## 4 Related Works  
Several recent studies have followed a similar structure and methodology, focusing on performance analysis in IoT and network contexts. For instance, [PERSON] et al. [10] evaluated the performance of MQTT v5.0 brokers using the MQTTLoader tool, offering insights into the broker's efficiency under high load scenarios. Similarly, [PERSON] et al. [11] developed a benchmarking methodology for MQTT brokers, providing stress test data to compare different implementations. [PERSON] et al. [12] conducted a comparative analysis of performance measurements by stress-testing MQTT brokers, while [PERSON] et al. [13] introduced the BORDER framework to assess the scalability and fault tolerance of distributed MQTT systems. Additionally, [PERSON] et al. [14] presented an analysis of security protocols for distributed measurement systems (DMS) based on IoT, focusing on performance with constrained hardware and open-source infrastructures. These studies, like our own, focus on providing empirical data and practical insights, demonstrating the effectiveness of MQTT in various IoT settings. In the context of large-scale IoT deployments, it is worth comparing MQTT with other protocols such as lightweight machine-to-machine (LWM2M). While MQTT excels in quickly launching IoT projects with minimal effort, LWM2M offers features more suited for long-term universal infrastructure. LWM2M provides superior device management tools, including connection monitoring, firmware updates, and remote actions on devices. For enterprises managing large numbers of devices sending substantial volumes of data to a central platform, LWM2M might be the preferable choice. However, MQTT's widespread adoption and broader support make it more than adequate for most IoT deployments. [PERSON] et al. [15] conducted a performance assessment of MQTT on Raspberry Pi, analyzing throughput and data transfer times across different devices and evaluating the impact of Denial of Service (DoS) attacks on various brokers. This research extends the findings of [PERSON] et al. [16], who investigated MQTT protocols in a mist computing environment and assessed service quality metrics including power usage and response times. [PERSON] et al. [17] further explored the security requirements and threats in IoT, noting the significant impact of DoS attacks on QoS parameters. [PERSON] et al. [12] examined MQTT broker behavior under high-load conditions, revealing Mosquito's superiority across multiple performance indicators. [PERSON] et al. [18] and [PERSON] et al. [19] further investigated MQTT brokers, focusing on node clustering and comprehensive monitoring through dynamic dashboards that provide real-time statistics for cluster nodes and connections. Comparative studies have highlighted MQTT's performance advantages in certain scenarios. For example, [PERSON] and [PERSON] [20] compared MQTT with CoAP, demonstratingthat MQTT performs better in real-time data exchange scenarios due to its lower overhead. Similarly, [PERSON] and [PERSON] [21] found that MQTT outperformed HTTP in terms of bandwidth usage and response time in IoT applications. However, it is important to note that these advantages are context-dependent and may not apply uniformly across all IoT use cases. In terms of protocol comparison, [PERSON] [22] provided an analysis of MQTT against other IoT protocols, highlighting its reliability in high-traffic networks but also pointing out limitations like higher latency and bandwidth consumption. [PERSON] and [PERSON] [23] extended this by offering a survey of MQTT's use in machine-to-machine and IoT systems, comparing it with other protocols. [PERSON] [24] examined scalability challenges within MQTT, identifying potential bottlenecks in the publish/subscribe model and suggesting strategies such as clustering and broker federation to enhance reliability. [PERSON] et al. [25] proposed a distributed broker architecture using a ring topology for reliable, low-latency communication, particularly suitable for real-time services in smart cities. [PERSON] et al.