## 4 Performance Modeling of the IASF-IoT Framework
### Sensitivity Analysis  
To account for potential variations in real-world scenarios, a sensitivity analysis was conducted by varying key parameters within reasonable ranges:  
* Processing power: 40 MHz to 120 MHz. * Memory: 32 MB to 128 MB. * Security overhead: 5 KB to 20 KB. * Frequency of security operations: 3 to 12 per hour. The results of this analysis suggest that  
* Processing impact remains below 0.05% across all scenarios. * Memory usage stays under 0.1% in all cases. * Energy consumption varies between 0.3 mAh to 1.5 mAh per day. * Added latency ranges from 0.025 to 0.1 s per operation. These ranges provide a more comprehensive view of the framework's potential performance under different conditions, while still indicating generally low resource utilization. These results have several important implications for the potential deployment of the IASF-IoT framework. The projected minimal resource usage suggests that the framework might be scalable to a wide range of IoT devices, including those with severe resource constraints. This scalability could be crucial for the framework's adoption across diverse IoT ecosystems. The low projected energy impact indicates that the framework might be suitable for long-term deployment in battery-powered devices, a critical factor in many IoT applications where frequent battery replacement is impractical or costly. Figure 3: Energy consumption and network latency impact. Note: the energy consumption impact is scaled by a factor of 10 for visibility. The actual projected daily consumption is 0.6864 mAh. From a user experience perspective, the projected negligible impact on processing power and network latency suggests that the framework might not noticeably affect the responsiveness of IoT devices. This could be particularly important in applications where real-time data processing and transmission are essential, such as in healthcare monitoring or industrial control systems. The model also provides a basis for adapting the framework to different IoT scenarios. By adjusting parameters such as the frequency of security operations or the size of security overhead, the framework could potentially be fine-tuned to meet the specific requirements of various IoT applications while maintaining optimal performance. While these projected results are promising, it is important to note that real-world performance may vary depending on the specific IoT device, network conditions, and security threats encountered. Scalability is another crucial factor that could affect these results. As the number of IoT devices in a network increases, the cumulative impact of the framework on the overall system performance may become more significant. For instance, in large-scale deployments, the slight increase in network latency for each device could potentially compound, leading to more noticeable delays in data transmission across the network. Similarly, the energy consumption, while projected to be minimal for a single device, might have a more substantial impact when considering the power requirements of an extensive IoT ecosystem. Future research should focus on validating these theoretical results in diverse IoT environments, exploring the framework's performance under various scales of deployment, and investigating ways to further optimize its efficiency, particularly for ultra-low-power devices or in bandwidth-constrained networks. This research should also consider the framework's adaptability to different network topologies and its performance in heterogeneous IoT environments. The integration of robust security measures in IoT devices often raises concerns about their impact on device performance, energy consumption, and overall system efficiency. To address these concerns and validate the viability of the IASF-IoT framework, a comprehensive performance model has been developed. This model assesses the framework's impact on critical operational parameters of IoT devices, ensuring that the enhanced security does not compromise the devices' primary functions or user experience.