Control designs and reinforcement learning-based management for software defined networks

In this thesis, we focus our investigations around the novel software defined net- working (SDN) paradigm. The central goal of SDN is to smoothly introduce centralised control capabilities to the otherwise distributed computer networks. This is achieved by abstracting and concentrating network control functionalities in a logically centralised control unit, which is referred to as the SDN controller. To further balance between centralised control, scalability and reliability considerations, distributed SDN is introduced to enable the coexistence of multiple physical SDN controllers. For distributed SDN, networking elements are grouped together to form various domains, with each domain managed by an SDN controller. In such a distributed SDN setting, SDN controllers of all domains synchronise with each other to maintain logically centralised network views, which is referred to as controller synchronisation. Centred on the problem of SDN controller synchronisation, this thesis specifically aims at addressing two aspects of the subject as follows. First, we model and analyse the performance enhancements brought by controller synchronisation in distributed SDN from a theoretical perspective. Second, we design intelligent controller synchronisation policies by leveraging existing and creating new Reinforcement Learning (RL) and Deep Learning (DL)-based approaches. In order to understand the performance gains of SDN controller synchronisation from a fundamental and analytical perspective, we propose a two-layer network model based on graphs to capture various characteristics of distributed SDN net- works. Then, we develop two families of analytical methods to investigate the performance of distributed SDN in relationship to network structure and the level of SDN controller synchronisation. The significance of our analytical results is that they can be used to quantify the contribution of controller synchronisation level, in improving the network performance under different network parameters. Therefore, they serve as fundamental guidelines for future SDN performance analyses and protocol designs. For the designs of SDN controller synchronisation policies, most existing works focus on the engineering-centred system design aspect of the problem for ensuring anomaly-free synchronisation. Instead, we emphasise on the performance improvements with respect to (w.r.t.) various networking tasks for designing controller synchronisation policies. Specifically, we investigate various scenarios with diverse control objectives, which range from routing related performance metric to other more sophisticated optimisation goals involving communication and computation resources in networks. We also take into consideration factors such as the scalability and robustness of the policies developed. For this goal, we employ machine learning techniques to assist our policy designs. In particular, we model the SDN controller synchronisation policy as serial decision-making processes and resort to RL-based techniques for developing the synchronisation policy. To this end, we leverage a combination of various RL and DL methods, which are tailored for handling the specific characteristics and requirements in different scenarios. Evaluation results show that our designed policies consistently outperform some already in-use controller synchronisation policies, in certain cases by considerable margins. While exploring existing RL algorithms for solving our problems, we identify some critical issues embedded within these algorithms, such as the enormity of the state-action space, which can cause inefficiency in learning. As such, we propose a novel RL algorithm to address these issues, which is named state action separable reinforcement learning (sasRL). Therefore, the sasRL approach constitutes another major contribution of this thesis in the field of RL research.Open Acces

Data Movement Challenges and Solutions with Software Defined Networking

