The increasing complexity of healthcare data management requires advanced solutions to ensure privacy, security, and regulatory compliance. Consent management, in particular, is a critical component of patient-centered care in the digital age, as patients need complete control over how their sensitive health information is accessed and used. This paper presents the PAROMA-MED platform, which introduces a user-centric consent management framework designed to improve transparency and trust in healthcare data exchanges. By integrating technologies such as the Fast Healthcare Interoperability Resources (FHIR) standard, the EU Data Space Connector, and an intuitive user interface, PAROMA-MED empowers patients to control their health data. We explore the technical and user interaction aspects of the platform, highlighting how it addresses the challenges of consent management while ensuring regulatory compliance with GDPR. This paper discusses the implications of these technologies for improving healthcare delivery and fostering patient engagement.

In this paper, we present the framework evolution covering key concepts, principles and architectural approach of the EU funded Project PAROMA-MED. The project aims to provide privacy preserving techniques based on a hybrid edge/cloud approach that focuses on the establishment of high degree of trust between federation entities. This in turn introduces a new paradigm in the context of privacy and data protection that can streamline the roles and operations of data subject and data controllers/processors by artifacts in a context that has been aspired as functional GDPR. The approach attempts to create fusion between the flexibility of data driven ecosystems as they are formulated by modern Data Spaces and data protection practices based on trust establishment practices such as Hardware Root of Trust. Considering the fact that 6G prospects provide ample room for radically new approaches and enabling network architectures, this paper continues to elaborate on the project's vision as projected on future networks capabilities.

This paper presents the details of a novel approach, based on edge and advanced privacy preserving solutions, that tries to accelerate the adoption of personal data federation for the benefit of the evolution of valuable advanced AI models. The approach focuses on the establishment of high degree of trust between data owner and data management infrastructure so that consent in data processing is given by means of functional and enforceable options applicable at all levels of workloads and processes. The overall set of solutions will be delivered as an open-source set of implementations in the context of the PAROMA-MED project.

In order to compete for a prominent market share, network operators and service providers should retain and increase the verticals' subscription, catering to their needs in order to differentiate themselves from competitors. In this scenario, verticals' satisfaction arises of paramount importance. As such, user experience is becoming a reliable indicator for service providers and telecommunication operators to convey overall end-to-end system functioning. To properly estimate end user satisfaction, operators and service providers require efficient means for quality monitoring and estimation at all layers, in conjunction with mechanisms able to maintain said quality at optimum levels. Given these factors, this paper proposes a mechanism for Quality of Perception (QoP) estimation in e-Health services, enabling the QoP-aware management of network slices fulfilling the requirements of supported services. To this end, the paper proposes a cognitive-based architecture which allows for the collection and monitoring of verticals' data to estimate QoP and provides mechanisms to re-configure the underlying network slices according to the monitored quality levels. A machine learning (ML) model is introduced that aims to forecast any future degradation in the quality perceived by vertical users. In case of a predicted degradation, the proposed architecture reacts and triggers the necessary remedial actions, referred as actuations. In order to evaluate the developed ML model and to showcase the interaction between the different components of the proposed architecture, an experimental study is presented with real data extracted from a roaming ambulance. In addition, a Proof of Concept of the actuation mechanism is demonstrated through an experimental testbed emulating e-Health services.

This paper presents an orchestration framework for the delivery of 5G vertical services and end-to-end network slices in a multi-domain scenario. The proposed architecture relies on a business model where verticals and service providers take the roles of digital service consumers, digital service providers and network service providers, each acting in its administrative domain. The interactions and delivery procedures among these entities leverage on standard solutions for interfaces and information models defined by ETSI and 3GPP. The paper also presents proof-of-concept applications of the proposed architecture in two H2020 European research initiatives.

Citation for published version (APA): Chirivella-Perez, E., Marco-Alaez, R., Hita, A., Serrano, A., Alcaraz Calero, J. M., Wang, Q., Neves, P. M., Bernini, G., Koutsopoulos, K., Gil Pérez, M., Martínez Pérez, G., Barros, M. J., & Gavras, A. (2020). SELFNET 5G mobile edge computing infrastructure: design and prototyping. Software Practice and Experience, 50(5), 741-756. https://doi.org/10.1002/spe.2681

SummaryThis paper presents the design and prototype implementation of the SELFNET fifth‐generation (5G) mobile edge infrastructure. In line with the current and emerging 5G architectural principles, visions, and standards, the proposed infrastructure is established primarily based on a mobile edge computing paradigm. It leverages cloud computing, software‐defined networking, and network function virtualization as core enabling technologies. Several technical solutions and options have been analyzed. As a result, a novel portable 5G infrastructure testbed has been prototyped to enable the preliminary testing of the integrated key technologies and to provide a realistic execution platform for further investigating and evaluating software‐defined networking– and network function virtualization–based application scenarios in 5G networks.

