An Integrated, Virtualized Joint Edge and Fog Computing System with Multi-RAT Convergence

Notably, developing an innovative architectural network paradigm is essential to address the technical challenging of 5G applications' requirements in a unified platform. Forthcoming applications will provide a wide range ofnetworking, computing and storage capabilities closer to the endusers.In this context, the 5G-PPP Phase two project named "5GCORAL:A 5G Convergent Virtualized Radio Access Network Living at the Edge" aims at identifying and experimentally validating which are the key technology innovations allowing for the development of a convergent 5G multi-RAT access based on a virtualized Edge and Fog architecture being scalable, flexible and interoperable with other domains including transport, core network and distant Clouds. In 5G-CORAL, an architecture is proposed based on ETSI MEC and ETSI NFV frameworks in a unified platform. Then, a set of exemplary use cases benefiting from Edge and Fog networks in near proximity of the end-user are proposed for demonstration on top of connected car, shopping mall and high-speed train platforms.This work has been partially funded by the H2020 collaborative Europe/Taiwan research project 5G-CORAL (grant num. 761586

Edge Robotics: are we ready? An experimental evaluation of current vision and future directions

Cloud-based robotics systems leverage a wide range of Information Technologies (IT) to offer tangible benefits like cost reduction, powerful computational capabilities, data offloading, etc. However, the centralized nature of cloud computing is not well-suited for a multitude of Operational Technologies (OT) nowadays used in robotics systems that require strict real-time guarantees and security. Edge computing and fog computing are complementary approaches that aim at mitigating some of these challenges by providing computing capabilities closer to the users. The goal of this work is hence threefold: i) to analyze the current edge computing and fog computing landscape in the context of robotics systems, ii) to experimentally evaluate an end-to-end robotics system based on solutions proposed in the literature, and iii) to experimentally identify current benefits and open challenges of edge computing and fog computing. Results show that, in the case of an exemplary delivery application comprising two mobile robots, the robot coordination and range can be improved by consuming real-time radio information available at the edge. However, our evaluation highlights that the existing software, wireless and virtualization technologies still require substantial evolution to fully support edge-based robotics systems.This work has been partially funded by European Union’s Horizon 2020 research and innovation programme under grant agreement No 101015956, and the Spanish Ministry of Economic Affairs and Digital Transformation and the European Union- NextGenerationEU through the UNICO 5G I+ D 6G-EDGEDT and 6G-DATADRIVE

Towards edge robotics: the progress from cloud-based robotic systems to intelligent and context-aware robotic services

