## 7 Conclusions  
In this paper, we addressed the communication network types and communication technologies used in NMGs. We evaluated papers that address QoD measurement of NMG control data. These papers measured one-way delay using either simulation tools or real-life testbeds. There are two main points that limit the realism of QoD measurement in current papers. First, NMG are designed to transfer control data in bidirectionally so that the RTT measurement yields a better understanding of data exchange between NMG endpoints. Second, simulation tools provide a partial representation of real-life scenarios in NMGs.  
To further investigate the effect of background traffic on the QoD of NMG control data, this paper addressed the RTT measurements in NMGs using a real hardware testbed. We injected various levels of background traffic into the communication network. In summary, we concluded that high-variance in background traffic, caused by TCP-based VS, led to the RTTs of NMG control data surpassing industrial requirements by more than 25 times.  
The results of this paper have significant consequences for sustainable development in energy systems. By analysing the impact of various levels of background traffic on QoD of NMG control data, this paper highlights the need for optimised communication networks in NMGs. The empirical evaluation using the real hardware NMG testbed presents tangible evidence supporting the implementation of robust communication networks that ensure reliable communication between NMG endpoints. Enhanced QoD in NMGs enables the effective integration of renewables, which is crucial for achieving net-zero carbon targets. As renewable integration in NMGs increases, optimised communication networks become 419 essential to facilitate key functionalities such as effective power-sharing, improved NMG controller performance, and optimal NMG operations. These improvements strengthen the role of NMGs within sustainable energy systems, supporting both environmental sus-tainability and economic development through more reliable and resilient power systems.  
Conceptualization, Y.E.K. and R.d.F.; methodology, Y.E.K. and R.d.F.; software, Y.E.K.; validation, Y.E.K. and R.d.F.; formal analysis, Y.E.K. and R.d.F.; investigation, Y.E.K. and R.d.F.; resources, R.d.F.; data curation, Y.E.K.; writing--original draft preparation, Y.E.K. and R.d.F.; writing--review and editing, Y.E.K. and R.d.F.; visualization, Y.E.K. and R.d.F.; supervision, R.d.F.; project administration, R.d.F.; funding acquisition, R.d.F. All authors have read and agreed to the published version of the manuscript.  
**Funding:** This publication emanated from research conducted with the financial support of Taighde Eireann under Grant numbers 18/CRT/6222, 15/SIRG/3459 and 13/RC/2077_P2. For the purpose of open access, the author has applied a CC BY public copyright license to any author-accepted manuscript version arising from this submission.  
**Institutional Review Board Statement:** Not applicable.  
**Informed Consent Statement:** Not applicable.  
**Data Availability Statement:** Datasets are available on request.  
**Acknowledgments:** The first author completed his placement at the Electricity Supply Board (ESB) in Ireland, where he worked on smart grids and networked microgrids as a member of the Strategy, Innovation, and Transformation (SIT) team. The authors thank [PERSON] for hosting the first author during his placement with the ESB.  
**Conflicts of Interest:** The authors declare no conflicts of interest.