With the recent rise in cloud computing, applications are routinely accessing and interacting with data on remote resources. Interaction with such remote resources for the operation of media-rich applications in mobile environments is also on the rise. As a result, the performance of the underlying network infrastructure can have a significant impact on the quality of service experienced by the user. Despite receiving significant attention from both academia and industry, computer networks still face a number of challenges. Users oftentimes report and complain about poor experiences with their devices and applications, which can oftentimes be attributed to network performance when downloading or uploading application data. This dissertation investigates problems that arise with data movement across computer networks and proposes novel solutions to address these issues through software defined networking (SDN). SDN is lauded to be the paradigm of choice for next generation networks. While academia explores use cases in various contexts, industry has focused on data center and wide area networks. There is a significant range of complex and application-specific network services that can potentially benefit from SDN, but introduction and adoption of such solutions remains slow in production networks. One impeding factor is the lack of a simple yet expressive enough framework applicable to all SDN services across production network domains. Without a uniform framework, SDN developers create disjoint solutions, resulting in untenable management and maintenance overhead. The SDN-based solutions developed in this dissertation make use of a common agent-based approach. The architecture facilitates application-oriented SDN design with an abstraction composed of software agents on top of the underlying network. There are three key components modern and future networks require to deliver exceptional data transfer performance to the end user: (1) user and application mobility, (2) high throughput data transfer, and (3) efficient and scalable content distribution. Meeting these key components will not only ensure the network can provide robust and reliable end-to-end connectivity, but also that network resources will be used efficiently. First, mobility support is critical for user applications to maintain connectivity to remote, cloud-based resources. Today\u27s network users are frequently accessing such resources while on the go, transitioning from network to network with the expectation that their applications will continue to operate seamlessly. As users perform handovers between heterogeneous networks or between networks across administrative domains, the application becomes responsible for maintaining or establishing new connections to remote resources. Although application developers often account for such handovers, the result is oftentimes visible to the user through diminished quality of service (e.g. rebuffering in video streaming applications). Many intra-domain handover solutions exist for handovers in WiFi and cellular networks, such as mobile IP, but they are architecturally complex and have not been integrated to form a scalable, inter-domain solution. A scalable framework is proposed that leverages SDN features to implement both horizontal and vertical handovers for heterogeneous wireless networks within and across administrative domains. User devices can select an appropriate network using an on-board virtual SDN implementation that manages available network interfaces. An SDN-based counterpart operates in the network core and edge to handle user migrations as they transition from one edge attachment point to another. The framework was developed and deployed as an extension to the Global Environment for Network Innovations (GENI) testbed; however, the framework can be deployed on any OpenFlow enabled network. Evaluation revealed users can maintain existing application connections without breaking the sockets and requiring the application to recover. Second, high throughput data transfer is essential for user applications to acquire large remote data sets. As data sizes become increasingly large, often combined with their locations being far from the applications, the well known impact of lower Transmission Control Protocol (TCP) throughput over large delay-bandwidth product paths becomes more significant to these applications. While myriads of solutions exist to alleviate the problem, they require specialized software and/or network stacks at both the application host and the remote data server, making it hard to scale up to a large range of applications and execution environments. This results in high throughput data transfer that is available to only a