Software Defined Networking (SDN), characterized by a clear separation of the control and data planes, is being adopted as a novel paradigm for wired networking. With SDN, network operators can run their infrastructure more efficiently, supporting a faster deployment of new services while enabling key features such as virtualization. In this article, we adopt an SDN-like approach applied to wireless mobile networks that will not only benefit from the same features as in the wired case, but also will leverage on the distinct features of mobile deployments to push improvements even further. We illustrate with a number of representative use cases the benefits from the adoption of the proposed architecture, which is detailed in terms of modules, interfaces and high-level signaling. We also review the ongoing standardization efforts, and discuss the potential advantages, weaknesses and the need for a coordinated approach.
Abstract-The introduction of new services requiring large and dynamic bitrate connectivity can cause changes in the direction of the traffic in metro and even core network segments along the day. This leads to large overprovisioning in statically managed virtual network topologies (VNT), designed to cope with the traffic forecast. To reduce expenses while ensuring the required grade of service, in this paper we propose the VNT reconfiguration approach based on data analytics for traffic prediction (VENTURE); it regularly reconfigures the VNT based on predicted traffic thus, adapting the topology to both, the current and the predicted traffic volume and direction. A machine learning algorithm based on artificial neural network (ANN) is used to provide robust and adaptive traffic models. The reconfiguration problem that takes as input the traffic prediction is modelled mathematically and a heuristic is proposed to solve it in practical times. To support VENTURE, we propose an architecture that allows collecting and storing data from monitoring at the routers and that is used to train predictive models for every origin-destination pair. Exhaustive simulation results of the algorithm together with the experimental assessment of the proposed architecture are finally presented.
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The on-going digital transformation is key to progress towards a new generation of more efficient, sustainable and connected industrial systems allowing the so-called factories of the future. This new generation, commonly referred to as industry 4.0, will be accompanied by a new wave of use cases that will allow companies from logistics and manufacturing sectors to increase flexibility, productivity and usability in the industrial processes executed within their factory premises. Unlike typical use cases from other vertical sectors (e.g. energy, media, smart cities), industry 4.0 use cases will bring very stringent requirements in terms of latency, reliability and high-accuracy positioning. The combination of 5G technology with enterprise network solutions becomes crucial to satisfy these requirements in indoor, private environments. In this context, the concept of 5G non-public networks has emerged. In this article we provide an overview of 5G non-public networks, studying their applicability to the industry 4.0 ecosystem. On the basis of the work (being) developed in 3GPP Rel-16 specifications, we identify a number of deployment options relevant for non-public networks, and discuss their integration with mobile network operators' public networks. Finally, we provide a comparative analysis of these options, assessing their feasibility according to different criteria, including technical, regulatory and business aspects. The outcome of this analysis will help industry players interested in using non-public networks to decide which is the most appropriate deployment option for their use cases.
This paper presents on-going research to develop the Intercloud Architecture Framework (ICAF) that addresses problems in multi-provider multi-domain heterogeneous cloud based infrastructure services and applications integration and interoperability. The paper refers to existing standards in Cloud Computing, in particular, recently published NIST Cloud Computing Reference Architecture (CCRA). The proposed ICAF defines four complementary components addressing Intercloud integration and interoperability: multi-layer Cloud Services Model (CSM) that combines commonly adopted cloud service models, such as IaaS, PaaS, SaaS, in one multilayer model with corresponding inter-layer interfaces including also access and delivery infrastructure layer; Intercloud Control and Management Plane (ICCMP) that supports cloud based applications interaction; Intercloud Federation Framework (ICFF), and Intercloud Operation Framework (ICOF). The paper provides general definition of the ICFF, its generic components and interfaces. The paper briefly describes the architectural framework for cloud based infrastructure services provisioned on-demand being developed in the framework of the GEYSERS project that provides a basis for CSM and ICCMP implementation allowing optimized provisioning of computing, storage and networking resources. The proposed architecture is intended to provide an architectural model for developing Intercloud middleware and in this way will facilitate clouds interoperability and integration.
The Novel Enablers for Cloud Slicing (NECOS) project addresses the limitations of current cloud computing infrastructures to respond to the demand for new services, as presented in two use-cases, that will drive the whole execution of the project. The first use-case is focused on Telco service provider and is oriented towards the adoption of cloud computing in their large networks. The second use-case is targeting the use of edge clouds to support devices with low computation and storage capacity. The envisaged solution is based on a new concept, the Lightweight Slice Defined Cloud (LSDC), as an approach that extends the virtualization to all the resources in the involved networks and data centers and provides uniform management with a high-level of orchestration. In this position paper, we discuss the motivation, objectives, architecture, research challenges (and how to overcome them) and initial efforts for the NECOS project.
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