Current robotic systems handle a different range of applications such as video surveillance, delivery of goods, cleaning, material handling, assembly, painting, or pick and place services. These systems have been embraced not only by the general population but also by the vertical industries to help them in performing daily activities. Traditionally, the robotic systems have been deployed in standalone robots that were exclusively dedicated to performing a specific task such as cleaning the floor in indoor environments. In recent years, cloud providers started to offer their infrastructures to robotic systems for offloading some of the robot’s functions. This ultimate form of the distributed robotic system was first introduced 10 years ago as cloud robotics and nowadays a lot of robotic solutions are appearing in this form. As a result, standalone robots became software-enhanced objects with increased reconfigurability as well as decreased complexity and cost. Moreover, by offloading the heavy processing from the robot to the cloud, it is easier to share services and information from various robots or agents to achieve better cooperation and coordination. Cloud robotics is suitable for human-scale responsive and delay-tolerant robotic functionalities (e.g., monitoring, predictive maintenance). However, there is a whole set of real-time robotic applications (e.g., remote control, motion planning, autonomous navigation) that can not be executed with cloud robotics solutions, mainly because cloud facilities traditionally reside far away from the robots. While the cloud providers can ensure certain performance in their infrastructure, very little can be ensured in the network between the robots and the cloud, especially in the last hop where wireless radio access networks are involved. Over the last years advances in edge computing, fog computing, 5G NR, network slicing, Network Function Virtualization (NFV), and network orchestration are stimulating the interest of the industrial sector to satisfy the stringent and real-time requirements of their applications. Robotic systems are a key piece in the industrial digital transformation and their benefits are very well studied in the literature. However, designing and implementing a robotic system that integrates all the emerging technologies and meets the connectivity requirements (e.g., latency, reliability) is an ambitious task. This thesis studies the integration of modern Information andCommunication Technologies (ICTs) in robotic systems and proposes some robotic enhancements that tackle the real-time constraints of robotic services. To evaluate the performance of the proposed enhancements, this thesis departs from the design and prototype implementation of an edge native robotic system that embodies the concepts of edge computing, fog computing, orchestration, and virtualization. The proposed edge robotics system serves to represent two exemplary robotic applications. In particular, autonomous navigation of mobile robots and remote-control of robot manipulator where the end-to-end robotic system is distributed between the robots and the edge server. The open-source prototype implementation of the designed edge native robotic system resulted in the creation of two real-world testbeds that are used in this thesis as a baseline scenario for the evaluation of new innovative solutions in robotic systems. After detailing the design and prototype implementation of the end-to-end edge native robotic system, this thesis proposes several enhancements that can be offered to robotic systems by adapting the concept of edge computing via the Multi-Access Edge Computing (MEC) framework. First, it proposes exemplary network context-aware enhancements in which the real-time information about robot connectivity and location can be used to dynamically adapt the end-to-end system behavior to the actual status of the communication (e.g., radio channel). Three different exemplary context-aware enhancements are proposed that aim to optimize the end-to-end edge native robotic system. Later, the thesis studies the capability of the edge native robotic system to offer potential savings by means of computation offloading for robot manipulators in different deployment configurations. Further, the impact of different wireless channels (e.g., 5G, 4G andWi-Fi) to support the data exchange between a robot manipulator and its remote controller are assessed. In the following part of the thesis, the focus is set on how orchestration solutions can support mobile robot systems to make high quality decisions. The application of OKpi as an orchestration algorithm and DLT-based federation are studied to meet the KPIs that autonomously controlledmobile robots have in order to provide uninterrupted connectivity over the radio access network. The elaborated solutions present high compatibility with the designed edge robotics system where the robot driving range is extended without any interruption of the end-to-end edge robotics service. While the DLT-based federation extends the robot driving range by deploying access point extension on top of external domain infrastructure, OKpi selects the most suitable access point and computing resource in the cloud-to-thing continuum in order to fulfill the latency requirements of autonomously controlled mobile robots. To conclude the thesis the focus is set on how robotic systems can improve their performance by leveraging Artificial Intelligence (AI) and Machine Learning (ML) algorithms to generate smart decisions. To do so, the edge native robotic system is presented as a true embodiment of a Cyber-Physical System (CPS) in Industry 4.0, showing the mission of AI in such concept. It presents the key enabling technologies of the edge robotic system such as edge, fog, and 5G, where the physical processes are integrated with computing and network domains. The role of AI in each technology domain is identified by analyzing a set of AI agents at the application and infrastructure level. In the last part of the thesis, the movement prediction is selected to study the feasibility of applying a forecast-based recovery mechanism for real-time remote control of robotic manipulators (FoReCo) that uses ML to infer lost commands caused by interference in the wireless channel. The obtained results are showcasing the its potential in simulation and real-world experimentation.Programa de Doctorado en Ingeniería Telemática por la Universidad Carlos III de MadridPresidente: Karl Holger.- Secretario: Joerg Widmer.- Vocal: Claudio Cicconett

Towards 5G Software-Defined Ecosystems: Technical Challenges, Business Sustainability and Policy Issues

Techno-economic drivers are creating the conditions for a radical change of paradigm in the design and operation of future telecommunications infrastructures. In fact, SDN, NFV, Cloud and Edge-Fog Computing are converging together into a single systemic transformation termed “Softwarization” that will find concrete exploitations in 5G systems. The IEEE SDN Initiative1 has elaborated a vision, an evolutionary path and some techno-economic scenarios of this transformation: specifically, the major technical challenges, business sustainability and policy issues have been investigated. This white paper presents: 1) an overview on the main techno-economic drivers steering the “Softwarization” of telecommunications; 2) an introduction to the Open Mobile Edge Cloud vision (covered in a companion white paper); 3) the main technical challenges in terms of operations, security and policy; 4) an analysis of the potential role of open source software; 5) some use case proposals for proof-of-concepts; and 6) a short description of the main socio-economic impacts being produced by “Softwarization”. Along these directions, IEEE SDN is also developing of an open catalogue of software platforms, toolkits, and functionalities aiming at a step-by-step development and aggregation of test-beds/field-trials on SDNNFV- 5G

An Edge and Fog Computing Platform for Effective Deployment of 360 Video Applications

This paper has been presented at: Seventh International Workshop on Cloud Technologies and Energy Efficiency in Mobile Communication Networks (CLEEN 2019). How cloudy and green will mobile network and services be? 15 April 2019 - Marrakech, MoroccoIn press / En prensaImmersive 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.This work has been partially funded by the H2020 collaborative Europe/Taiwan research project 5G-CORAL (grant num. 761586)

