Unmanned Aerial Vehicles (UAVs) are increasingly deployed in inspection and monitoring missions, yet onboard computation and communication impose significant energy burdens that limit flight time and operational scope. In this work, we introduce a novel, blockchain-enabled framework-grounded in the Distributed Autonomous Organization (DAO) paradigm-for orchestrating distributed analytics across a swarm of UAVs. Leveraging the OASEES project's smart-contract architecture, each drone embeds a Metrics Module for real-time power monitoring, a Behavioral Module for adaptive control, and a Blockchain Agent that autonomously proposes, votes on, and executes collective decisions. Three concurrent threads-Proposal Trigger, Voting, and Action Execution-enable fully decentralized governance of swarm behavior: from detecting critical energy thresholds and formulating swarm-wide conservation maneuvers, to executing approved strategies across all members. We validate our framework in a UAV-based infrastructure inspection scenario, employing a YOLOv5 object-detection pipeline to classify four corrosion classes on a telecommunications mast under three video-capture modalities (short-distance, long-distance, and horizontally concatenated streams). Across all configurations, our system achieves near-perfect precision, recall, and mean Average Precision (mAP50-95$\approx 0.995$), demonstrating both the efficacy of distributed workload inference and the feasibility of treating a single drone as a multi-feed processor. These results underscore the potential of DAO-driven UAV swarms for energy-aware, resilient aerial analytics, and pave the way for fully decentralized 5G/6G-enabled airborne networks.

According to the EU State of Cybersecurity report by the European Union Agency for Cybersecurity (ENISA), the number of cybersecurity-related incidents will increase by 24 percent by 2025, with ransomware and DoS/DDoS attacks being the most common. The emergence of new threats [1] and the consolidation of existing ones require doubling of efforts in proactive prevention and a decisive increase in research dedicated to cybersecurity. CyberNEMO (End-to-end Cybersecurity to NEMO meta-OS) project emerges as an evolution of the NEMO (Next Generation Meta Operating System) platform, designed to provide a secure, trustworthy, and robust execution environment across the IoT-Edge-Cloud computing continuum. Leveraging NEMO modular meta-operating system (mOS) framework, CyberNEMO introduces advanced cybersecurity and privacy-preserving mechanisms, emphasizing Zero Trust principles. This paper presents the CyberNEMO architecture, details its core innovative technologies, and describes its validation strategy through diverse living labs-including Smart Energy, Smart Water, Smart Manufacturing, Healthcare, Multimedia Distribution, and Smart Farming scenarios-demonstrating end-to-end cybersecurity and real-time threat mitigation capabilities, aligned with Europe's strategic cybersecurity goals.

Communications play a fundamental role in the economic and social well-being of the citizens and on operations of most of the critical infrastructures (CIs). Extreme weather events, natural disasters and criminal attacks represent a challenge due to their increase in frequency and intensity requiring smarter resilience of the Communication CIs, which are extremely vulnerable due to the ever-increasing complexity of the architecture also in light of the evolution towards 5G, the extensive use of programmable platforms and exponential growth of connected devices. In this paper, we present the aim of RESISTO H2020 EU-funded project, which constitutes an innovative solution for Communication CIs holistic situation awareness and enhanced resilience.

The eHealth constitutes the largest wave of change in the sector of healthcare. In this context, Internet of Things is of immense importance since connected data would facilitate treatment with more efficiency and comprehensive knowledge and would "act" as preventive medicine. Monitoring health data and making them ubiquitously accessible to predefined and authorized healthcare personnel are shared through various IoT platforms, which usually lack IoT-protocol-interoperability. In this paper, we present the impact of IoT systems in the eHealth services' evolution and we introduce the VICINITY ecosystem solution. Its high-level architecture is analyzed and several security considerations are offering "thought for food".

