## 7 Conclusions and Future Work  
This review paper has explored the state of the art in IIoT-Edge networks for high-availability, consistent-performance-demanding environments like the next-generation offshore wind farms, or \"wind farms of tomorrow\". The paper illustrated how Industry 4.0 technologies such as IIoT, Edge computing, and virtualization are integrated into the design of offshore wind farm data acquisition systems. The paper, then examined key protocols involved in transmitting data within these systems that support offshore wind farm operations. Although traditional communication networks could facilitate data transfer in next-generation offshore wind farms, they come with significant drawbacks: high deployment costs, complex management at scale, difficulty in configuration and maintenance due to their distributed nature, and vendor lock-in that hampers innovation and customization. This paper discussed two pivotal technologies--SDN (software-defined networking) and NFV (network function virtualization)--that will revolutionize IIoT-Edge data-acquisition systems by making networks more software-defined, programmable, and vendor-neutral. Unlike traditional networks, SDN/NFV-based networks facilitate dynamic, centralized control, allowing network administrators to rapidly diagnose and rectify faults, as well as to adapt the network to meet specific business intents, objectives, or industrial service-level agreements. Moreover, these networks boast significantly faster convergence times, achieving rates of 100 us, compared to the 10-30 ms typical of traditional networks. Despite their potential, software-defined IIoT-Edge networks face performance, reliability, security, and scalability challenges that may impede their implementation. This review has addressed these challenges and highlighted various mitigation strategies such as redundancy and load balancing, fault detection and recovery, traffic engineering with Quality of Service (QoS) policies, network isolation, and segmentation. Finally, the paper reviewed AI-driven self-X (self-configuring, self-healing, and self-optimizing) approaches that not only autonomously manage and optimize network traffic but also proactively tackle performance, security, reliability, and scalability challenges before they affect operations. This development is increasingly vital for addressing the complex and growing demands of software-defined IIoT-Edge networks, suggesting a pivotal direction for future research in creating more resilient networking architectures. These strategies are vital for fostering robust, reliable, and high-performing software-defined IIoT-Edge networks that can fully support the sophisticated requirements of next-generation offshore wind farms. As a main advantage, software-defined networks provide dynamic reconfiguration capabilities, allowing the communication network to adapt to changing conditions and demands in real time. Such flexibility will have a crucial role in supporting the anticipated developments in offshore renewable energy systems, consisting of (multiple) large-scale wind farms and other renewable energy generation technologies (e.g., wave and floating solar photovoltaic power), offshore electrolyzers, electricity and hydrogen storage systems, etc. The deployment of software-defined IIoT-Edge networks to facilitate a more resilient and adaptable cyber-physical energy system that includes heterogeneous energy conversion, storage, and transport technologies in a harsh offshore environment represents a promising future research direction. Conceptualization, A.M.; Methodology, A.M., E.F., M.G. ([PERSON]); Resources, R.S., M.G. ([PERSON]); Writing--original draft preparation, A.M.; Writing--review and editing, A.M., E.F., R.S., M.G. ([PERSON]), M.G. ([PERSON]); Visualization, A.M.; Supervision, E.F., M.G. ([PERSON]), M.G. ([PERSON]); Funding acquisition, M.G. ([PERSON]). All authors have read and agreed to the published version of the manuscript.