arXiv subjects

Vasileios Theodorou

Publications and source records attributed to Vasileios Theodorou.

6 recordsLinked to original sources

arXiv2026

AI-Native Orchestration in the 6G Continuum: Evolving Operator Platforms with Agentic AI

As Sixth-Generation (6G) networks evolve towards a seamless Cloud-Edge-Internet of Things (IoT) continuum, autonomous orchestration across distributed compute and network domains becomes critical. Future 6G services will span multiple administrative and operator domains, making federation essential for ubiquitous, ultra-low-latency service continuity beyond individual footprints. This complexity demands AI-native mechanisms supporting intent-driven automation and closed-loop management. While the GSMA Operator Platform (OP) provides the architectural blueprint for multi-operator federation and network capability exposure, and the ETSI Software Development Group OpenOP (SDG OOP) offers a primary open-source reference implementation, current frameworks are limited by stateless API interactions and lack native intelligence. This paper proposes an Agentic-driven Intelligence extension for the GSMA OP architecture, using the OOP as the reference framework. We introduce an AI-native orchestration layer where autonomous agents manage persistent service contexts and enable closed-loop control via CAMARA APIs. By integrating a Declarative Monitoring and Alerting System (DeMAS) into the OOP stack and establishing a decentralised agent negotiation protocol, the proposed architecture enables real-time, intent-driven resource optimisation and autonomous cross-domain conflict resolution across federated domains. We validate our approach through a representative 6G use case involving Ultra-Reliable Low-Latency Communication (URLLC) and enhanced Mobile Broadband (eMBB) coexistence, demonstrating that an agentic OP framework autonomously reconciles stringent Service Level Agreements (SLAs) while enhancing infrastructure energy efficiency. Our findings establish a scalable blueprint for cross-domain Network-as-a-Service (NaaS) models that align standardised exposure with 6G autonomous requirements.

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arXiv2026

Towards Secure and Interoperable Data Spaces for 6G: The 6G-DALI Approach

The next generation of mobile networks, 6G, is expected to enable data-driven services at unprecedented scale and complexity, with stringent requirements for trust, interoperability, and automation. Central to this vision is the ability to create, manage, and share high-quality datasets across distributed and heterogeneous environments. This paper presents the data architecture of the 6G-DALI project, which implements a federated dataspace and DataOps infrastructure to support secure, compliant, and scalable data sharing for AI-driven experimentation and service orchestration. Drawing from principles defined by GAIA-X and the International Data Spaces Association (IDSA), the architecture incorporates components such as federated identity management, policy-based data contracts, and automated data pipelines. We detail how the 6G-DALI architecture aligns with and extends GAIA-X and IDSA reference models to meet the unique demands of 6G networks, including low-latency edge processing, dynamic trust management, and cross-domain federation. A comparative analysis highlights both convergence points and necessary innovations.

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arXiv2026

Towards Scalable Federated Container Orchestration: The CODECO Approach

This paper presents CODECO, a federated orchestration framework for Kubernetes that addresses the limitations of cloud-centric deployment. CODECO adopts a data-compute-network co-orchestration approach to support heterogeneous infrastructures, mobility, and multi-provider operation. CODECO extends Kubernetes with semantic application models, partition-based federation, and AI-assisted decision support, enabling context-aware placement and adaptive management of applications and their micro-services across federated environments. A hybrid governance model combines centralized policy enforcement with decentralized execution and learning to preserve global coherence while supporting far Edge autonomy. The paper describes the architecture and core components of CODECO, outlines representative orchestration workflows, and introduces a software-based experimentation framework for reproducible evaluation in federated Edge-Cloud infrastructure environments.

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arXiv2023

EdgeDS: Data Spaces enabled Multi-access Edge Computing

The potential of Edge Computing technologies is yet to be exploited for multi-domain, multi-party data-driven systems. One aspect that needs to be tackled for the realization of envisioned open edge Ecosystems, is the secure and trusted exchange of data services among diverse stakeholders. In this work, we present a novel approach for integrating mechanisms for trustworthy and sovereign data exchange, into Multi-access Edge Computing (MEC) environments. To this end, we introduce an architecture that extends the ETSI MEC Architectural Framework with artifacts from the International Data Spaces Reference Architecture Model, accompanied by processes that automatically enrich Edge Computing applications with data space capabilities in an as-a-service paradigm. To validate our approach, we implement an open-source prototype solution and we conduct experiments that showcase its functionality and scalability. To our knowledge, this is one of the first concrete architectural specifications for enabling data space features in MEC systems.

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arXiv2021

MEDAL: An AI-driven Data Fabric Concept for Elastic Cloud-to-Edge Intelligence

Current Cloud solutions for Edge Computing are inefficient for data-centric applications, as they focus on the IaaS/PaaS level and they miss the data modeling and operations perspective. Consequently, Edge Computing opportunities are lost due to cumbersome and data assets-agnostic processes for end-to-end deployment over the Cloud-to-Edge continuum. In this paper, we introduce MEDAL, an intelligent Cloud-to-Edge Data Fabric to support Data Operations (DataOps)across the continuum and to automate management and orchestration operations over a combined view of the data and the resource layer. MEDAL facilitates building and managing data workflows on top of existing flexible and composable data services, seamlessly exploiting and federating IaaS/PaaS/SaaS resources across different Cloud and Edge environments. We describe the MEDAL Platform as a usable tool for Data Scientists and Engineers, encompassing our concept and we illustrate its application though a connected cars use case.

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arXiv2019

VirtuWind - An SDN- and NFV-based Architecture for Softwarized Industrial Networks

VirtuWind proposes the application of Software Defined Networking (SDN) and Network Functions Virtualization (NFV) in critical infrastructure networks. We aim at introducing network programmability, reconfigurability and multi-tenant capability both inside isolated and inter-connected industrial networks. Henceforth, we present the design of the VirtuWind architecture that addresses the requirements of industrial communications: granular Quality of Service (QoS) guarantees, system modularity and secure and isolated per-tenant network access. We present the functional components of our architecture and provide an overview of the appropriate realization mechanisms. Finally, we map two exemplary industrial system use-cases to the designed architecture to showcase its applicability in an exemplary industrial wind park network.

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