select subset of network users who have access to such specialized software. An SDN based solution called Steroid OpenFlow Service (SOS) has been proposed as a network service that transparently increases the throughput of TCP-based data transfers across large networks. SOS shifts the complexity of high performance data transfer from the end user to the network; users do not need to configure anything on the client and server machines participating in the data transfer. The SOS architecture supports seamless high performance data transfer at scale for multiple users and for high bandwidth connections. Emphasis is placed on the use of SOS as a part of a larger, richer data transfer ecosystem, complementing and compounding the efforts of existing data transfer solutions. Non-TCP-based solutions, such as Aspera, can operate seamlessly alongside an SOS deployment, while those based on TCP, such as wget, curl, and GridFTP, can leverage SOS for throughput improvement beyond what a single TCP connection can provide. Through extensive evaluation in real-world environments, the SOS architecture is proven to be flexibly deployable on a variety of network architectures, from cloud-based, to production networks, to scaled up, high performance data center environments. Evaluation showed that the SOS architecture scales linearly through the addition of SOS “agents†to the SOS deployment, providing data transfer performance improvement to multiple users simultaneously. An individual data transfer enhanced by SOS was shown to have increased throughput nearly forty times the same data transfer without SOS assistance. Third, efficient and scalable video content distribution is imperative as the demand for multimedia content over the Internet increases. Current state of the art solutions consist of vast content distribution networks (CDNs) where content is oftentimes hosted in duplicate at various geographically distributed locations. Although CDNs are useful for the dissemination of static content, they do not provide a clear and scalable model for the on demand production and distribution of live, streaming content. IP multicast is a popular solution to scalable video content distribution; however, it is seldom used due to deployment and operational complexity. Inspired from the distributed design of todays CDNs and the distribution trees used by IP multicast, a SDN based framework called GENI Cinema (GC) is proposed to allow for the distribution of live video content at scale. GC allows for the efficient management and distribution of live video content at scale without the added architectural complexity and inefficiencies inherent to contemporary solutions such as IP multicast. GC has been deployed as an experimental, nation-wide live video distribution service using the GENI network, broadcasting live and prerecorded video streams from conferences for remote attendees, from the classroom for distance education, and for live sporting events. GC clients can easily and efficiently switch back and forth between video streams with improved switching latency latency over cable, satellite, and other live video providers. The real world dep loyments and evaluation of the proposed solutions show how SDN can be used as a novel way to solve current data transfer problems across computer networks. In addition, this dissertation is expected to provide guidance for designing, deploying, and debugging SDN-based applications across a variety of network topologies

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

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

Cellular, Wide-Area, and Non-Terrestrial IoT: A Survey on 5G Advances and the Road Towards 6G

The next wave of wireless technologies is proliferating in connecting things among themselves as well as to humans. In the era of the Internet of things (IoT), billions of sensors, machines, vehicles, drones, and robots will be connected, making the world around us smarter. The IoT will encompass devices that must wirelessly communicate a diverse set of data gathered from the environment for myriad new applications. The ultimate goal is to extract insights from this data and develop solutions that improve quality of life and generate new revenue. Providing large-scale, long-lasting, reliable, and near real-time connectivity is the major challenge in enabling a smart connected world. This paper provides