Introduction

The meta-Network Cluster Controller (mNCC) is a key component within the meta Operating System (meta-OS) of the NEMO project, responsible for managing network connectivity and exposure of performance metrics in multi-cluster and multi-domain environments. Its main function is to act as an interface between the NEMO orchestration layer and the underlying physical infrastructure, providing abstraction of network services and enabling real-time access to network features for the rest of the system components.

Architecture and Components

The mNCC is composed of several modules that integrate advanced management, monitoring and adaptive technology capabilities:

• Intent-Based System (IBS): Translates high-level intents into specific network configurations, allowing users to define connectivity requirements without worrying about the underlying technology. The IBS classifies, translates and executes intents, supporting the continuous integration of new technology adapters through a modular microkernel architecture.

• Network Metrics Exposure (NeMeX): Acts as the northbound interface (NBI) to the mNCC, integrating topology and performance metrics from multiple sources and exposing them through RabbitMQ for consumption by the Meta-Orchestrator and other NEMO components. NeMeX enables advanced real-time network health monitoring and analysis.

• Technology Connectivity Adaptors: These include adapters for technologies such as 5G, TeraFlow SDN Controller and L2SM (Link Layer Secure Microservices), facilitating secure and flexible connection between microservices in different Kubernetes clusters. The L2SM adapter, for example, enables the creation and management of virtual networks between clusters using a gRPC API and custom Kubernetes resources.

• Network Performance Monitoring: Implements Python-based probes to measure latency, throughput, packet loss and other key metrics, integrating this data into the system to support autonomous decision making.

Workflow and Key Functionalities

The mNCC operates on a continuous cycle of network management and exposure:

1. Intent Management: The Meta-Orchestrator sends connectivity intents to the mNCC via RabbitMQ. The IBS classifies these intents and translates them into configurations specific to the available technology adapters (e.g. creation of an L2 VPN with TeraFlow SDN or an inter-cluster virtual network with L2SM).
2. Monitoring and Metrics Exposure: NeMeX collects network metrics from the nodes and links of each cluster, integrating information from Kubernetes and network probes. These metrics are periodically exposed to RabbitMQ, allowing other NEMO components (such as Meta-Orchestrator or CF-DRL) to make decisions based on the current state of the network.
3. Multi-Technology Integration: The mNCC supports the integration of multiple network technologies (5G, SDN, Kubernetes overlay, etc.), enabling unified resource management in heterogeneous and distributed environments.
4. Automation and Scalability: mNCC deployment and management are supported by CI/CD frameworks and automation tools, facilitating scalability and efficient operation in production environments.

Use Case: Inter-Cluster Network Management

A typical use case is the creation of a virtual network between two Kubernetes clusters managed by NEMO:

1. Receiving Intent: Meta-Orchestrator sends an inter-cluster network creation intent.
2. Classification and Translation: The IBS classifies the intent and translates it into a specific configuration for the L2SM adapter.
3. Execution: The L2SM adapter uses a gRPC API to create custom network resources on each cluster, establishing a secure, centrally managed connection.
4. Monitoring: NeMeX collects network metrics from both clusters and exposes them to RabbitMQ, enabling observability and dynamic tuning of connectivity.

Benefits and Future Perspectives

• Abstraction and Simplification: The mNCC abstracts away the complexity of network management, allowing users to define high-level connectivity requirements without worrying about the underlying technology.

• Interoperability and Flexibility: The mNCC’s modular architecture facilitates the integration of new network technologies and the management of multi-domain environments.

• Advanced Monitoring: Real-time exposure of network metrics enables dynamic optimisation and early detection of problems.

• Automation and Security: The mNCC supports automated deployments and advanced security mechanisms, such as the establishment of encrypted connections or secure workload migration.

As a continuation, the CyberNEMO project is defining Zero-Thrust Network Access (ZTNA), a network management component that evolves from mNCC by providing secure segmentation of content in microservices and the management and monitoring of network access. This component includes other advantages such as log attestation or the use of metrics calculated with AI… But that is another story.

Conclusion

The mNCC is a fundamental component in the NEMO meta-OS, providing advanced, flexible and automated network management in multi-cluster and multi-technology environments. Its modular architecture, based on intents and technology adapters, positions it as a robust and scalable solution for network orchestration in the edge-cloud continuum era.

Video link: https://youtu.be/UkOsPaxf5mw

Text: The Smart Media XR Pilot used the Next Generation Meta Operating System  (Nemo Meta OS) framework to enhance the boundaries of user involvement in XR systems and applications for the public in the context of Historical and Educational applications.

During the pilots two XR experiences were enhanced using cloud computing resources and AI/ML processing. The whole IoT-Edged-Far Edge-Cloud pipeline available from NEMO was used in order to integrate it into two VR systems and presentations.
The pilots took place on the 24/6/2025 at the Hellenic Cosmos Cultural Center.

