Multi-access edge computing (MEC) is an emerging ecosystem, which aims at converging telecommunication and IT services, providing a cloud computing platform at the edge of the radio access network. MEC offers storage and computational resources at the edge, reducing latency for mobile end users and utilizing more efficiently the mobile backhaul and core networks. This paper introduces a survey on MEC and focuses on the fundamental key enabling technologies. It elaborates MEC orchestration considering both individual services and a network of MEC platforms supporting mobility, bringing light into the different orchestration deployment options. In addition, this paper analyzes the MEC reference architecture and main deployment scenarios, which offer multitenancy support for application developers, content providers, and third parties. Finally, this paper overviews the current standardization activities and elaborates further on open research challenges.

Network slicing has been identified as the backbone of the rapidly evolving 5G technology. However, as its consolidation and standardization progress, there are no literatures that comprehensively discuss its key principles, enablers and research challenges. This paper elaborates network slicing from an endto-end perspective detailing its historical heritage, principal concepts, enabling technologies and solutions as well as the current standardization efforts. In particular, it overviews the diverse use cases and network requirements of network slicing, the pre-slicing era, considering RAN sharing as well as the endto-end orchestration and management, encompassing the radio access, transport network and the core network. This paper also provides details of specific slicing solutions for each part of the 5G system. Finally, this paper identifies a number of open research challenges and provides recommendations towards potential solutions.

-This paper proposes an approach to enhance users' experience of video streaming in the context of smart cities. The proposed approach relies on the concept of mobile edge computing (MEC) as a key factor in enhancing the Quality of Service (QoS). It sustains QoS by ensuring that applications/services follow the mobility of users, realizing the "Follow-me-Edge" concept. The proposed scheme enforces an autonomic creation of MEC services to allow anywhere-anytime data access with optimum Quality of Experience (QoE) and reduced latency. Considering its application in smart city scenarios, the proposed scheme represents an important solution for reducing core network traffic and ensuring ultra-short latency, and that is through a smart MEC architecture capable of achieving 1 ms latency dream for the upcoming 5G mobile systems.

5G mobile systems are expected to meet different strict requirements beyond the traditional operator use cases. Effectively, to accommodate needs of new industry segments such as health care or manufacturing, 5G systems need to accommodate elasticity, flexibility, dynamicity, scalability, manageability, agility and customization along with different levels of service delivery parameters according with the service requirements. This is currently possible only by running the networks on top of the same infrastructure, technology named network function virtualization, through this sharing the development and infrastructure costs between the different networks.In this paper, we showcase the need for the deep customization of mobile networks at different granularity levels: per network, per application, per group of users, per individual users and even per data of users. The paper also assesses the potential of network slicing to provide the appropriate customization and highlights the technology challenges. Finally, a high level architectural solution is proposed addressing a massive multi-slice environment.

The post-pandemic future will offer tremendous opportunity and challenge from transformation of the human experience linking physical, digital and biological worlds: 6G should be based on a new architecture to fully realize the vision to connect the worlds. We explore several novel architecture concepts for the 6G era driven by a decomposition of the architecture into platform, functions, orchestration and specialization aspects. With 6G, we associate an open, scalable, elastic, and platform agnostic het-cloud, with converged applications and services decomposed into micro-services and serverless functions, specialized architecture for extreme attributes, as well as open service orchestration architecture. Key attributes and characteristics of the associated architectural scenarios are described. At the air-interface level, 6G is expected to encompass use of sub-Terahertz spectrum and new spectrum sharing technologies, airinterface design optimized by AI/ML techniques, integration of radio sensing with communication, and meeting extreme requirements on latency, reliability and synchronization. Fully realizing the benefits of these advances in radio technology will also call for innovations in 6G network architecture as described.

Mobile Edge Computing (MEC) will play a key role in next-generation mobile networks to extend the range of supported delay-sensitive applications. Furthermore, an increasing attention is paid to provide user-centric services, to better address the strict requirements of novel immersive applications. In this scenario, MEC solutions need to efficiently cope with user mobility, which requires fast relocation of service instances to guarantee the desired Quality of Experience. However, service migration is still an open issue, especially for resource-constrained edge nodes interconnected by high-latency and low-bandwidth links. In this paper, by leveraging the potential of lightweight container-based virtualization techniques, we investigate a novel approach to support service provisioning in dynamic MEC environments. In particular, we present a framework where proactive service replication for stateless applications is exploited to drastically reduce the time of service migration between different cloudlets and to meet the latency requirements. The performance evaluation shows promising results of our approach with respect to classic reactive service migration. INTRODUCTIONSeveral classes of new applications are challenging the current network and cloud infrastructures. As illustrated in a recent report from International Telecommunication Union, 1 applications such as tactile internet, mobile gaming, and augmented reality are pushing new requirements, especially in terms of latency. To guarantee the desired Quality of Experience (QoE) for the end user, not only the network access delay, but also the cloud service processing should be performed within a few milliseconds. To achieve the 1 ms latency dream for the next-generation 5G cloud-enabled services, both network and cloud providers should jointly cooperate and investigate novel approaches. In this regard, academic and industrial research communities have focused on Mobile Edge Computing (MEC) solutions to exploit processing and storage capabilities at the edge of the network, as near as possible to the end user. 2,3 Indeed, the deployment of micro datacentres in the network access points, known as cloudlets, 4,5 can guarantee remarkable benefits of low latency interaction and scalability, by balancing the workload over the distributed edge infrastructure. Furthermore, bringing the cloudlet concept into the Internet of Things (IoT) scenario results in the definition of the so-called Fog Computing paradigm, which envisages a highly virtualized infrastructure composed of distributed edge nodes to monitor and analyse the most time-sensitive data generated by network connected devices. [6][7][8] In a MEC environment, a key challenge is represented by the user mobility, which could cause significant application degradation, even in small scenarios, as reported in a previous study.9,10 To guarantee service continuity and to meet the strict requirements of application latency, the MEC framework needs to properly cope with service migration between edge nodes. I...

This paper introduces a content delivery network as a service (CDNaaS) platform that allows dynamic deployment and life-cycle management of virtual content delivery network (CDN) slices running across multiple administrative cloud domains. The CDN slice consists of four virtual network function (VNF) types, namely virtual transcoders, virtual streamers, virtual caches, and a CDN-slice-specific Coordinator for the management of the slice resources across the involved cloud domains. To create an efficient CDN slice, the optimal placement of its composing VNFs using adequate amount of virtual resources for each VNF is of vital importance. In this vein, this paper devises mechanisms for allocating an appropriate set of VNFs for each CDN slice to meet its performance requirements and minimize as much as possible the incurred cost in terms of allocated virtual resources. A mathematical model is developed to evaluate the performance of the proposed mechanisms. We first formulate the VNF placement problem as two Linear Integer problem models, aiming at minimizing the cost and maximizing the quality of experience (QoE) of the virtual streaming service. By applying the bargaining game theory, we ensure an optimal tradeoff solution between the cost efficiency and QoE. Extensive simulations are conducted to evaluate the effectiveness of the proposed models in achieving their design objectives and encouraging results are obtained.

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