a comprehensive survey on existing and emerging communication solutions for serving IoT applications in the context of cellular, wide-area, as well as non-terrestrial networks. Specifically, wireless technology enhancements for providing IoT access in fifth-generation (5G) and beyond cellular networks, and communication networks over the unlicensed spectrum are presented. Aligned with the main key performance indicators of 5G and beyond 5G networks, we investigate solutions and standards that enable energy efficiency, reliability, low latency, and scalability (connection density) of current and future IoT networks. The solutions include grant-free access and channel coding for short-packet communications, non-orthogonal multiple access, and on-device intelligence. Further, a vision of new paradigm shifts in communication networks in the 2030s is provided, and the integration of the associated new technologies like artificial intelligence, non-terrestrial networks, and new spectra is elaborated. Finally, future research directions toward beyond 5G IoT networks are pointed out.Comment: Submitted for review to IEEE CS&

Distributed Resource Management in Converged Telecommunication Infrastructures

Η πέμπτη γενιά (5G) των ασύρματων και κινητών επικοινωνιών αναμένεται να έχει εκτεταμένο αντίκτυπο σε τομείς πέρα από αυτόν της τεχνολογίας πληροφοριών και επικοινωνιών (Information and Communications Technology - ICT). Το 5G ευθυγραμμίζεται με την 4η βιομηχανική εξέλιξη (4th industrial evolution), θολώνοντας τα όρια μεταξύ της φυσικής, της ψηφιακής και της βιολογικής σφαίρας. Σχεδιάστηκε για να προσφέρει δυνατότητες πολλαπλών υπηρεσιών και χρηστών, εκπληρώνοντας ταυτόχρονα πολλαπλές απαιτήσεις και επιχειρηματικά οικοσυστήματα. Ωστόσο, ορισμένες υπηρεσίες, όπως η επαυξημένη πραγματικότητα (Augmented Reality -AR), το εργοστάσιο του μέλλοντος (Factory of the Future) κ.λπ. θέτουν προκλήσεις για την ανάπτυξη μιας ενιαίας 5G υποδομής με βάση την ενεργειακή και οικονομική αποδοτικότητα. Σε αυτή τη κατεύθυνση, η παρούσα διδακτορική διατριβή υιοθετεί την ιδέα μιας καθολικής πλατφόρμας 5G που ενσωματώνει μια πληθώρα τεχνολογιών δικτύωσης (ασύρματες και ενσύρματες), και στοχεύει στην ανάπτυξη μαθηματικών εργαλείων, αλγορίθμων και πρωτοκόλλων για την ενεργειακή και λειτουργική βελτιστοποίηση αυτής της υποδομής και των υπηρεσιών που παρέχει. Αυτή η υποδομή διασυνδέει υπολογιστικούς, αποθηκευτικούς και δικτυακούς πόρους μέσω του προγραμματιζόμενου υλισμικού (hardware-HW) και της λογισμικοποίησης του δικτύου (network softwarisation). Με αυτό τον τρόπο, επιτρέπει την παροχή οποιασδήποτε υπηρεσίας με την ευέλικτη και αποτελεσματική μίξη και αντιστοίχιση πόρων δικτύου, υπολογισμού και αποθήκευσης. Αρχικά, η μελέτη επικεντρώνεται στις προκλήσεις των δικτύων ραδιοπρόσβασης επόμενης γενιάς (NG-RAN), τα οποία αποτελούνται από πολλαπλές τεχνολογίες δικτύου για τη διασύνδεση ενός ευρέος φάσματος συσκευών με υπολογιστικούς και αποθηκευτικούς πόρους. Η ανάπτυξη μικρών κυψελών (small cells) είναι ζωτικής σημασίας για τη βελτίωση της φασματικής απόδοσης και της ρυθμαπόδοσης και μπορεί να επιτευχθεί είτε μέσω παραδοσιακών κατανεμημένων δικτύων ραδιοπρόσβασης (D-RAN) είτε μέσω δικτύων ραδιοπρόσβασης νέφους (C-RAN). Ενώ το C-RAN προσφέρει μεγάλα οφέλη όσο αφορά την επεξεργασία σήματος και τον συντονισμό σε σχέση με τα D-RAN, απαιτεί υψηλό εύρος ζώνης μετάδοσης και επιβάλλει σοβαρούς περιορισμούς καθυστέρησης στο δίκτυο μεταφοράς. Για την αντιμετώπιση αυτών των ζητημάτων, προτείνεται μια νέα αρχιτεκτονική «αποσύνθεσης των πόρων». Σύμφωνα με αυτήν, οι λειτουργιές βασικής επεξεργασίας σήματος (BBU functions) μπορούν να διαχωριστούν και να εκτελεστούν είτε στην ίδια θέση με τη κεραία (RU), είτε απομακρυσμένα σε κάποια μονάδα επεξεργασίας που βρίσκεται κοντά (DU) ή μακριά (CU) από την κεραία. Αυτή η έννοια της «αποσύνθεσης των πόρων» επιτρέπει την πρόσβαση σε κοινόχρηστους πόρους που παρέχονται από κέντρα δεδομένων μικρής ή μεγάλης κλίμακας, χωρίς να απαιτείται ιδιοκτησία των πόρων. Ωστόσο, η προσέγγιση αυτή απαιτεί την ανάπτυξη νέων πλαισίων βελτιστοποίησης για τη βελτίωση της αποδοτικότητας και της ευελιξίας των υποδομών 5G, ώστε να διαχειρίζονται αποτελεσματικά τους διαχωρισμένους πόρους. Καθοριστικό ρόλο σε αυτό αποτελεί η αρχιτεκτονική της Δικτύωσης Καθορισμένης από Λογισμικό (SDN), η οποία στοχεύει να επιτρέψει την προγραμματιζόμενη και δυναμική διαχείριση των πόρων