# A Novel SDWSN-Based Testbed for IoT Smart Applications
## 5 Conclusions  
This paper demonstrated physical network implementation using commercial sensor node TI CC2538 with a focus on node capabilities and ability to interact with network operation requirements. Physical network implementation scenarios with a focus on RSSI data were designed to reflect the mobility of the network with the use of rechargeable batteries. This reflected the RSSI values when the node departed from the network and thus the distances were obtained. Also, the change in transmission power indicated the change in RSSI values for indoor and outdoor scenarios. The router/gateway node capacity was tested based on packet loss, indicating slightly more packet loss compared to the virtual network due to real-world factors such as obstacles. This promotes the importance of pretesting on the virtual platform and of enabling interaction between virtual and physical networks. In addition, another use case related to the nodes' distribution on the ground was structured for physical implementation with a focus on stationary scenarios. The proposed physical network topology enables node reconfigurability via virtualization wherein the source code within the virtual platform can be modified, allowing the node to perform various functions depending on the designed scenario. This can be achieved by using the over-the-air debugging (OAD) functionality associated with the proposed TI LaunchPad modules used in this paper. A small-scale network testbed was examined, followed by a large-scale network testbed, using the SensorTag CC1352R LaunchPad, development boards, and Raspberry Pi in order to evaluate network performance variables such as packet delivery rate and consumed energy. The results of physical testing were then compared to the results of simulation testing to validate the proposed concept. This work's limitation is the deployment of the physical network as based on the designed use case. Herein, for future work, the physical network can be implemented on a road to reflect a vehicular network use case as well as in a forest to reflect trap monitoring.  
Figure 27: Packets received by coordinators (gateways) from distributed leaf nodes during physical ground network communication.  
**Author Contributions:** Conceptualization, D.Z.A.-H. and P.A.K.; methodology, D.Z.A.-H. and P.A.K.; software, D.Z.A.-H. and P.A.K.; validation, D.Z.A.-H.; investigation, D.Z.A.-H., P.A.K. and P.H.J.C.; writing--original draft preparation, D.Z.A.-H.; writing--review and editing, D.Z.A.-H., P.A.K. and P.H.J.C.; visualization, D.Z.A.-H. All authors have read and agreed to the published version of the manuscript.  
**Funding:** This research received no external funding.  
**Data Availability Statement:** Not applicable; this study did not report any data.  
**Acknowledgments:** The authors would like to thank the Department of Electrical and Electronic Engineering in the School of Engineering, Computer and Mathematical Sciences at Auckland University of Technology for providing hardware and advice for this research project.  
**Conflicts of Interest:** The authors declare no conflict of interest.