An efficient RAN slicing strategy for a heterogeneous network with eMBB and V2X services

Emerging 5G wireless technology will support services and use cases with vastly heterogeneous requirements. Network slicing, which allows composing multiple dedicated logical networks with specific functionality running on top of a common infrastructure, is introduced as a solution to cope with this heterogeneity. At the radio access network (RAN), the use of network slicing involves the assignment of radio resources to each slice in accordance with its expected requirements and functionalities. Therefore, RAN slicing will provide the required design flexibility and will be necessary for any network slicing solution. This paper investigates the RAN slicing problem for providing two generic services of 5G, namely enhanced mobile broadband (eMBB) and vehicle-to-everything (V2X). In this respect, we propose an efficient RAN slicing scheme based on an off-line reinforcement learning followed by a low-complexity heuristic algorithm, which allocates radio resources to different slices with the target of maximizing the resource utilization while ensuring the availability of resources to fulfill the requirements of the traffic of each RAN slice. A simulation-based analysis is presented to assess the performance of the proposed solution. The simulation results have shown that the proposed algorithm improves the network performance in terms of resource utilization, the latency of V2X services, achievable data rate, and outage probability.Peer ReviewedPostprint (published version

How should I slice my network? A multi-service empirical evaluation of resource sharing efficiency

Proceeding of: MobiCom '18: The 24th Annual International Conference on Mobile Computing and Networking, New Delhi, India, October 29 - November 2, 2018By providing especially tailored instances of a virtual network,network slicing allows for a strong specialization of the offered services on the same shared infrastructure. Network slicing has profound implications on resource management, as it entails an inherent trade-off between: (i) the need for fully dedicated resources to support service customization, and (ii) the dynamic resource sharing among services to increase resource efficiency and cost-effectiveness of the system. In this paper, we provide a first investigation of this trade-off via an empirical study of resource management efficiency in network slicing. Building on substantial measurement data collected in an operational mobile network (i) we quantify the efficiency gap introduced by non-reconfigurable allocation strategies of different kinds of resources, from radio access to the core of the network, and (ii) we quantify the advantages of their dynamic orchestration at different timescales. Our results provide insights on the achievable efficiency of network slicing architectures, their dimensioning, and their interplay with resource management algorithms.We would like to thank the shepherd and reviewers for their valuable comments and feedback. The work of University Carlos III of Madrid was supported by the H2020 5G-MoNArch project (grant agreement no. 761445), and the work of NEC Europe Ltd. was supported by the H2020 5GTransformer project (grant agreement no. 761536)

Network Slicing Landscape: A holistic architectural approach, orchestration and management with applicability in mobile and fixed networks and clouds

Tutorial at IEEE NetSoft2018 - 29th June 2018 Montreal Abstract: A holistic architectural approach, orchestration and management with applicability in mobile and fixed networks and clouds Topics: Key Slicing concepts and history Slicing Key Characteristics & Usage scenarios & Value Chain Multi-Domain Network Function Virtualisation Review of Research projects and results in network and cloud slicing Open Source Orchestrators Standard Organization activities: NGMN, ITU-T, ONF, 3GPP, ETSI, BBF, IETF Industrial perspective on Network Slicing Review of industry Use Cases Network Slicing Challenges Concluding remarks of Network Slicing Acknowledgements & Reference

Resource sharing efficiency in network slicing

The economic sustainability of future mobile networks will largely depend on the strong specialization of its offered services. Network operators will need to provide added value to their tenants, by moving from the traditional one-size-fits-all strategy to a set of virtual end-to-end instances of a common physical infrastructure, named network slices , which are especially tailored to the requirements of each application. Implementing network slicing has significant consequences in terms of resource management: service customization entails assigning to each slice fully dedicated resources, which may also be dynamically reassigned and overbooked in order to increase the cost-efficiency of the system. In this paper, we adopt a data-driven approach to quantify the efficiency of resource sharing in future sliced networks. Building on metropolitan-scale real-world traffic measurements, we carry out an extensive parametric analysis that highlights how diverse performance guarantees, technological settings, and slice configurations impact the resource utilization at different levels of the infrastructure in presence of network slicing. Our results provide insights on the achievable efficiency of network slicing architectures, their dimensioning, and their interplay with resource management algorithms at different locations and reconfiguration timescales.The work of University Carlos III of Madrid was supported by the H2020 5G-MoNArch project (Grant Agreement No. 761445) and the work of NEC Laboratories Europe by the 5GTransformer project (Grant Agreement No. 761536). The work of CNR-IEIIT was partially supported by the ANR CANCAN project (ANR-18-CE25-0011).Publicad

