# Performance and Scalability Analysis of SDN-Based Large-Scale Wi-Fi Networks
## 2 Related Work  
SDN controllers, wired networks, Wi-Fi networks, and simulation toolkits used for SDN Wi-Fi networks are all aspects of related study that are being investigated here. Onthe topic of performance evaluation of wired SDN networks, there are a good number of research articles available:  
The effectiveness of floodlight controllers and POX controllers was analyzed and contrasted by [PERSON] et al. [16]. The authors used Mininet to imitate a variety of topologies and then measured the round-trip time as well as the bandwidth. They came to the conclusion that Floodlight was doing significantly better than POX. POX is recommended in addition to Floodlight because of its usability, notwithstanding the fact that Floodlight achieves good performance. Performance of \"Ryu\", \"POX\", and \"Pyretic\" SDN controllers was analyzed and evaluated by [PERSON] et al. [17]. Mininet was the instrument the creators used to recreate a wired SDN. The round-trip time was the most important performance parameter. Pyretic performs better than Ryu and POX, according to the findings of this research report, which compares the three different controllers. [PERSON] et al. [18] advise using Floodlight and POX to compare the two systems' performances. They take into consideration measures such as throughput and delay. Experiments on the controllers have been conducted in a variety of geographical settings. The authors reach the conclusion that Floodlight is effective than POX in terms of its performance. The execution of Floodlight, on the other hand, requires a predetermined quantity of memory space. Because POX is dependent on Python, it is the superior option in this scenario. In [19], the authors contrast the performance of the SDN Controllers \"Beacon, Mul, Mestro, POX, NOX, Floodlight and Ryu\" by making use of the characteristics such as throughput, reliability, safety, and other similar factors. According to the findings of the study, Beacon, NOX, Floodlight, POX, and Ryu are all effective under typical traffic conditions. On the other hand, Mul and Maestro do not appear to be efficient under the same conditions. [PERSON] et al. [20] examine the similarities and differences between the python-based SDN controllers POX and RYU. Emulation of networks and the production of traffic were both possible with Mininet's use. The authors concluded that POX offers superior performance when it comes to layer 1 switching. On the other hand, it appears that RYU is superior to POX when it comes to layer 2 exchanging. There have only been a few studies that have evaluated the performance of \"Software defined Wireless networks\". \"Ryu, POX, ONOS, and Floodlight\" were tested to see how well they performed in an emulated wireless network by [PERSON] and his colleagues [11]. They evaluated each of these based on jitter and throughput to determine which had the superior performance. It seems that Floodlight has a rather low amount of jitter. The throughput of SDN controllers, on the other hand, does not vary greatly from one to the next. The authors of the paper [21] demonstrated the scalability of an SDN-based Wi-Fi Network running on Mininet by analyzing performance characteristics in a variety of different dynamic scenarios. The authors concluded that increasing the number of hosts for the TCP protocol results in a drop in bandwidth and performance, whereas increasing the number of hosts for the UDP protocol has the opposite effect: jitter increases, yet the bandwidth almost entirely maintains its previous level. In wired networks, it would appear that SDN controllers have been thoroughly analyzed in terms of performance. On the other hand, SDWN are a relatively new topic, and large-scale SDN Wi-Fi networks require performance evaluation using a variety of SDN controllers. This can be inferred from an examination of the state of the art. The study in [22] proposes an algorithm for efficiently and intelligently changing packet directions in SDN networks.