του δικτύου μέσω κεντρικού ελέγχου. Έχοντας υπόψιν τα παραπάνω, στο πρώτο μέρος της διατριβής αναπτύσσεται ένα πλαίσιο βελτιστοποίησης που προσδιορίζει το βέλτιστο λειτουργικό διαχωρισμό μεταξύ των λειτουργιών βασικής επεξεργασίας σήματος, σε συνδυασμό με τη βέλτιστη τοποθέτηση του SDN ελεγκτή, λαμβάνοντας επίσης υπόψη τη σταθερότητα του συνολικού συστήματος και τη μείωση των συνολικών λειτουργικών δαπανών. Η ανάλυση επεκτείνεται περαιτέρω με προηγμένα σχήματα βελτιστοποίησης, με σκοπό την προσέγγιση ενός πιο ρεαλιστικού περιβάλλοντος 5G, όπου η ραγδαία αύξηση της κίνησης συνεπάγεται την ανάγκη για μεγαλύτερες δυνατότητες κλιμάκωσης για τη διαχείριση των χωρικών και χρονικών μεταβολών της, καθώς και τερματικών με διαφορετικές απαιτήσεις ποιότητας. Στη συνέχεια μελετούνται τα δίκτυα πυρήνα του 5G. Στα δίκτυα πυρήνα 5G κάθε λειτουργία είναι λογισμικοποιημένη (softwarized) και απομονωμένη, επιτρέποντας την ανάπτυξη της σε υλικό γενικής χρήσης. Επίσης εισάγεται ένας νέος διαχωρισμό μεταξύ των λειτουργιών του επιπέδου ελέγχου και του επιπέδου δεδομένων (Control and User Plane Seperation – CUPS) με βάση την SDN αρχιτεκτονική. Με τον τρόπο αυτό διαχωρίζεται η δικτυακή κίνηση μεταξύ των διαφορετικών 5G οντοτήτων (επίπεδο ελέγχου) και η δικτυακή κίνηση των χρηστών (επίπεδο χρήστη). Κρίσιμο ρόλο στο χειρισμό σημαντικού μέρους του επιπέδου χρήστη στα συστήματα 5G διαδραματίζει η οντότητα «λειτουργία επιπέδου χρήστη» (User Plane Function – UPF). Το UPF είναι υπεύθυνο για την προώθηση της πραγματικής κίνησης χρηστών με πολύ αυστηρές απαιτήσεις απόδοσης. Ανάλογα με τον τύπο της απαιτούμενης υπηρεσίας και την αρχιτεκτονική του δικτύου ραδιοπρόσβασης, οι κόμβοι UPF μπορούν να βρίσκονται είτε πιο κοντά είτε πιο μακριά από αυτό, ανακατευθύνοντας την κυκλοφορία σε διακομιστές κοντά στην άκρη του δικτύου για μείωση του χρόνου καθυστέρησης ή σε κεντρικές εγκαταστάσεις. Ως εκ τούτου, προκύπτει το ερώτημα της επιλογής των βέλτιστων στοιχείων UPF, καθώς η επιλογή ενός μη διαθέσιμου υπολογιστικού πόρου UPF μπορεί να οδηγήσει σε μπλοκάρισμα και καθυστερήσεις της υπηρεσίας. Για την αντιμετώπιση αυτού του ζητήματος, προτείνουμε ένα μοντέλο ειδικά σχεδιασμένο για δυναμική επιλογή βέλτιστων στοιχείων UPF με στόχο την ελαχιστοποίηση της συνολικής καθυστέρησης της υπηρεσίας. Αναπτύσσουμε συναρτήσεις κόστους για το μοντέλο χρησιμοποιώντας εργαστηριακές μετρήσεις που ελήφθησαν από μια πλατφόρμα 5G ανοιχτού κώδικα που φιλοξενείται σε περιβάλλον νέφους οπτικού κέντρου δεδομένων. Με το προτεινόμενο μοντέλο, μπορούμε να επιλέξουμε δυναμικά το καταλληλότερο στοιχείο UPF για τη χρήση υπολογιστικών πόρων, μειώνοντας τη καθυστέρηση εξυπηρέτησης. Επεκτείνοντας την έννοια αποσύνθεσης των δικτυακών πόρων, η ανάλυση εστιάζει στα συστήματα 6G, τα οποία αναμένεται να υποστηρίξουν ένα ευρύ φάσμα υπηρεσιών μέσω μιας κοινής υποδομής που διευκολύνεται από τον τεμαχισμό δικτύου (network slicing). Τα συστήματα 6G προβλέπεται να λειτουργούν με αποκεντρωμένο τρόπο, που επιτρέπει στις εφαρμογές να παρεμβαίνουν άμεσα στις διαδικασίες ελέγχου για την πιο αποτελεσματική διασφάλιση της ποιότητας εμπειρίας (Quality of Experience – QoE) των τελικών χρηστών. Αυτό πραγματοποιείται μέσω της χρήσης της οντότητας «λειτουργία εφαρμογής» (Application Function – AF), η οποία διαχειρίζεται την εφαρμογή που εκτελείται στο τερματικό χρήστη (User Equipment – UE) και στο διακομιστή (Application Server - AS) που υποστηρίζει την υπηρεσία. Το AF διαδραματίζει κρίσιμο ρόλο στην παροχή υπηρεσιών υψηλού QoE, καθώς ενημερώνεται από την εφαρμογή και μπορεί να επηρεάσει τις αποφάσεις δρομολόγησης της κυκλοφορίας. Ωστόσο, η ανεξέλεγκτη λειτουργία του AF μπορεί να οδηγήσει σε αστάθεια στο σύστημα. Για την αντιμετώπιση αυτού του ζητήματος σχεδιάζουμε, εφαρμόζουμε και αξιολογούμε θεωρητικά και πειραματικά ένα πλήρως κατανεμημένο πλαίσιο λήψης αποφάσεων για την εκχώρηση ροών (flow assignment) στα συστήματα 6G. Το πλαίσιο αυτό αποδεικνύεται ότι, υπό συγκεκριμένες συνθήκες, συγκλίνει σε ένα σταθερό σημείο που παρέχει τη βέλτιστη ισορροπία μεταξύ QoE και αποδοτικότητας κόστους. Οι συναρτήσεις κόστους που χρησιμοποιούνται ενσωματώνουν τόσο το κόστος δικτύου όσο και το υπολογιστικό κόστος, τα οποία προκύπτουν ρεαλιστικά μέσω μιας λεπτομερούς διαδικασίας που διεξάγεται σε μια λειτουργική 5G πλατφόρμα. Αυτή η διαδικασία επιτρέπει τη μοντελοποίηση της απόδοσης του συστήματος και των απαιτήσεων σε διαφορετικά σενάρια λειτουργίας, τα