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

Radio resource management for V2X in cellular systems

The thesis focuses on the provision of cellular vehicle-to-everything (V2X) communications, which have attracted great interest for 5G due to the potential of improving traffic safety and enabling new services related to intelligent transportation systems. These types of services have strict requirements on reliability, access availability, and end-to-end (E2E) latency. V2X requires advanced network management techniques that must be developed based on the characteristics of the networks and traffic requirements. The integration of the Sidelink (SL), which enables the direct communication between vehicles (i.e., vehicle-to-vehicle (V2V)) without passing through the base station into cellular networks is a promising solution for enhancing the performance of V2X in cellular systems. In this thesis, we addressed some of the challenges arising from the integration of V2V communication in cellular systems and validated the potential of this technology by providing appropriate resource management solutions. Our main contributions have been in the context of radio access network slicing, mode selection, and radio resource allocation mechanisms. With regard to the first research direction that focuses on the RAN slicing management, a novel strategy based on offline Q-learning and softmax decision-making has been proposed as an enhanced solution to determine the adequate split of resources between a slice for eMBB communications and a slice for V2X. Then, starting from the outcome of the off-line Q-learning algorithm, a low-complexity heuristic strategy has been proposed to achieve further improvements in the use of resources. The proposed solution has been compared against proportional and fixed reference schemes. The extensive performance assessment have revealed the ability of the proposed algorithms to improve network performance compared to the reference schemes, especially in terms of resource utilization, throughput, latency and outage probability. Regarding the second research direction that focuses on the mode selection, two different mode selection solutions referred to as MSSB and MS-RBRS strategies have been proposed for V2V communication over a cellular network. The MSSB strategy decides when it is appropriate to use one or the other mode, i.e. sidelink or cellular, for the involved vehicles, taking into account the quality of the links between V2V users, the available resources, and the network traffic load situation. Moreover, the MS-RBRS strategy not only selects the appropriate mode of operation but also decides efficiently the amount of resources needed by V2V links in each mode and allows reusing RBs between different SL users while guaranteeing the minimum signal to interference requirements. The conducted simulations have revealed that the MS-RBRS and MSSB strategies are beneficial in terms of throughput, radio resource utilization, outage probability and latency under different offered loads comparing to the reference scheme. Last, we have focused on the resource allocation problem including jointly mode selection and radio resource scheduling. For the mode selection, a novel mode selection has been presented to decide when it is appropriate to select sidelink mode and use a distributed approach for radio resource allocation or cellular mode and use a centralized radio resource allocation. It takes into account three aspects: the quality of the links between V2V users, the available resources, and the latency. As for the radio resource allocation, the proposed approach includes a distributed radio resource allocation for sidelink mode and a centralized radio resource allocation for cellular mode. The proposed strategy supports dynamic assignments by allowing transmission over mini-slots. A simulation-based analysis has shown that the proposed strategies improved the network performance in terms of latency of V2V services, packet success rate and resource utilization under different network loads.La tesis se centra en la provisión de comunicaciones para vehículos sistemas celulares (V2X: Vehicle to Everything), que han atraído un gran interés en el contexto de 5G debido a su potencial de mejorar la seguridad del tráfico y habilitar nuevos servicios relacionados con los sistemas inteligentes de transporte. Estos tipos de servicios tienen requisitos estrictos en términos fiabilidad, disponibilidad de acceso y latencia de extremo a extremo (E2E). Para ello, V2X requiere técnicas avanzadas de gestión de red que deben desarrollarse en función de las características de las redes y los requisitos de tráfico. La integración del Sidelink (SL), que permite la comunicación directa entre vehículos (es decir, vehículo a vehículo (V2V)) sin pasar por la estación base de las redes celulares, es una solución prometedora para mejorar el rendimiento de V2X en el sistema celular. En esta tesis, abordamos algunos de los desafíos derivados de la integración de la comunicación V2V en los sistemas celulares y validamos el potencial de esta tecnología al proporcionar soluciones de gestión de recursos adecuadas. Nuestras principales contribuciones han sido en el contexto del denominado "slicing" de redes de acceso radio, la selección de modo y los mecanismos de asignación de recursos radio. Respecto a la primera dirección de investigación que se centra en la gestión del RAN slicing, se ha propuesto una estrategia novedosa basada en Q-learning y toma de decisiones softmax como una solución para determinar la división adecuada de recursos entre un slice para comunicaciones eMBB y un slice para V2X. Luego, a partir del resultado del algoritmo de Q-learning, se ha propuesto una estrategia heurística de baja complejidad para lograr mejoras adicionales en el uso de los recursos. La solución propuesta se ha comparado con esquemas de referencia proporcionales y fijos. La evaluación ha revelado la capacidad de los algoritmos propuestos para mejorar el rendimiento de la red en comparación con los esquemas de referencia, especialmente en términos de utilización de recursos, rendimiento, y latencia . Con respecto a la segunda dirección de investigación que se centra en la selección de modo, se han propuesto dos soluciones de diferentes llamadas estrategias MSSB y MS-RBRS para la comunicación V2V a través de una red celular. La estrategia MSSB decide cuándo es apropiado usar el modo SL o el modo celular, para los vehículos involucrados, teniendo en cuenta la calidad de los enlaces entre los usuarios de V2V, los recursos disponibles y la situación de carga de tráfico de la red. Además, la estrategia MS-RBRS no solo selecciona el modo de operación apropiado, sino que también decide eficientemente la cantidad de recursos que los enlaces V2V necesitan en cada modo, y permite que los RB se reutilicen entre diferentes usuarios de SL al tiempo que garantiza requisitos mínimos de señal a interferencia. Se ha presentado un análisis basado en simulación para evaluar el desempeño de las estrategias propuestas. Finalmente, nos hemos centrado en el problema conjunto de la selección de modo y la asignación de recursos de radio. Para la selección de modo, se ha presentado una nueva estrategia para decidir cuándo es apropiado seleccionar el modo SL y usar un enfoque distribuido para la asignación de recursos de radio o el modo celular y usar la asignación de recursos de radio centralizada. Tiene en cuenta tres aspectos: la calidad de los enlaces entre los usuarios de V2V, los recursos disponibles y la latencia. En términos de asignación de recursos de radio, el enfoque propuesto incluye una asignación de recursos de radio distribuida para el modo SL y una asignación de recursos de radio centralizada para el modo celular. La estrategia propuesta admite asignaciones dinámicas al permitir la transmisión a través de mini-slots. Los resultados muestran las mejoras en términos de latencia, tasa de recepción y la utilización de recursos bajo diferentes cargas de red.Postprint (published version

