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

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.

I. Introduction

The Transmission Control Protocol (TCP) has been adopted widely for reliable and error-checked delivery by extensive applications like streaming media, peer-to-peer file sharing, email, file transfer, World Wide Web (www), remote administration, secure shell and the like. On the other hand, mobile networks have evolved substantially over a decade. The next generation networks aim to provide ultra low latency, high throughput and massive connectivity. With the evolution of mobile networks, many real time mobile applications have emerged demanding high bandwidth and less delay, which at times may cause congestion in the network. Moreover, with the introduction of next generation mobile network services like Internet of Things (IoT), D2D (Device to Device) communications, Internet of Vehicles (IoV), the network conditions change dynamically.