The firt VR application that was enhanced was the Head Mounted Display VR experience of a visit at the Ancient Workshop of the Sculpturer Phidias. For this the biodata of the user was captured using an Smart Watch IoT device in order to have the application and the museum staff respond to any discomfort and nausea of the user. As it is widely known the usage of head Mounted Display can cause nausea and discomfort , which are very difficult to spot by external observation. Therefore the cloud computations, ML models and resource components of NEMO were used to analyze in realtime the biodata of the user and understand his status.

The second VR application that was enhanced, was a large scale VR Theatre Dome show. The Hellenic Cosmos is one of the few Museums worldwide that features realtime Dome shows with real navigation and presentation form a person. During the trial Nemo resources and ML models were used to capture onsite images of the Museumeducator that drive the experience and understand his gestures and need in navigation and external communication. During the pilot the museumeducator could pilot the VR show just using gestures and signal information to the museum reception about the status of the show all while he was presenting live in from of the audience.

The completion of these trials complete the use case analysis of Trial 5.5 as part of the NEMO project. The NEMO project has the priviledge to be the only project to host use cases targeting Culture and Media among all the EU funded projects.

What is mNCC and why is it important for the connectivity of the future?

In an increasingly connected world, where we work, play and communicate via the internet and mobile networks, the way we manage and control those connections becomes critical. This is where the mNCC, or meta-Network Cluster Controller, comes in, a key part of advanced projects such as NEMO, which aims to revolutionise network management in the future.

What does the mNCC do?

Imagine you have several offices, each with its own internet network, and you want them all to work together as if they were one, no matter where they are. The mNCC is like a “conductor” for these networks: it coordinates and controls how they connect to each other, ensuring that everything runs smoothly and efficiently.

Its main job is to unify the management of multiple networks (e.g. those of different companies, cities or even countries), allowing services and applications to run smoothly, no matter what technology or where they are deployed.

Why is this useful?

• Simplifies management: Previously, each network was managed separately, which was complicated and time-consuming. The mNCC allows many networks to be controlled from one place.

• Improves communication: It makes it easier for different devices and services (such as video calls, cloud applications or smart sensors) to communicate with each other, even if they are on different networks.

• Increases security and efficiency: Having centralised control makes it easier to detect and fix problems, as well as protect networks from potential threats.

How does mNCC work in practice?

The mNCC does not work alone: it is part of a larger system called the meta-Operating System (meta-OS), which integrates other tools to monitor, analyse and automate networks. For example, the mNCC can receive a “command” (called an “attempt” or “intent”) to connect two offices and automatically configure everything necessary to make that connection work, even if the networks use different technologies.

In addition, the mNCC monitors network performance (such as speed or stability) and shares that information with other systems so that they can make intelligent decisions, such as moving data to the fastest network or detecting failures before they affect users.

Who is mNCC useful for?

Although mNCC is an advanced technology, its benefits reach all types of users:

• Enterprises: To connect offices, factories or data centres securely and efficiently.

• Telecommunications operators: To manage mobile networks, fibre optics or cloud services more intelligently.

• Smart cities: To coordinate sensors, cameras and public services through a unified network.

Conclusion

The mNCC is a solution that allows multiple networks to be managed and connected as if they were one, simplifying administration, improving communication and making everything work more securely and efficiently. It is a building block for the future of connectivity, where collaboration between different technologies and locations will become increasingly important.

The Smart Media City Pilot used the Next Generation Meta Operating System  (Nemo Meta OS) framework to enhance the boundaries of live media capture and user involvement in a live outdoor race event, providing an effective broadcast, analysis and productivity solution and seeked to enhance user engagement  by offering a Personalized Content Delivery solution using a dedicated app.

During the race, spectators and selected runners captured media content using smartphones, tablets, 360 cameras, and, where available along the running circuit. This incoming content underwent automated processing, annotation, and rendering, with AI/ML models running partially on devices and partially at the edge. A curated selection of this content (Production control was remote in Spain Madrid) is then broadcasted in real time, such as through social media, based on the location of leading runners and notable race events, as identified through automated and user-provided annotations.

Spectators if the Pilot Race enhanced their contributions and interacted with other users in response to specific race incidents. The trial emphasized real-time, user-generated content processing and rendering, leveraging Federated Learning (FL) hosted across IoT nodes (smartphones), edge devices, and cloud infrastructure. AI models were trained to recognize Racing Bib Numbers enabling better identification of runners and their precise positioning within each video stream.

You can add the link to the video: https://youtu.be/SKpcN5UUjJs?si=vUQa7wV4z27q2cJ0