An Accurate Platform for Investigating TCP Performance in Wi-Fi Networks

• Published in: Future internet Vol. 15; no. 7; p. 246
• Main Authors: Aoyagi, Shunji, Horie, Yuki, Thi Thu Hien, Do, Duc Ngo, Thanh, Le, Duy-Dinh, Nguyen, Kien, Sekiya, Hiroo
• Format: Journal Article
• Language: English
• Published: Basel MDPI AG 01-07-2023
• Subjects: Access control; Algorithms; Bandwidths; Buffers; Congestion; congestion control; Control algorithms; emulator; Emulators; evaluation; Internet of Things; Investigations; Networks; Protocol; TCP; TCP (protocol); Transmission Control Protocol/Internet Protocol (Computer network protocol); Wi-Fi; Wide area networks; Wireless access points; Nevada
• ISSN: 1999-5903; 1999-5903
• DOI: 10.3390/fi15070246

An increasing number of devices are connecting to the Internet via Wi-Fi networks, ranging from mobile phones to Internet of Things (IoT) devices. Moreover, Wi-Fi technology has undergone gradual development, with various standards and implementations. In a Wi-Fi network, a Wi-Fi client typically uses the Transmission Control Protocol (TCP) for its applications. Hence, it is essential to understand and quantify the TCP performance in such an environment. This work presents an emulator-based approach for investigating the TCP performance in Wi-Fi networks in a time- and cost-efficient manner. We introduce a new platform, which leverages the Mininet-WiFi emulator to construct various Wi-Fi networks for investigation while considering actual TCP implementations. The platform uniquely includes tools and scripts to assess TCP performance in the Wi-Fi networks quickly. First, to confirm the accuracy of our platform, we compare the emulated results to the results in a real Wi-Fi network, where the bufferbloat problem may occur. The two results are not only similar but also usable for finding the bufferbloat condition under different methods of TCP congestion control. Second, we conduct a similar evaluation in scenarios with the Wi-Fi link as a bottleneck and those with varying signal strengths. Third, we use the platform to compare the fairness performance of TCP congestion control algorithms in a Wi-Fi network with multiple clients. The results show the efficiency and convenience of our platform in recognizing TCP behaviors.