## 4 Development and Validation of the Platform
### Experimental Platform Setup  
To validate the architecture proposal, the experimental setup shown in Figure 3 was deployed using a two-site, geographically distributed design. The setup integrates Edge nodes at both sites, interconnected via secure links, with each site playing a vital role in managing data and running real-time applications. Edge Site 1 hosts a main router (Router 1) that provides access to both the Cloud and two additional servers: one hosting the 5G core and the other responsible for hosting the Edge applications (Edge Server 1). A secure direct connection, protected by a firewall, links Edge Site 1 to Edge Site 2, ensuring safe communication between the two locations. Edge Site 2 similarly features a main router (Router 2) that connects Edge Server 2 to the 5G core network. Both sites are integrated with their respective 5G radio access network (RAN), which operates under an open-source framework (OpenRAN) to facilitate the interoperability and replication of the setup. The RAN setup includes a remote Radio Unit (RU) that supports advanced radio splitting, allowing efficient communication between the Distributed Units  
Figure 3: The hyper-distributed experimental setup, comprising two geographically distanced Edge sites for the development and validation of an IoT-to-Edge-to-Cloud platform. The architecture illustrates the distribution of essential elements, such as the 5G core location, distributed RAN components—CUs (Centralized Units), DUs (Distributed Units), and RUs (Remote Units)—and Edge Servers at both sites. Edge Site 1 and Edge Site 2 are interconnected via secure links, with dedicated firewalls and internal routers to manage network traffic. This configuration allows for real-time data processing and transmission across the IoT, Edge, and Cloud layers, supporting latency-sensitive applications and resilient network connectivity. (DUs) and Centralized Units (CUs). Edge Site 1 features a Baseband Unit (BBU) that is logically composed of a DU and CU, with the DU positioned near the RU to facilitate communication between the RU and the 5G core. The architecture supports various connectivity options between the two sites, including direct fiber connections and more complex network routes that integrate the 5G core. To support the computational requirements of real-time Digital Twin applications, each Edge node is equipped with high-performance processors, powerful RAM, and storage capabilities to handle intensive data processing and AI-driven analytics. As an example, one of the servers used in this experimental setup is configured with an Intel(r) Xeon(r) Gold 6548N 32-Core Processor at 2.80 GHz, paired with 4 \(\times\) 64 GB DDR5 4800 MHz ECC RDIMM server memory and storage based on NVMe technology for faster data access. Additionally, the server supports GPU processing with an NVIDIA T4 GPU, allowing efficient handling of compute-intensive tasks, including machine learning inference and real-time analytics. In terms of communication performance, it is important to note that this network is completely experimental, not commercial, with specific configurations to support research and development. The radio access network at Edge Site 1 is configured with a TDD pattern that has an uplink/downlink slot ratio of 3/7, prioritizing the uplink to better suit the needs of real-time applications that require robust uplink performance. The n40 band operates with a bandwidth of 20 MHz, a 256 QAM modulation, and MIMO 2 \(\times\) 2 on the downlink. Similarly, the n78 band is configured with a bandwidth of 100 MHz, a 64 QAM modulation, and MIMO 2 \(\times\) 2 on the downlink. These configurations facilitate high data throughput and low latency, crucial for maintaining seamless communication between the IoT, Edge, and Cloud layers of the platform. The 5G core in this site deploys seven UPFs to serve different slices, allowing for effective resource allocation and testing across multiple scenarios. The UPF selection is determined by the DNN (Data Network Name) chosen by the UE.