Sistemas Difusos: Una Aproximación a las redes 5G bajo el Paradigma SDN

The exploitation that has had the fuzzy systems related to advances of 5G networks (Fifth Generation Mobile Networks) and how this development has been framed by the paradigm of SDN (Software Defined Networks) architectures are reviewed in this article. The first part will review terms required for understanding the technologies and their evolution; on which different scenarios are evaluated because they have contributed to the development of the definition of 5G networks. Following, the research and development of the fuzzy systems applied to telecommunications, specifically 5G technology and SDN architectures will be described. Finally, the respective conclusions of the fuzzy systems in the 5G networks and SDN architectures will be exposed.En este artículo se revisó la utilización que ha tenido los sistemas difusos en torno a los avances delas redes 5G (Redes Móviles de Quinta Generación) y cómo este desarrollo ha sido enmarcado por elparadigma de SDN (Software Defined Networks). La primera parte revisó los términos requeridos paraentender las tecnologías planteadas y su evolución; en esta definición se evalúan diferentes escenariosque han contribuido al desarrollo de la definición de las redes 5G. Posteriormente se describió la investigación y desarrollo de los sistemas difusos aplicados a las telecomunicaciones, específicamente la tecnología 5G y las arquitecturas SDN. Finalmente, se expusieron las conclusiones respectivas de los sistemas difusos en las redes 5G y las arquitecturas SDN