View on 5G Architecture: Version 2.0

The 5G Architecture Working Group as part of the 5GPPP Initiative is looking at capturing novel trends and key technological enablers for the realization of the 5G architecture. It also targets at presenting in a harmonized way the architectural concepts developed in various projects and initiatives (not limited to 5GPPP projects only) so as to provide a consolidated view on the technical directions for the architecture design in the 5G era. The first version of the white paper was released in July 2016, which captured novel trends and key technological enablers for the realization of the 5G architecture vision along with harmonized architectural concepts from 5GPPP Phase 1 projects and initiatives. Capitalizing on the architectural vision and framework set by the first version of the white paper, this Version 2.0 of the white paper presents the latest findings and analyses with a particular focus on the concept evaluations, and accordingly it presents the consolidated overall architecture design

Network Slicing

Network slicing is emerging as a key enabling technology to support new service needs, business cases, and the evolution of programmable networking. As an end-to-end concept involving network functions in different domains and administrations, network slicing calls for new standardization efforts, design methodologies, and deployment strategies. This chapter aims at addressing the main aspects of network slicing with relevant challenges and practical solutions

Progressive introduction of network softwarization in operational telecom networks: advances at architectural, service and transport levels

Technological paradigms such as Software Defined Networking, Network Function Virtualization and Network Slicing are altogether offering new ways of providing services. This process is widely known as Network Softwarization, where traditional operational networks adopt capabilities and mechanisms inherit form the computing world, such as programmability, virtualization and multi-tenancy. This adoption brings a number of challenges, both from the technological and operational perspectives. On the other hand, they provide an unprecedented flexibility opening opportunities to developing new services and new ways of exploiting and consuming telecom networks. This Thesis first overviews the implications of the progressive introduction of network softwarization in operational networks for later on detail some advances at different levels, namely architectural, service and transport levels. It is done through specific exemplary use cases and evolution scenarios, with the goal of illustrating both new possibilities and existing gaps for the ongoing transition towards an advanced future mode of operation. This is performed from the perspective of a telecom operator, paying special attention on how to integrate all these paradigms into operational networks for assisting on their evolution targeting new, more sophisticated service demands.Programa de Doctorado en Ingeniería Telemática por la Universidad Carlos III de MadridPresidente: Eduardo Juan Jacob Taquet.- Secretario: Francisco Valera Pintor.- Vocal: Jorge López Vizcaín

Machine Learning-based Orchestration Solutions for Future Slicing-Enabled Mobile Networks

The fifth generation mobile networks (5G) will incorporate novel technologies such as network programmability and virtualization enabled by Software-Defined Networking (SDN) and Network Function Virtualization (NFV) paradigms, which have recently attracted major interest from both academic and industrial stakeholders. Building on these concepts, Network Slicing raised as the main driver of a novel business model where mobile operators may open, i.e., “slice”, their infrastructure to new business players and offer independent, isolated and self-contained sets of network functions and physical/virtual resources tailored to specific services requirements. While Network Slicing has the potential to increase the revenue sources of service providers, it involves a number of technical challenges that must be carefully addressed. End-to-end (E2E) network slices encompass time and spectrum resources in the radio access network (RAN), transport resources on the fronthauling/backhauling links, and computing and storage resources at core and edge data centers. Additionally, the vertical service requirements’ heterogeneity (e.g., high throughput, low latency, high reliability) exacerbates the need for novel orchestration solutions able to manage end-to-end network slice resources across different domains, while satisfying stringent service level agreements and specific traffic requirements. An end-to-end network slicing orchestration solution shall i) admit network slice requests such that the overall system revenues are maximized, ii) provide the required resources across different network domains to fulfill the Service Level Agreements (SLAs) iii) dynamically adapt the resource allocation based on the real-time traffic load, endusers’ mobility and instantaneous wireless channel statistics. Certainly, a mobile network represents a fast-changing scenario characterized by complex spatio-temporal relationship connecting end-users’ traffic demand with social activities and economy. Legacy models that aim at providing dynamic resource allocation based on traditional traffic demand forecasting techniques fail to capture these important aspects. To close this gap, machine learning-aided solutions are quickly arising as promising technologies to sustain, in a scalable manner, the set of operations required by the network slicing context. How to implement such resource allocation schemes among slices, while trying to make the most efficient use of the networking resources composing the mobile infrastructure, are key problems underlying the network slicing paradigm, which will be addressed in this thesis

5G Network Slicing using SDN and NFV: A Survey of Taxonomy, Architectures and Future Challenges

In this paper, we provide a comprehensive review and updated solutions related to 5G network slicing using SDN and NFV. Firstly, we present 5G service quality and business requirements followed by a description of 5G network softwarization and slicing paradigms including essential concepts, history and different use cases. Secondly, we provide a tutorial of 5G network slicing technology enablers including SDN, NFV, MEC, cloud/Fog computing, network hypervisors, virtual machines & containers. Thidly, we comprehensively survey different industrial initiatives and projects that are pushing forward the adoption of SDN and NFV in accelerating 5G network slicing. A comparison of various 5G architectural approaches in terms of practical implementations, technology adoptions and deployment strategies is presented. Moreover, we provide a discussion on various open source orchestrators and proof of concepts representing industrial contribution. The work also investigates the standardization efforts in 5G networks regarding network slicing and softwarization. Additionally, the article presents the management and orchestration of network slices in a single domain followed by a comprehensive survey of management and orchestration approaches in 5G network slicing across multiple domains while supporting multiple tenants. Furthermore, we highlight the future challenges and research directions regarding network softwarization and slicing using SDN and NFV in 5G networks.Comment: 40 Pages, 22 figures, published in computer networks (Open Access

Developing and deploying NFV solutions with OpenStack, Kubernetes and Docker

This document explains the deployment of virtualized network functions in a private cloud through ONAP, together with the architecture used, the machines employed and the software required. ONAP (Open Networking Automation Platform) is an open source project of the Linux Foundation, which provides a platform for real - time orchestration and automation of physical and virtual network functions.ONAP allows designing, orchest rating and managing all the elements related to virtualized network functions. In order to deploy ONAP, we acquired and installed a cloud infrastructure from scratch following the latest market best practices, which included setting up the servers and ne twork devices, configuring their NICs and installing all the software required: OpenStack, ONAP, etc. Moreover, these software solutions also have to be properly configured and installed, something that will be clarified in this paper along with the conf iguration of the cloud network. ONAP, being a novel solution, is not fully developed. Meaning it has presented many challenges and setbacks we have had to overcome in order to deploy it successfully in our environment. The final goal of this project is to create an environment in a private cloud with working virtualized network functions and to serve as a guide for other people who desire to deploy ONAP, overcoming all the obstacles we had to face and providing solutions, or at least, alternatives to th e plethora of issues they might stumble across, just as we did. Everything discussed in this document can be replicated in environments of greater scope than the ones defined in the paper, to the point that what is explained can even be applied in produc tion scenarios by telephone operators