# Multiple Mobile Sinks for Quality of Service Improvement in Large-Scale Wireless Sensor Networks
## 6 Conclusions  
This paper investigated the impact of using multiple mobile sinks on network energy efficiency and QoS metrics using a cluster-based routing approach and random mobility patterns.  
More specifically, this type of protocol uses hierarchical routing, which offers good energy conservation and latency time results. Moreover, random mobility models run through the network in the context of a simulated battlefield observation where fast and unexpected events reoccur by getting closer to CHs to reduce power consumption during the transmission phase, reduce delays during data collection and increase the number of packets collected.  
The simulation results obtained demonstrate that the Random Direction mobility model with four sinks has a significant impact on power consumption and QoS metrics. In particular, the EA-CRP and P-LEACH protocols achieve a significant improvement in terms of energy consumption, throughput, and reliability, while the latency time gains better with the LEACH protocol.  
In addition, the simulation results show that RD is more suitable for ISWSN because it maintains good performance in terms of power consumption and all the QoS criteria studied for the large supervised RoI and that one can optimize the number of mobile sinks according to the real-time constraints of the RCSF application and the allocated budget.  
After an in-depth discussion of the current approach limits regarding certain uncertainties in the operation of the mobility models used. We planned for future work to first, investigate the use of mobility traces collected from real-world deployments to create more accurate random mobility models. Secondly, consider a hierarchical routing protocol with random mobility awareness of the sinks to reduce the number of mobile sinks and associated costs while respecting QoS. Finally, optimize the mobility models to ensure they accurately reflect the movement of sinks in realistic WSN applications with QoS constraints. The proposed model may also be applied to numerous real-world engineering problems [61; 62].  
Conceptualization, A.B.Y.; Methodology, A.B.Y. and B.B.G.; Software, A.B.Y. and R.G.; Validation, A.B.Y., S.M., M.A.A. and I.A.; Formal analysis, M.A. ([PERSON]); Data curation, A.B.Y. and M.A. ([PERSON]); Writing--original draft, A.B.Y. and S.M.; Supervision, S.H. All authors have read and agreed to the published version of the manuscript.  
This research received no external funding.  
**Institutional Review Board Statement:** Not applicable.  
**Informed Consent Statement:** Not applicable.  
**Data Availability Statement:** Data and codes are available by open request.  
\begin{table}
\begin{tabular}{c c c} \hline \hline
**Criteria** & **Limitation** & **Potential Solutions/Future Research** \\ \hline \multirow{8}{*}{Multiple mobile sinks Cost} & The use of several mobile sinks in simulation & Consider a hierarchical routing protocol with random mobility awareness of the sinks. The protocol allows dynamic and adaptive coordination between sinks and CHs to optimize routes and reduce the number of mobile sinks and associated costs while respecting important QoS metrics such as delay and coverage. \\  & Random mobility models might not & Conduct empirical studies to optimize the mobility models with machine learning to ensure they accurately reflect the movement of sinks in realistic WSN applications with QoS constraints. \\ \cline{1-1}  & & \\ \cline{1-1}  & & \\ \cline{1-1}  & & \\ \cline{1-1}  & & \\ \cline{1-1}  & & \\ \cline{1-1}  & & \\ \cline{1-1}  & & \\ \cline{1-1}  & & \\ \cline{1-1}  & & \\ \cline{1-1}  & & \\ \cline{1-1}  & & \\ \cline{1-1}  & & \\ \cline{1-1}  & & \\ \cline{1-1}  & & \\ \hline \hline \end{tabular}
\end{table}
Table 3: _Cont._