Survey on 5G Second Phase RAN Architectures and Functional Splits

The Radio Access Network (RAN) architecture evolves with different generations of mobile communication technologies and forms an indispensable component of the mobile network architecture. The main component of the RAN infrastructure is the base station, which includes a Radio Frequency unit and a baseband unit. The RAN is a collection of base stations connected to the core network to provide coverage through one or more radio access technologies. The advancement towards cloud native networks has led to centralizing the baseband processing of radio signals. There is a trade-off between the advantages of RAN centralization (energy efficiency, power cost reduction, and the cost of the fronthaul) and the complexity of carrying traffic between the data processing unit and distributed antennas. 5G networks hold high potential for adopting the centralized architecture to reduce maintenance costs while reducing deployment costs and improving resilience, reliability, and coordination. Incorporating the concept of virtualization and centralized RAN architecture enables to meet the overall requirements for both the customer and Mobile Network Operator. Functional splitting is one of the key enablers for 5G networks. It supports Centralized RAN, virtualized Radio Access Network, and the recent Open Radio Access Networks. This survey provides a comprehensive tutorial on the paradigms of the RAN architecture evolution, its key features, and implementation challenges. It provides a thorough review of the 3rd Generation Partnership Project functional splitting complemented by associated challenges and potential solutions. The survey also presents an overview of the fronthaul and its requirements and possible solutions for implementation, algorithms, and required tools whilst providing a vision of the evaluation beyond 5G second phase.info:eu-repo/semantics/submittedVersio