οποία μπορούν να βοηθήσουν στη βελτιστοποιημένη διαχείριση του κύκλου ζωής των παρεχόμενων υπηρεσιών. Τέλος, η μελέτη επικεντρώνεται στην πραγματική ανάπτυξη μιας υποδομής 5G που υποστηρίζει τον τεμαχισμό του δικτύου κατά παραγγελία από πολλαπλούς χρήστες. Ο τεμαχισμός του δικτύου επιτρέπει τον διαχωρισμό της φυσικής υποδομής δικτύου σε πολλαπλές λογικές υποδομές που μπορούν να υποστηρίξουν διαφορετικές κατηγορίες υπηρεσιών. Ένα τμήμα δικτύου (slice) έχει τους δικούς του αποκλειστικούς πόρους από το δίκτυο πρόσβασης, μεταφοράς, και πυρήνα, καθώς και στοιχεία από διάφορους τομείς κάτω από τους ίδιους ή διαφορετικούς διαχειριστές. Η κοινή χρήση της υποκείμενης φυσικής υποδομής από τα τμήματα δικτύου περιλαμβάνει την ανάπτυξη κατάλληλων διεπαφών που μπορούν να χρησιμοποιηθούν για την σύνδεση των διαφορετικών δικτυακών στοιχείων, καθώς και τη δημιουργία κατάλληλων περιγραφών (descriptors) για την εικονοποίηση των 5G λειτουργιών (Εικονικές Δικτυακές Λειτουργίες 5G - 5G Virtual Network Functions – VNFs). Η συλλογή και ο κατάλληλος συνδυασμός πολλαπλών VNF δίνει μια 5G υπηρεσία δικτύου (Network Service - NS) από άκρη σε άκρη (End to End - E2E). Μέσω μιας πλατφόρμας διαχείρισης και ενορχήστρωσης (Management and Orchestration Platform - MANO), μπορούμε να συνδυάσουμε αυτές τις υπηρεσίες δικτύου για να δημιουργήσουμε και να διαχειριστούμε ένα 5G τμήμα δικτύου. Για να επιτευχθεί αυτό, στη μελέτη αυτή χρησιμοποιείται ένας ενορχηστρωτής που ονομάζεται Open Source MANO (OSM), ο οποίος είναι συμβατός με το πρότυπο της Εικονικοποίησης Λειτουργιών Δικτύου (NFV). Αναπτύσσονται descriptors τόσο για τις λειτουργίες του επιπέδου ελέγχου του 5G, όσο και για το επίπεδο χρήστη. Συνδυάζοντας αυτούς τους descriptors, επιτυγχάνεται η δυναμική υλοποίηση πολλαπλών τμημάτων δικτύου πάνω σε μια 5G πλατφόρμα που υποστηρίζει πολλαπλούς χρήστες και φιλοξενείται σε μια υποδομή κέντρου δεδομένων. Χρησιμοποιώντας τα δημιουργημένα VNF, μπορούμε να εκτελέσουμε το δίκτυο πυρήνα με το πάτημα ενός κουμπιού και να παρέχουμε πολλαπλά τμήματα δικτύου με διαφορετικά χαρακτηριστικά.The fifth generation (5G) of wireless and mobile communications is expected to have a far-reaching impact on society and businesses beyond the information and communications technology (ICT) sector. 5G is aligned with the 4th industrial evolution, blurring the lines between the physical, digital, and biological spheres. A common design is necessary to accommodate all service types based on energy and cost efficiency. To address this, this PhD thesis adopts the idea of a universal 5G platform that integrates a variety of networking technologies (wireless and wired), and aims to develop mathematical tools, algorithms and protocols for the energy and operational optimization of this infrastructure and the services it provides. This infrastructure interconnects computing, storage and network components that are placed at different locations, using the concepts of programmable hardware (hardware-HW) and network software (network softwarisation). In this way, it enables the provision of any service by flexibly and efficiently mixing and matching network, computing and storage resources. The thesis targeted four distinct contributions. All proposed contributions are implemented and investigated experimentally in a 5G open-source lab testbed. The first contribution focused on optimal function and resource allocation adopting the innovative 5G RAN architecture, that splits flexibly the baseband processing function chain between Remote, Distributed and Central Units. This enables access to shared resources provided by micro or large-scale remote data centers, without requiring resource ownership. To support this architecture, networks adopt the Software Defined Networking (SDN) approach, where the control plane is decoupled from the data plane and the associated network devices and is centralized in a software-based controller. In this context, the goal of the proposed approach was to develop effective optimization techniques that identify the optimal functional split, along with the optimal location and size of the SDN controllers. The second contribution concentrated on solving the User Plane Function (UPF) selection problem in 5G core networks. According to the SDN paradigm 5G core control plane functions manage the network, while UPFs are responsible for handling users’ data. Depending on the 5G RAN deployment option and the nature of the service, UPF nodes can be placed closer to the network edge, directing traffic to the Multi-access Edge Computing (MEC) servers hence reducing latency, or be placed deeper into the network directing traffic to central cloud facilities. In this context, a framework that selects the optimal UPF nodes to handle user’s traffic minimizing total service delay has been proposed. The third contribution pertained to service provisioning in upcoming telecommunication systems. 