## 5 Results and Discussion
### Experimental Details
(**b**) AARNET throughput at 5 GB bandwidth TCP. (**c**) AARNET throughput at 10 GB bandwidth TCP. Figure 9: AARNET throughput at different bandwidths UDP. (**a**) AARNET throughput at 2 GB bandwidth UDP. (**b**) AARNET throughput at 5 GB bandwidth UDP. (**c**) AARNET throughput at 10 GB bandwidth UDP. Figure 11: DFN throughput at different bandwidths UDP. (**a**) DFN throughput at 2 GB bandwidth. UDP. (**b**) DFN throughput at 5 GB bandwidth UDP. (**c**) DFN throughput at 10 GB bandwidth UDP. Figure 10: DFN throughput at different bandwidths TCP. (**a**) DFN throughput at 2 GB bandwidth TCP. (**b**) DFN throughput at 5 GB bandwidth TCP. (**c**) DFN throughput at 10 GB bandwidth TCP. In the last test case, we do not fix the same bandwidth of each controller. We randomly assign different bandwidths to each controller. The result generated in this test case is changed every time, and there is much variation in the throughput compared to the fixed bandwidth test cases. It shows a need to understand this situation further and find methods to stabilize the system's throughput. After analyzing the whole system for the delay between controllers, we can say that controller placement is critical in these topologies. ## 6 Conclusions

In conclusion, the use of SDN to address heterogeneity the in IoT networks shows great potential for improving QoS and enhancing security. In this study, we developed a framework that converts heterogeneous controllers into homogeneous ones based on their service rate, which was tested using the RA FCFS algorithm. Our experiments showed that when the bandwidth is shared equally across all controllers, there is less throughput variation. However, further study is required to investigate different bandwidth allocations to controllers, stability of throughput, and other affected parameters. The inclusion of delay and bandwidth as metrics may also enhance the framework's performance. As for future work, we suggest investigating the delay between controllers, testing the framework's performance in actual IoT networks, comparing it with other similar SDN-based methods, developing bandwidth-on-demand solutions, addressing the central point of failure issue, implementing traffic-specific flow, and studying the framework for other parameters of QoS. These efforts would help advance the framework and its potential applications in the field. Conceptualization, A.Z. and FS. ; methodology, A.Z. and FS. ; software, H.J.S. ; validation, A.Z., F.S., M.A. and H.J.S. ; formal analysis, A.O.I, M.A. and M.E. ; investigation, M.A. and M.E. ; resources, A.O.I, M.A. and M.E. ; writing--original draft preparation, A.Z. and FS. ; writing--review and editing, A.Z., F.S. and H.J.S. ; visualization, A.O.I, M.A. and M.E. ; supervision, F.S. ; project administration, A.O.I, M.A. and M.E. ; funding acquisition, M.A. and M.E. All authors have read and agreed to the published version of the manuscript. This project is funded by Princess Nourah bint Abdulrahman University Researchers Supporting Project number (PNURSP2023R383), Princess Nourah bint Abdulrahman University, Riyadh, Saudi Arabia. Not applicable. This work was supported through Princess Nourah bint Abdulrahman University Researchers Supporting Project number (PNURSP2023R383), Princess Nourah bint Abdulrahman University, Riyadh, Saudi Arabia. The authors declare no conflict of interest. Figure 12: AARNET throughput at 10 GB bandwidth TCP/UDP with bandwidth utilization technique. (**a**) AARNET throughput at 10 GB bandwidth TCP with bandwidth utilization technique. (**b**) AARNET throughput at 10 GB bandwidth UDP with bandwidth utilization technique. ## References

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