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In the last few years, the research community has witnessed the rapid development of the Information-Centric Networking (ICN) approach aiming at evolving the Internet from today's host based packet delivery towards directly retrieving information in a secure, reliable, scalable, and efficient way. The Internet of Things (IoT) concept envisions scenarios in which "smart objects" can be interconnected to enable a whole new class of applications and services, positively increasing the impact of Information and Communication Technologies (ICT). Although ICN tested scenarios have been mainly limited to multimedia and data, quoted advantages of ICN make from this architectural design a valuable approach in addressing the challenges that arise from the increasing deployment of IoT. In general, IoT applications impose stringent requirements in terms of information freshness, which can be highly impacted by the intrinsic caching mechanisms existing in ICN approaches. In the present work, the available freshness mechanism conceived as part of the Content-Centric Networking (CCN) protocol is assessed and a novel consumer driven information freshness approach is proposed to satisfy the consumers' needs while mitigating the negative effect of the freshness requirements in the overall network performance. The new mechanism was evaluated through simulation, with obtained results showing that the proposed approach leads to better performance, as compared with the available CCN freshness mechanism.

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Network slicing emerges as a key technology in next generation networks, boosted by the integration of software‐defined networking and network functions virtualization. However, while allowing resource sharing among multiple tenants, such networks must also ensure the security requirements needed for the scenarios they are employed. This letter presents the leading security challenges on the use of network slices at the packet core, the solutions that academy and industry are proposing to address them, pointing out some directions that should be considered.

Information-Centric Networking (ICN) has recently emerged as a promising Future Internet architecture that aims to cope with the increasing demand for highly scalable and efficient distribution of content. Moving away from the Internet communication model based in addressable hosts, ICN leverages in-network storage for caching, multi-party communication through replication, and interaction models that decouple senders and receivers. This novel networking approach has the potential to outperform IP in several dimensions, besides just content dissemination. Concretely, the rise of the Internet of Things (IoT), with its rich set of challenges and requirements placed over the current Internet, provide an interesting ground for showcasing the contribution and performance of ICN mechanisms. This work analyses how the in-network caching mechanisms associated to ICN, particularly those implemented in the Content-Centric Networking (CCN) architecture, contribute in IoT environments, particularly in terms of energy consumption and bandwidth usage. A simulation comparing IP and the CCN architecture (an instantiation of ICN) in IoT environments demonstrated that CCN leads to a considerable reduction of the energy consumed by the information producers and to a reduction of bandwidth requirements, as well as highlighted the flexibility for adapting current ICN caching mechanisms to target specific requirements of IoT.

This article introduces the key innovations of the 5Growth service platform to empower verticals industries with an AI-driven automated 5G End-to-End (E2E) slicing solution which allows industries to achieve their service requirements. Specifically, we present multiple vertical pilots (Industry 4.0, Transportation and Energy), identify the key 5G requirements to enable them and analyze existing technical and functional gaps as compared to current solutions. Based on the identified gaps, we propose a set of innovations to address them with: (i) support of 3GPP-based RAN slices by introducing a RAN slicing model and providing automated RAN orchestration and control, (ii) an AI-driven closed-loop for automated service management with Service Level Agreement (SLA) assurance, and, (iii) Multi-domain solutions to expand service offerings by aggregating services and resources from different provider domains and also enable the integration of private 5G networks with public networks.

Spurred by a growing demand for higher-quality mobile services in vertical industries, 5G is integrating a rich set of technologies, traditionally alien to the telco ecosystem, such as machine learning or cloud computing. Despite the initial steps taken in prior research projects in Europe and beyond, additional innovations are needed to support vertical use cases. This is the objective of the 5Growth project: automate vertical support through (i) a portal connecting verticals to 5G platforms (a.k.a. vertical slicer), (ii) closed-loop machine-learning based Service Level Agreement (SLA) control, and (iii) end-to-end optimization. In this paper, we introduce a set of key 5Growth innovations supporting radio slicing, enhanced monitoring and analytics and integration of machine learning.

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