Search

The upcoming sixth-generation (6G) networks are expected to be more heterogeneous, scalable, reliable, secure and energy-efficient. 6G services and applications will benefit from the fast data transmission rates, global coverage, precise positioning, and widespread intelligence capabilities provided by 6G technology. In this complex scenario, new attack surfaces and vectors will emerge, due to the distributed, disaggregated, dynamic, programmable and open nature of the entire end-to-end 6G infrastructure along with the fragmentation of data, as well as the need for supporting cross-platforms interoperability, making the application of security and trust fundamentally challenging. To securely manage services in the future 6G mobile networks along with the set of functions ruling its management, conceptual work is needed to defining functional blocks supporting a secure end-to-end 6G systems management. This is especially critical in handling specific functionalities, such as network disaggregation, risk and threats business impact, energy-efficiency, self-configuration or dynamic discovery. This paper positions an innovative 6G security services management architecture, which builds on a set of innovative building blocks, leveraging key technologies, such as AI-assisted models and Digital Twin, while enabling a human-centric approach toward an end-to-end security solution. Two canonical workflows along with two illustrative application scenarios are proposed, Light Rail Transit and Extended Reality, to conceptually highlight the proposed architecture impact and its expected benefits when high bandwidth, ultra-low latency, and secure communications are required.

The 6th generation of wireless mobile networks is emerging as a paradigm shifting successor to unifying the experience across the physical, digital, and human worlds, pushing boundaries on performance in capacity, throughput, latency, scalability, flexibility, and reliability, while prominently addressing new major factors, including sustainability, security and privacy, as well as digital inclusion. Many research institutions and initiatives worldwide have started investigations to make 6G a reality by approximately 2030. In Germany, federal funding from the German Ministry of Education and Research (BMBF) supports a large-scale 6G initiative, with its lighthouse project, called 6G-ANNA. The core aim of this project is to develop the key aspects of a holistic, sustainable, secure, and resilient 6G system design that will simplify and improve the interaction between humans, digital assets, and the physical environment. This paper shares the vision of the project’s main technical working areas and advances, spanning topics from radio access, integration of multiple networks, as well as automation and simplification in networking to new applications and testbed scenarios, including real-time digital twins and extended reality. The industrial impact and relevance of standardization makes 6G-ANNA uniquely positioned to lead and realize the vision of next-generation wireless mobile network technologies, systems, and applications.

This paper considers service provider network design with a view of meeting application availability. Our primary goal is to design a service provider network using disparate network components and low-availability Virtual Network Functions (VNFs) while achieving high-availability Service Function Chains (SFCs). To this end, we attempt to answer the questions as to how much redundancy, and what type of redundancy should be incorporated in the network. Initially, we model a state-of-the-art provider architecture that is spread across the access, metro-core and backbone networks with associated discrete components such as switches, routers, optical equipment and data-centers. Our network design model leads to computing the amount of over-the-top (OTT) services that can be provisioned over a given network while achieving a particular availability. To this end, we formulate a constrained optimization model whose objective is profit maximization subject to availability measures that OTT services demand. We provide constraints of robustness that facilitate traffic churn. Four heuristics are also proposed with objectives that consider the breadth of the three key impacting parameters: VNF licensing cost, server utilization and delay optimization and the case for dynamic traffic. A simulation model presents comparative data for efficiency, latency and server utilization as well as validates our optimization model. The results stress the importance of an efficient optimization model in planning the network, as well as planning VNF placement ahead in time.

The specific demands of supply chains built upon large and complex IoT systems, make it a must to design a coordinated framework for cyber resilience provisioning, intended to guarantee trusted supply chains of ICT systems, built upon distributed, dynamic, potentially insecure, and heterogeneous ICT infrastructures. As such, the solution proposed in this paper is envisioned to deal with the whole supply chain system components, from the IoT ecosystem to the infrastructure connecting them, addressing security and privacy functionalities related to risks and vulnerabilities management, accountability, and mitigation strategies, as well as security metrics and evidence-based security assurance. In this paper, we present FISHY as a preliminary architecture that is designed to orchestrate existing and beyond state-of-the-art security appliances in composed ICT scenarios. To this end, the FISHY architecture leverages the capabilities of programmable networks and IT infrastructure through seamless orchestration and instantiation of novel security services, both in real-time and proactively. The paper also includes a thorough business analysis to go far beyond the technical benefits of a potential FISHY adoption, as well as three real-world use cases highlighting the envisioned benefits of a potential FISHY adoption.

The wide adoption of the recently coined fog and edge computing paradigms alongside conventional cloud computing creates a novel scenario, known as the cloud continuum, where services may benefit from the overall set of resources to optimize their execution. To operate successfully, such a cloud continuum scenario demands for novel management strategies, enabling a coordinated and efficient management of the entire set of resources, from the edge up to the cloud, designed in particular to address key edge characteristics, such as mobility, heterogeneity and volatility. The design of such a management framework poses many research challenges and has already promoted many initiatives worldwide at different levels. In this paper we present the results of one of these experiences driven by an EU H2020 project, focusing on the lessons learnt from a real deployment of the proposed management solution in three different industrial scenarios. We think that such a description may help understand the benefits brought in by a holistic cloud continuum management and also may help other initiatives in their design and development processes.

In this paper, we investigate an animal-human cohabitation problem with the help of machine learning and fiber-wireless (FiWi) access networks integrating cloud and edge (fog) computing. We propose an early warning system which detects wild animals near the road/rail with the help of wireless sensor networks and alerts passing vehicles of possible animal crossing. Additionally, we show that animals’ detection at the earliest and the related processing, if possible, at sensors would reduce the energy consumption of edge devices and the end-to-end delay in notifying vehicles, as compared to the scenarios where raw sensed data needs to be transferred up the base stations or the cloud. At the same time, machine learning helps in classification of captured images at edge devices, and in predicting different time-varying traffic profiles— distinguished by latency and bandwidth requirements—at base stations, including animal appearance events at sensors, and allocating bandwidth in FiWi access networks accordingly. We compare three scenarios of processing data at sensor nodes, base stations and a hybrid case of processing sensed data at either sensors or at base stations, and showed that dynamic allocation of bandwidth in FiWi access networks and processing data at its origin lead to lowering the congestion of network traffic at base stations and reducing the average end-to-end delay.