scholarly journals Comparison of TCP SIAD and TCP BBR Congestion Control in Simulated 5G Networks

Author(s):  
Donát Scharnitzky ◽  
Zsolt Krämer ◽  
Sándor Molnár

Abstract 5G cellular networks have introduced a completely novel air interface called New Radio (NR). This technology delivers numerous benefits compared to previous generations, including significantly higher peak data rates. However, due to the propagation properties of the frequencies used in NR, the volatility of the available downlink capacity also increases. In this paper, we study two TCP congestion control algorithms which are designed to be able to quickly utilize sudden increases in available capacity. We present an implementation of TCP SIAD in the ns-3 open source network simulator and compare its performance with TCP BBR using the mmWave module of the simulator.

Congestion is an important issue in cable network where transmitted packets to the network are much more than holding capacity of network. Each network needs the maximum number of successful packets to reach the destination with less number of packet losses and low time delay with better fairness. There are several congestion control algorithms which have been studied to keep the network stable. They employ various techniques from which the buffer or queue management used by the router is one significant issue to control congestion. The Active Queue Management algorithms like RED controls the queue size by dropping or marking the packets before buffer becomes full . In this paper a new algorithm has been proposed and the results are compared with existing RED algorithm using network simulator (NS-2) in a responsive environment of the cable network


Telecom ◽  
2021 ◽  
Vol 2 (1) ◽  
pp. 1-26
Author(s):  
Athanasios Kanavos ◽  
Dimitrios Fragkos ◽  
Alexandros Kaloxylos

Vehicular communications is expected to be one of the key applications for cellular networks during the following decades. Key international organizations have already described in detail a number of related use cases, along with their requirements. This article provides a comprehensive analysis of these use cases and a harmonized view of the requirements for the latest and most advanced autonomous driving applications. It also investigates the extent of support that 4G and 5G networks can offer to these use cases in terms of delay and spectrum needs. The paper identifies open issues and discusses trends and potential solutions.


1999 ◽  
Vol 27 (1) ◽  
pp. 212-213 ◽  
Author(s):  
Narayanan Venkitaraman ◽  
Tae-eun Kim ◽  
Kang-Won Lee

Sensors ◽  
2021 ◽  
Vol 21 (13) ◽  
pp. 4510
Author(s):  
Josip Lorincz ◽  
Zvonimir Klarin ◽  
Julije Ožegović

In today’s data networks, the main protocol used to ensure reliable communications is the transmission control protocol (TCP). The TCP performance is largely determined by the used congestion control (CC) algorithm. TCP CC algorithms have evolved over the past three decades and a large number of CC algorithm variations have been developed to accommodate various network environments. The fifth-generation (5G) mobile network presents a new challenge for the implementation of the TCP CC mechanism, since networks will operate in environments with huge user device density and vast traffic flows. In contrast to the pre-5G networks that operate in the sub-6 GHz bands, the implementation of TCP CC algorithms in 5G mmWave communications will be further compromised with high variations in channel quality and susceptibility to blockages due to high penetration losses and atmospheric absorptions. These challenges will be particularly present in environments such as sensor networks and Internet of Things (IoT) applications. To alleviate these challenges, this paper provides an overview of the most popular single-flow and multy-flow TCP CC algorithms used in pre-5G networks. The related work on the previous examinations of TCP CC algorithm performance in 5G networks is further presented. A possible implementation of TCP CC algorithms is thoroughly analysed with respect to the specificities of 5G networks, such as the usage of high frequencies in the mmWave spectrum, the frequent horizontal and vertical handovers, the implementation of the 5G core network, the usage of beamforming and data buffering, the exploitation of edge computing, and the constantly transmitted always-on signals. Moreover, the capabilities of machine learning technique implementations for the improvement of TCPs CC performance have been presented last, with a discussion on future research opportunities that can contribute to the improvement of TCP CC implementation in 5G networks. This survey paper can serve as the basis for the development of novel solutions that will ensure the reliable implementation of TCP CC in different usage scenarios of 5G networks.


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