Enhanced connectivity in wireless mobile programmable networks

Mención Interancional en el título de doctorThe architecture of current operator infrastructures is being challenged by the non-stop growing demand of data hungry services appearing every day. While currently deployed operator networks have been able to cope with traffic demands so far, the architectures for the 5th generation of mobile networks (5G) are expected to support unprecedented traffic loads while decreasing costs associated with the network deployment and operations. Indeed, the forthcoming set of 5G standards will bring programmability and flexibility to levels never seen before. This has required introducing changes in the architecture of mobile networks, enabling different features such as the split of control and data planes, as required to support rapid programming of heterogeneous data planes. Network softwarisation is hence seen as a key enabler to cope with such network evolution, as it permits controlling all networking functions through (re)programming, thus providing higher flexibility to meet heterogeneous requirements while keeping deployment and operational costs low. A great diversity in terms of traffic patterns, multi-tenancy, heterogeneous and stringent traffic requirements is therefore expected in 5G networks. Software Defined Networking (SDN) and Network Function Virtualisation (NFV) have emerged as a basic tool-set for operators to manage their infrastructure with increased flexibility and reduced costs. As a result, new 5G services can now be envisioned and quickly programmed and provisioned in response to user and market necessities, imposing a paradigm shift in the services design. However, such flexibility requires the 5G transport network to undergo a profound transformation, evolving from a static connectivity substrate into a service-oriented infrastructure capable of accommodating the various 5G services, including Ultra-Reliable and Low Latency Communications (URLLC). Moreover, to achieve the desired flexibility and cost reduction, one promising approach is to leverage virtualisation technologies to dynamically host contents, services, and applications closer to the users so as to offload the core network and reduce the communication delay. This thesis tackles the above challengeswhicharedetailedinthefollowing. A common characteristic of the 5G servicesistheubiquityandthealmostpermanent connection that is required from the mobile network. This really imposes a challenge in thesignallingproceduresprovidedtogettrack of the users and to guarantee session continuity. The mobility management mechanisms will hence play a central role in the 5G networks because of the always-on connectivity demand. Distributed Mobility Management (DMM) helps going towards this direction, by flattening the network, hence improving its scalability,andenablinglocalaccesstotheInternet and other communication services, like mobile-edge clouds. Simultaneously, SDN opens up the possibility of running a multitude of intelligent and advanced applications for network optimisation purposes in a centralised network controller. The combination of DMM architectural principles with SDN management appears as a powerful tool for operators to cope with the management and data burden expected in 5G networks. To meet the future mobile user demand at a reduced cost, operators are also looking at solutions such as C-RAN and different functional splits to decrease the cost of deploying and maintaining cell sites. The increasing stress on mobile radio access performance in a context of declining revenues for operators is hence requiring the evolution of backhaul and fronthaul transport networks, which currently work decoupled. The heterogeneity of the nodes and transmisión technologies inter-connecting the fronthaul and backhaul segments makes the network quite complex, costly and inefficient to manage flexibly and dynamically. Indeed, the use of heterogeneous technologies forces operators to manage two physically separated networks, one for backhaul and one forfronthaul. In order to meet 5G requirements in a costeffective manner, a unified 5G transport network that unifies the data, control, and management planes is hence required. Such an integrated fronthaul/backhaul transport network, denoted as crosshaul, will hence carry both fronthaul and backhaul traffic operating over heterogeneous data plane technologies, which are software-controlled so as to adapt to the fluctuating capacity demand of the 5G air interfaces. Moreover, 5G transport networks will need to accommodate a wide spectrum of services on top of the same physical infrastructure. To that end, network slicing is seen as a suitable candidate for providing the necessary Quality of Service (QoS). Traffic differentiation is usually enforced at the border of the network in order to ensure a proper forwarding of the traffic according to its class through the backbone. With network slicing, the traffic may now traverse many slice edges where the traffic policy needs to be enforced, discriminated and ensured, according to the service and tenants needs. However, the very basic nature that makes this efficient management and operation possible in a flexible way – the logical centralisation – poses important challenges due to the lack of proper monitoring tools, suited for SDN-based architectures. In order to take timely and right decisions while operating a network, centralised intelligence applications need to be fed with a continuous stream of up-to-date network statistics. However, this is not feasible with current SDN solutions due to scalability and accuracy issues. Therefore, an adaptive telemetry system is required so as to support the diversity of 5G services and their stringent traffic requirements. The path towards 5G wireless networks alsopresentsacleartrendofcarryingoutcomputations close to end users. Indeed, pushing contents, applications, and network functios closer to end users is necessary to cope with thehugedatavolumeandlowlatencyrequired in future 5G networks. Edge and fog frameworks have emerged recently to address this challenge. Whilst the edge framework was more infrastructure-focused and more mobile operator-oriented, the fog was more pervasive and included any node (stationary or mobile), including terminal devices. By further utilising pervasive computational resources in proximity to users, edge and fog can be merged to construct a computing platform, which can also be used as a common stage for multiple radio access technologies (RATs) to share their information, hence opening a new dimension of multi-RAT integration.La arquitectura de las infraestructuras actuales de los operadores está siendo desafiada por la demanda creciente e incesante de servicios con un elevado consumo de datos que aparecen todos los días. Mientras que las redes de operadores implementadas actualmente han sido capaces de lidiar con las demandas de tráfico hasta ahora, se espera que las arquitecturas de la quinta generación de redes móviles (5G) soporten