6G systems require novel architectural Quality of Experience (QoE) models and resource allocation strategies that can differentiate between data streams originating from the same or multiple User Equipment (UEs), respond to changes in the underlying physical infrastructure, and scale with the number of connected devices. Currently, centralized management and network orchestration (MANO) platforms provide this functionality, but they suffer scalability issues. Therefore, future systems are anticipated to operate in a distributed manner, allowing applications to directly intervene in relevant control processes to ensure the required QoE. The proposed approach focused on developing a flow assignment model that supports applications running on UEs. The final contribution of this thesis focused on the deployment of a 5G infrastructure that supports multi-tenant network slicing on demand. Sharing of the underlying physical infrastructure was achieved through the development of suitable interfaces for integrating different network components and the creation of appropriate descriptors for virtual 5G network functions (VNFs). By collecting and combining multiple VNFs, an end-to-end 5G Network Service (NS) can be obtained. Using a MANO platform, these NSs can be combined to instantiate and manage a 5G network slice

Ecosystemic Evolution Feeded by Smart Systems

Information Society is advancing along a route of ecosystemic evolution. ICT and Internet advancements, together with the progression of the systemic approach for enhancement and application of Smart Systems, are grounding such an evolution. The needed approach is therefore expected to evolve by increasingly fitting into the basic requirements of a significant general enhancement of human and social well-being, within all spheres of life (public, private, professional). This implies enhancing and exploiting the net-living virtual space, to make it a virtuous beneficial integration of the real-life space. Meanwhile, contextual evolution of smart cities is aiming at strongly empowering that ecosystemic approach by enhancing and diffusing net-living benefits over our own lived territory, while also incisively targeting a new stable socio-economic local development, according to social, ecological, and economic sustainability requirements. This territorial focus matches with a new glocal vision, which enables a more effective diffusion of benefits in terms of well-being, thus moderating the current global vision primarily fed by a global-scale market development view. Basic technological advancements have thus to be pursued at the system-level. They include system architecting for virtualization of functions, data integration and sharing, flexible basic service composition, and end-service personalization viability, for the operation and interoperation of smart systems, supporting effective net-living advancements in all application fields. Increasing and basically mandatory importance must also be increasingly reserved for human–technical and social–technical factors, as well as to the associated need of empowering the cross-disciplinary approach for related research and innovation. The prospected eco-systemic impact also implies a social pro-active participation, as well as coping with possible negative effects of net-living in terms of social exclusion and isolation, which require incisive actions for a conformal socio-cultural development. In this concern, speed, continuity, and expected long-term duration of innovation processes, pushed by basic technological advancements, make ecosystemic requirements stricter. This evolution requires also a new approach, targeting development of the needed basic and vocational education for net-living, which is to be considered as an engine for the development of the related ‘new living know-how’, as well as of the conformal ‘new making know-how’