## 7 Conclusions  
This paper presented the application-aware (AA) approach, which adopted the IT-SDN framework on top of the TSCH technology. The proposed approach dynamically changes the current scheduling to adapt to the application's QoS requirements. The AA approach isolates the different traffic types and supports the network scalability using shared timeslots. We employed two different strategies to evaluate the AA approach: (i) comparing it with the ATI approach, which assigns a single timeslot per application, and (ii) comparing the obtained results with the application's QoS requirements in terms of \begin{table}
\begin{tabular}{p{113.8 pt} p{113.8 pt} p{113.8 pt}} \hline \hline Evaluation & AA Approach Vs Application’s & Number of Applications \\ Metric & QoS Requirements & **Number of Applications** \\ \hline \multirow{4}{*}{Data delivery rate} & Ensured of up to 225 nodes & One App \\ \cline{2-3}  & Ensured of up to 196 nodes & Two Apps \\ \cline{2-3}  & Ensured of up to 196 nodes & Three Apps \\ \cline{2-3}  & Ensured of up to 144 nodes & Four Apps \\ \hline \multirow{4}{*}{Data delay} & Ensured of up to 144 nodes & One App \\ \cline{2-3}  & Ensured of up to 144 nodes & Two Apps \\ \cline{2-3}  & Ensured of up to 100 nodes & Two Apps \\ \cline{2-3}  & Ensured of up to 100 nodes & Three Apps \\ \cline{2-3}  & Ensured of up to 144 nodes & Four Apps \\ \hline \multirow{4}{*}{Data delay} & Ensured of up to 144 nodes & Four Apps \\ \cline{2-3}  & Ensured of up to 144 nodes & Four Apps \\ \hline \multirow{4}{*}{Data delay} & Ensured of up to 100 nodes & Two Apps \\ \cline{2-3}  & Ensured of up to 100 nodes & Three Apps \\ \cline{2-3}  & Ensured of up to 64 nodes & Four Apps \\ \hline \multirow{4}{*}{Data delivery rate} & Ensured of up to 100 nodes & Three Apps \\ \cline{2-3}  & Ensured of up to 225 nodes & Four Apps \\ \hline \hline \end{tabular}
\end{table} 
Table 6: AA approach versus application’s QoS requirements. delivery rate and delay. We considered up to four applications and network sizes of up to 225 nodes. Furthermore, we adopted six different scenarios to evaluate the impact of both MCR and DTR parameters on the network performance. The evaluation process took into account both the control and data planes, confirming the effectiveness of the AA approach. In comparison with the ATI approach, the AA approach increased the delivery rate by up to 28% and decreased the delay by up to 57%. Furthermore, our approach was capable of ensuring the application's QoS requirements for the different network sizes. In future work, we plan to investigate the impact of other parameters on network performance, such as the difference rate and the application's requirements. Conceptualization, T.S., R.M.S. and C.B.M. ; methodology, T.S., R.M.S. and C.B.M. ; software, T.S. ; validation, T.S. and R.M.S. ; formal analysis, T.S. and R.M.S. ; investigation, T.S. ; resources, T.S., R.M.S. and C.B.M. ; data curation, T.S. ; writing--original draft preparation, T.S. ; writing--review and editing, T.S., R.M.S. and C.B.M. ; visualization, T.S. ; supervision, R.M.S. and C.B.M. All authors have read and agreed to the published version of the manuscript. This research was financed in part by the Coordenacao de Aperfeicoamento de Pessoal de Nivel Superior-Brasil (CAPES)--Finance Code 001--and the FAPESP project #2022/07523-8. [PERSON] is supported by the CNPq fellowship #311687/2022-9. Not applicable. The authors declare that they have no known competing financial interest or personal relationships that could have influenced the work reported in this paper. The following abbreviations are used in this manuscript: