time as compared to legacy until packet loss or time out. We demonstrate the effectiveness of our algorithm with the help of live air experiments (performed in Samsung R&D India, Bangalore) and NS3 based simulation experiments. Through our experiments, we show that our algorithm outperforms the legacy congestion control algorithms (like CUBIC, RENO, TCPW) and the existing CLTCP algorithm in terms of goodput, intra algorithm fairness and inter algorithm fairness maintaining the scalability and friendliness.
机译:在过去的几十年中,已经研究了许多传输控制协议(TCP)拥塞控制算法,以满足日益增长的网络需求,并增强有损或高带宽延迟乘积(high-BDP)网络中TCP的性能。然而,对于各种各样的移动用户,网络状况和应用实现动态拥塞控制算法仍然是挑战。本文通过动态学习可用带宽并推导拥塞控制因子N,探索了增强下一代移动网络TCP拥塞控制算法的途径。使用传统的加性/乘性减少(AIMD)范例的方法。一旦出现拥塞,我们提出的算法将不允许CWND倍增或急剧下降。在下降到一定水平(低于传统水平)之后,我们尝试在计算出的带宽(基于学习)的帮助下将CWND自适应地恢复到先前状态。反过来,这有助于有效地控制CWND,以更好地利用网络,尤其是在有损和高BDP条件下。一旦达到原始状态,与传统相比,它会保持稳定的时间更长,直到丢包或超时。我们借助实时空气实验(在印度的Bangalore的三星研发中心进行)和基于NS3的模拟实验证明了我们算法的有效性。通过实验,我们证明了在保持吞吐量,友好性和算法公平性方面,我们的算法优于传统的拥塞控制算法(如CUBIC,RENO,TCPW)和现有的CLTCP算法。

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