cargas de tráfico sin precedentes a la vez que disminuyen los costes asociados a la implementación y operaciones de la red. De hecho, el próximo conjunto de estándares 5G traerá la programabilidad y flexibilidad a niveles nunca antes vistos. Esto ha requerido la introducción de cambios en la arquitectura de las redes móviles, lo que permite diferentes funciones, como la división de los planos de control y de datos, según sea necesario para soportar una programación rápida de planos de datos heterogéneos. La softwarisación de red se considera una herramienta clave para hacer frente a dicha evolución de red, ya que proporciona la capacidad de controlar todas las funciones de red mediante (re)programación, proporcionando así una mayor flexibilidad para cumplir requisitos heterogéneos mientras se mantienen bajos los costes operativos y de implementación. Por lo tanto, se espera una gran diversidad en términos de patrones de tráfico, multi-tenancy, requisitos de tráfico heterogéneos y estrictos en las redes 5G. Software Defined Networking (SDN) y Network Function Virtualisation (NFV) se han convertido en un conjunto de herramientas básicas para que los operadores administren su infraestructura con mayor flexibilidad y menores costes. Como resultado, los nuevos servicios 5G ahora pueden planificarse, programarse y aprovisionarse rápidamente en respuesta a las necesidades de los usuarios y del mercado, imponiendo un cambio de paradigma en el diseño de los servicios. Sin embargo, dicha flexibilidad requiere que la red de transporte 5G experimente una transformación profunda, que evoluciona de un sustrato de conectividad estática a una infraestructura orientada a servicios capaz de acomodar los diversos servicios 5G, incluso Ultra-Reliable and Low Latency Communications (URLLC). Además, para lograr la flexibilidad y la reducción de costes deseadas, un enfoque prometedores aprovechar las tecnologías de virtualización para alojar dinámicamente los contenidos, servicios y aplicaciones más cerca de los usuarios para descargar la red central y reducir la latencia. Esta tesis aborda los desafíos anteriores que se detallan a continuación. Una característica común de los servicios 5G es la ubicuidad y la conexión casi permanente que se requiere para la red móvil. Esto impone un desafío en los procedimientos de señalización proporcionados para hacer un seguimiento de los usuarios y garantizar la continuidad de la sesión. Por lo tanto, los mecanismos de gestión de la movilidad desempeñarán un papel central en las redes 5G debido a la demanda de conectividad siempre activa. Distributed Mobility Management (DMM) ayuda a ir en esta dirección, al aplanar la red, lo que mejora su escalabilidad y permite el acceso local a Internet y a otros servicios de comunicaciones, como recursos en “nubes” situadas en el borde de la red móvil. Al mismo tiempo, SDN abre la posibilidad de ejecutar una multitud de aplicaciones inteligentes y avanzadas para optimizar la red en un controlador de red centralizado. La combinación de los principios arquitectónicos DMM con SDN aparece como una poderosa herramienta para que los operadores puedan hacer frente a la carga de administración y datos que se espera en las redes 5G. Para satisfacer la demanda futura de usuarios móviles a un coste reducido, los operadores también están buscando soluciones tales como C-RAN y diferentes divisiones funcionales para disminuir el coste de implementación y mantenimiento de emplazamientos celulares. El creciente estrés en el rendimiento del acceso a la radio móvil en un contexto de menores ingresos para los operadores requiere, por lo tanto, la evolución de las redes de transporte de backhaul y fronthaul, que actualmente funcionan disociadas. La heterogeneidad de los nodos y las tecnologías de transmisión que interconectan los segmentos de fronthaul y backhaul hacen que la red sea bastante compleja, costosa e ineficiente para gestionar de manera flexible y dinámica. De hecho, el uso de tecnologías heterogéneas obliga a los operadores a gestionar dos redes separadas físicamente, una para la red de backhaul y otra para el fronthaul. Para cumplir con los requisitos de 5G de manera rentable, se requiere una red de transporte única 5G que unifique los planos de control, datos y de gestión. Dicha red de transporte fronthaul/backhaul integrada, denominada “crosshaul”, transportará tráfico de fronthaul y backhaul operando sobre tecnologías heterogéneas de plano de datos, que están controladas por software para adaptarse a la demanda de capacidad fluctuante de las interfaces radio 5G. Además, las redes de transporte 5G necesitarán acomodar un amplio espectro de servicios sobre la misma infraestructura física y el network slicing se considera un candidato adecuado para proporcionar la calidad de servicio necesario. La diferenciación del tráfico generalmente se aplica en el borde de la red para garantizar un reenvío adecuado del tráfico según su clase a través de la red troncal. Con el networkslicing, el tráfico ahora puede atravesar muchos fronteras entre “network slices” donde la política de tráfico debe aplicarse, discriminarse y garantizarse, de acuerdo con las necesidades del servicio y de los usuarios. Sin embargo, el principio básico que hace posible esta gestión y operación eficientes de forma flexible – la centralización lógica – plantea importantes desafíos debido a la falta de herramientas de supervisión necesarias para las arquitecturas basadas en SDN. Para tomar decisiones oportunas y correctas mientras se opera una red, las aplicaciones de inteligencia centralizada necesitan alimentarse con un flujo continuo de estadísticas de red actualizadas. Sin embargo, esto no es factible con las soluciones SDN actuales debido a problemas de escalabilidad y falta de precisión. Por lo tanto, se requiere un sistema de telemetría adaptable para respaldar la diversidad de los servicios 5G y sus estrictos requisitos de tráfico. El camino hacia las redes inalámbricas 5G también presenta una tendencia clara de realizar acciones cerca de los usuarios finales. De hecho, acercar los contenidos, las aplicaciones y las funciones de red a los usuarios finales es necesario para hacer frente al enorme volumen de datos y la baja latencia requerida en las futuras redes 5G. Los paradigmas de “edge” y “fog” han surgido recientemente para abordar este desafío. Mientras que el edge está más centrado en la infraestructura y más orientado al operador móvil, el fog es más ubicuo e incluye cualquier nodo (fijo o móvil), incluidos los dispositivos finales. Al utilizar recursos de computación de propósito general en las proximidades de los usuarios, el edge y el fog pueden combinarse para construir una plataforma de computación, que también se puede utilizar para compartir información entre múltiples tecnologías de acceso radio (RAT) y, por lo tanto, abre una nueva dimensión de la integración multi-RAT.Programa Oficial de Doctorado en Ingeniería TelemáticaPresidente: Carla Fabiana Chiasserini.- Secretario: Vincenzo Mancuso.- Vocal: Diego Rafael López Garcí