Enhancing trust among service providers and end-users with respect to data protection is an urgent matter in the growing information society. In response, CREDENTIAL proposes an innovative cloud-based service for storing, managing, and sharing of digital identity information and other highly critical personal data with a demonstrably higher level of security than other current solutions. CREDENTIAL enables end-to-end confidentiality and authenticity as well as improved privacy in cloud-based identity management and data sharing scenarios. In this paper, besides clarifying the vision and use cases, we focus on the adoption of CREDENTIAL. Firstly, for adoption by providers, we elaborate on the functionality of CREDENTIAL, the services implementing these functions, and the physical architecture needed to deploy such services. Secondly, we investigate factors from related research that could be used to facilitate CREDENTIAL's adoption and list key benefits as convincing arguments.

This paper focuses on the presentation of a simulation framework, prototyping environment and demonstration scenario developed in the context of the Self-NET Future Internet mechanisms. Self management mechanisms of Future Internet elements are introduced, which incorporate the Monitoring, Decision making and Execution cognitive cycles. Such functionality enables the envisaged elements to sense their environment and adapt to it dynamically. The scenario described here is the one related to coverage and capacity optimization. The cognitive framework of the network elements and the implemented Future Internet mechanisms are presented, along with the findings originated by the performance measurements on the developed prototypes. In order to enable the evaluation of the proposed schemes, a set of assessment metrics are identified and the scenario is fragmented in simpler test cases.

In future distributed systems, the appearance of mechanisms that should be able to realize robust, predictable and self-adaptive behaviour for existing networked systems can be seen as a critical enabler for further growth. If, in addition, such mechanisms are related to options for achieving cooperation of several (heterogeneous) network elements and/or domains, with the aim of reducing energy wastage and minimizing energy consumption, then the challenge becomes critical. To this aim, the present paper discusses an innovative approach, focusing upon the development of energy-aware distributed and cooperating systems for monitoring and control, centred on appropriate wireless sensor networks for the provision of radio and environmental context information. In particular, we discuss the concept of a “Self-Growing Network” that is able to efficiently incorporate autonomic and collaborative capabilities, intending to increase the level of the global network energy efficiency by using cognition-based features. Self-growing capabilities are enablers for a novel type of network flexibility. They allow optimising a heterogeneous collection of network nodes or sub-networks to be dedicated to a specific optimisation “purpose” temporarily and on-demand.

In next generation systems and networks, the incorporation of mechanisms achieving robust, predictable and self-adaptive behavior with minimum cost will be a key requirement. Towards this goal we introduce the notion of the "self-growing network". The latter, in its initial deployment stage, is limited to a single dedicated purpose (energy-efficient networking, spectrum efficient communications, control and surveillance use, etc) but can evolve/grow into a multi-purpose, versatile infrastructure, that serves a broader range of applications by utilising combinations of self-x and cooperating features.

In order to enable rapid and cost-effective deployment of WiMAX networks, relay technology which does not require backhaul line, can be considered as an essential feature for performing a successful business development. In the scope of a proposed Multi-Hop relay network architecture, (based on the recently developed IEEE 802.16j standard in order to enhance throughput, network coverage and capacity density), we provide an essential description of the Relay Station Software architecture design (PHY and MAC layers architecture), as it has been proposed by the REWIND European Research Program. The corresponding relay node is based on a highly integrated SoC device, which incorporates all baseband processing (PHY, MAC and CS), networking and control processors required for the relay station functionality. Thus, the Relay node software shall run all the PHY, MAC, scheduler and networking functionalities, required to operate a complete BS with relay functionality, and to integrate the node into the relay network.

We discuss a ldquoself-managementrdquo concept, suitable for the description of autonomic spectrum reallocation operations through dynamic resource allocation and control processes, for an effective realization of the Future Internet (FI) vision. We introduce a specific targeted methodology, in the form of the Generic Cognitive Cycle Model, including three distinct and separate processes (i.e. Monitoring, Decision Making and Execution), known as the ldquoMDErdquo model. We then present a fundamental use-case of practical interest, i.e. relevant to the dynamic spectrum re-allocation for efficient use of traffic in a modern wireless network, to avoid (or to overcome) congestion phenomena affecting network performance. The analysis is based on high autonomy of network elements to allow distributed management, fast decisions, and continuous local optimization.