Future networks including the Fifth Generation (5G) and beyond mobile networks shall manage, control and orchestrate the new services for users especially vertical sectors, thereby they shall maximize the potential of 5G infrastructures and their services. Network slicing has emerged as a major new networking paradigm for meeting the diverse requirements of various vertical businesses in virtualized and softwarised 5G networks. SliceNet is a project of the EU 5G Infrastructure Public Private Partnership (5G PPP) and focuses on network slicing as a cornerstone technology in 5G networks. This article describes how the SliceNet Control Plane shall evolve to meet the end-to-end needs of many different vertical businesses. SliceNet Control Plane shall span across multiple administrative domains, by integrating different technologies in each involved segments (RAN, MEC, CN, inter-connectivity). Moreover, SliceNet Control Plane is able to allow verticals to plug their own control logic on top of provisioned slices and specialize their services characteristics while optimizing the use of shared resources, providing dynamic configuration, dynamic management, resource isolation and scalability.

Media use cases for emergency services require mission-critical levels of reliability for the delivery of media-rich services, such as video streaming. With the upcoming deployment of the fifth generation (5G) networks, a wide variety of applications and services with heterogeneous performance requirements are expected to be supported, and any migration of mission-critical services to 5G networks presents significant challenges in the quality of service (QoS), for emergency service operators. This paper presents a novel SliceNet framework, based on advanced and customizable network slicing to address some of the highlighted challenges in migrating eHealth telemedicine services to 5G networks. An overview of the framework outlines the technical approaches in beyond the state-of-the-art network slicing. Subsequently, this paper emphasizes the design and prototyping of a media-centric eHealth use case, focusing on a set of innovative enablers toward achieving end-to-end QoS-aware network slicing capabilities, required by this demanding use case. Experimental results empirically validate the prototyped enablers and demonstrate the applicability of the proposed framework in such media-rich use cases.

With the Fifth-Generation (5G) mobile networks set to arrive within the next years, this new generation will transform the industry with a profound impact on its customers as well as on the existing technologies and network architectures. Software-Defined Networking (SDN) and Network Functions Virtualization (NFV) will play key roles for the network operators as they prepare the migration to 5G, allowing them to quickly scale their networks. This paper presents a research work undertaken on this new paradigm of virtualized and programmable networks, aiming to address Self-Organizing Networks (SON) scenarios in a NFV/SDN context, focusing on detection and prediction of potential network and service anomalies. Towards this end, the performance management system performs aggregation, correlation and analysis of data gathered from the virtualized and programmable network elements. In particular, customized catalog-driven tools are developed, and the results show that they are able to successfully address these requirements. Current performance management platforms in production are designed for non-virtualized (non-NFV) and non-programmable (non-SDN) networks, and the knowledge gathered from this research brings some new understanding on how management platforms must evolve in order to be prepared for the upcoming next-generation mobile networks.

Network slicing has emerged as a major new networking paradigm for meeting the diverse requirements of various vertical businesses in virtualised and softwarised 5G networks. SliceNet is a project of the EU 5G Infrastructure Public Private Partnership (5G PPP) and focuses on network slicing as a cornerstone technology in 5G networks, and addresses the associated challenges in managing, controlling and orchestrating the new services for users especially vertical sectors, thereby maximising the potential of 5G infrastructures and their services by leveraging advanced software networking and cognitive network management. This paper presents the vision of the SliceNet project, highlighting the gaps in existing work and challenges, the proposed overall architecture, proposed technical approaches, and use cases.

—5G networks are envisioned to support substantially more users than the current 4G does as a direct consequence of the anticipated large diffusion of Machine-2-Machine (M2M) and Internet of Things (IoT) interconnected devices, often with signif-icantly higher committed data rates than general bandwidth cur- rently available into Long Term Evolution (LTE) and broadband networks. The expected large number of 5G subscribers will offer new opportunities to compromise devices and user services, which will allow attackers to trigger much larger and effective cyber- attacks. Significant advances in network management automation are therefore needed to manage 5G networks and services in an efficient, scalable, and effective way while protecting users and infrastructures from a wide plethora of advanced security threats. This paper presents a novel self-organized network management approach for 5G mobile networks where autonomic capabilities are tightly combined with Network Functions Virtualization (NFV) and Software-Defined Networking (SDN) technologies so as to provide an effective detection and mitigation of cyber-attacks.

this paper describes a Tactical Autonomic Language (TAL) for Self-Organizing Networks (SON) enabled autonomic management of 5G networking infrastructures. The TAL is represented in the form of an XML Schema, and its information model is defined through an XSD. The paper presents the TAL aiming at describing the language as the means to define autonomic behaviors in terms of system reaction to certain network issues by presenting the main principles of the TAL concept and the information model. The information regarding the inclusion of TAL processing in development work is presented.