# An Accurate Platform for Investigating TCP Performance in Wi-Fi Networks
## 1 Introduction  
In recent years, Wi-Fi networks have been increasing in popularity [1]. On the one hand, an increasing number of devices are using Wi-Fi to connect to the Internet. Everyday devices, such as mobile phones and laptops, as well as Internet of Things (IoT) devices, such as smartwatches and Raspberry Pi devices [2], have always been used with Wi-Fi implementations. On the other hand, ongoing research and development on Wi-Fi/IEEE 802.11 technology has led to the emergence of new Wi-Fi standards every few years, ranging from IEEE 802.11a/b/c/g/n to ad (WiGig), ax (Wi-Fi), etc. Once a Wi-Fi standard has arrived, it offers improved performance compared to its predecessors, especially in terms of throughput. However, Wi-Fi technology focuses on the physical and medium access control (MAC) layers; hence, the performance gains are within the scope of an access point-client link. Consequently, Wi-Fi standards cannot completely reflect application behavior as doing so would require an end-to-end perspective, typically from a client to a server. Many applications use the Transmission Control Protocol (TCP), an essential protocol in the TCP/Internet Protocol (IP) suite, for reliable end-to-end transmission in the transport layer in Wi-Fi networks. TCP relies on congestion control algorithms (CCAs) to adaptto changes in the network. Since there are many TCP CCAs available, it is necessary to understand and quantify their performance. Moreover, TCP has been found to incur several performance degradation problems in Wi-Fi networks, such as bufferblot (i.e., an unexpectedly long delay when a buffer is fully occupied). A quick assessment of this issue can help support Wi-Fi deployment. In addition, when a Wi-Fi network has multiple clients, it is important to account for fairness among the clients' flows since all of them share the bandwidth of the backhaul link. These factors lead to a demand for a time- and cost-effective platform to investigate the TCP performance in Wi-Fi networks. The existing works that have addressed the problem of building an experimental platform for TCP evaluation in Wi-Fi networks can be classified into two categories: methods using real devices and methods relying on a simulator. Although the former can provide realistic and reliable results based on real hardware, they also have several disadvantages. Such a method may require many resources (e.g., network devices, access points, etc.) as well as considerable human effort for configuration and experimental operation. Note that human involvement increases the chance of unexpected errors. In contrast, a simulation does not require hardware resources, which significantly reduces the setup time. However, simulations cannot adequately consider the various characteristics of actual implementation, thus considerably impacting the reliability of the results. Moreover, most real TCP implementations are slightly different from those proposed in the literature, which are typically implemented in simulators. Hence, it is necessary to devise a better approach that can provide results as reliable as those of a physical experiment while offering the convenience of a simulation. This paper presents an emulator-based approach for investigating TCP performance in Wi-Fi networks, aiming to inherit the advantages of both simulations and real networks. The paper's earlier version is published in [3], which shows only the evaluations of CCAs with IEEE 802.11g Wi-Fi networks. The contributions of this study are summarized as follows. * We newly introduce a platform that leverages the emulator Mininet-WiFi for rapidly emulating Wi-Fi networks (e.g., with different IEEE 802.11 standards, etc.) while guaranteeing TCP accuracy by using the actual implementations of TCP CCAs on Linux kernels. We have incorporated performance measurement functionalities and tools to automate the testing processes in our platform. * We compare our platform's performance for 14 TCP CCAs to the corresponding performance results in a real Wi-Fi network with similar settings.