5G envisages a “hyperconnected society” where trillions of diverse entities could communicate with each other anywhere and at any time, some of which will demand extremely challenging performance requirements such as submillisecond low latency. Mobile Edge Computing (MEC) concept where application computing resources are deployed at the edge of the mobile network in proximity of an end user is a promising solution to improve quality of online experience. To make MEC more flexible and cost-effective Network Functions Virtualisation (NFV) and Software-Defined Networking (SDN) technologies are widely adopted. It leads to significant CAPEX and OPEX reduction with the help of a joint radio-cloud management and orchestration logic. In this paper we discuss and develop a reference architecture for the orchestration and management of the MEC ecosystem. Along with the lifecycle management flows of MEC services, indicating the interactions among the functional modules inside the Orchestrator and with external elements, QoS management with a focus on the channel state information technique is presented.

Upcoming 5G mobile networks are addressing ambitious Key Performance Indicators (KPIs) not just in terms of capacity and latency, but also in terms of network control and management. In this direction, network management schemes need to evolve to provide the required flexibility, and automated and integrated management of 5G networks. This also applies to the 5G-Crosshaul transport network, which provides an integrated fronthaul and backhaul. Software Defined Networking (SDN) and Network Function Virtualization (NFV) are seen as key enablers for that. This article validates the flexibility, scalability, and recovery capabilities of the 5G-Crosshaul architecture in a testbed distributed geographically. More specifically, the central component of the validation is the hierarchical 5G-Crosshaul control infrastructure (XCI), conceived to handle multi-domain multi-technology transport network resources. Its performance is characterized through two experimental case studies. The first one illustrates the automated provisioning of all network resources required to deploy a complete LTE virtual mobile network featuring fronthaul and backhaul configurations. This takes 10.467s. on average for the network under test. The second one exploits the flexibility of the hierarchical XCI to apply local or centralized service recovery in the event of link failure depending on the desired path optimality vs. recovery time trade-off. On average, recovery takes 0.299s. and 6.652s., respectively. Overall, the proposed solution contributes to attain the target set for 5G networks of reducing service setup from hours to minutes.

Inter-cell interference (ICI) is a key limiting factor to the radio frequency (RF) energy performance of a multi-cell multi-user radio access network (RAN). The channel quality of the cell edge users is greatly impaired by ICI owing to the fact that cell edge users are furthest away from their serving base stations (BSs) and closest to the interfering BSs. Consequently the BS is compelled to allocate more physical resource blocks [PRBs (In LTE a PRB spans 12 sub-carriers each with a bandwidth of 15 kHz over a 0.5 ms time slot)] to the cell edge users in order to meet their quality-of-service (QoS) targets. The study proposes a novel ICI management technique that mitigates the effects of ICI through a sequential game play between cells in the E-UTRAN [Evolved Universal Mobile Telecommunications Systems (UMTS) terrestrial radio access network] based on the instantaneous cell offered load. The proposed technique is shown to produce greater user channel quality improvements of 4 dB greater than the state-of-the-art ICI management techniques. The channel quality improvements result in a utilisation of less PRBs, RF and radio head energy which translate to energy reduction gains of 34 and 45% at low-and high-offered loads, respectively. In addition the proposed scheme does not require a central processing entity such as a radio network controller and can be implemented in unplanned self-organising networks.

Immersive video applications based on 360 video streaming require high-bandwidth, high-reliability and lowlatency 5G connectivity but also flexible, low-latency and costeffective computing deployment. This paper proposes a novel solution for decomposing and distributing the end-to-end 360 video streaming service across three computing tiers, namely cloud, edge and constrained fog, in order of proximity to the end user client. The streaming service is aided with an adaptive viewport technique. The proposed solution is based on the H2020 5G-CORAL system architecture using micro-services-based design and a unified orchestration and control across all three tiers based on Fog05. Performance evaluation of the proposed solution shows noticeable reduction in bandwidth consumption, energy consumption, and deployment costs, as compared to a solution where the streaming service is all delivered out of one computing location such as the Cloud.

Based upon the context of Mobile Edge Computing (MEC) actual research and within the innovative scope of the SESAME EU-funded research project, we propose and assess a framework for security analysis applied in virtualised Small Cell Networks, with the aim of further extending MEC in the broader 5G environment. More specifically, by applying the fundamental concepts of the SESAME original architecture that aims at providing enhanced multi-tenant MEC services though Small Cells coordination and virtualization, we focus on a realistic 5G-oriented scenario enabling the provision of large multi-tenant enterprise services by using MEC. Then we evaluate several security issues by using a formal methodology, known as Secure Tropos.