A Comparison of Congestion Control Algorithms in Emulated Wi-Fi Networks

RESEARCH CREW

14:56 19/09/2020

Wi-Fi technology has become popular in our lives with various Wi-Fi capable products such as laptops, mobile phones, etc. Moreover, in Wi-Fi networks, a device communicates typically with a server using Transmission Control Protocol (TCP) for most applications. In such a context, the behavior of the TCP congestion control primarily affects network performance. Hence, it is essential to determine and select an appropriate TCP congestion control that fits different network conditions. In this paper, we present a performance evaluation of TCP congestion control algorithms in an emulated Wi-Fi network. More specifically, we investigate 14 TCP congestion control algorithms in the Wi-Fi network, considering the variation of queue size and packet loss. The evaluation results of Round Trip Time (RTT) and achieved throughput allows us to compare the TCP congestion control algorithms. In our investigation, the Bottleneck Bandwidth Roundtrip-Time algorithm (BBR) has the best performance.

TIN LIÊN QUAN

An Approach of Adaptive Cyber Deception for Active Cyber-attack Defense Method based on Deep Reinforcement Learning

The diverse landscape of network models, including Software-Defined Networking (SDN), Cloud Computing (C2), and Internet of Things (IoT), is evolving to meet the demands of flexibility and performance. However, these environments face numerous security challenges due to cyber-attack complexity. Traditional defense mechanisms are no longer effective against modern attacks. Therefore,...

Multimodal Deep Learning Feedback for Generating Evasive Malware Samples against Malware Detector

As data driven-based Windows malware detectors become increasingly prevalent, the need for robust evaluation and enhancement of adversarial malware generation techniques also becomes imperative, as malicious actors will adapt and enhance their malware to evade detection. There are numerous works that introduce new techniques or enhancements for adversarial malware. One...

Medichain: A multi-chain based system for managing prescription medications using Zero Knowledge Proofs

The abuse of prescription medications has become a severe public health crisis fueled by limited coordination and oversight across healthcare systems. Current frameworks lack interoperability between doctors, pharmacies, and regulators, enabling abusive practices like doctor shopping and pharmacy hopping. To address these issues, this research proposes Medichain, a novel multichain-based...