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

Contributing to the pathway towards 5G experimentation with an SDN-controlled network box

Καθώς η απαίτηση σε ευρυζωνικές υπηρεσίες κινητών επικοινωνιών αυξάνεται ραγδαία, τα υπάρχοντα δίκτυα κινητών επικοινωνιών πλησιάζουν τα όριά τους κάνοντας επιτακτική την ανάγκη εξέλιξής τους η οποία θα επέλθει με την τεχνολογική άφιξη της επόμενης γενιάς κινητών επικοινωνιών, ευρέως γνωστής ως 5G. Το 5G μεταφέρει όλες εκείνες τις δυνατότητες οι οποίες είναι απαραίτητες για να καλυφθούν οι συνεχώς αυξανόμενες ανάγκες σε ευρυζωνικές υπηρεσίες, να υποστηρίξουν το Internet of Things καθώς και να ενοποιήσουν ετερογενείς υπηρεσίες σε διαφορετικές βιομηχανίες. Η παρούσα διπλωματική εργασία στοχεύει να παρουσιάσει το “Network in a box”, ένα καινοτόμο εργαλείο που αναπτύξαμε στο εργαστήριο, το οποίο βασίζεται επάνω στους θεμέλιους λίθους του 5G, το SDN και το NFV. Με το SDN να είναι η νέα προσέγγιση στα δίκτυα κινητών επικοινωνιών, ο έλεγχος διαχωρίζεται από τα δεδομένα παρέχοντας τη δυνατότητα οποιεσδήποτε αποφάσεις ελέγχου, να λαμβάνονται κεντρικά, μετατρέποντας έτσι τις κλασικές δικτυακές συσκευές σε απλά προωθητικά στοιχεία του δικτύου. Η συγκεκριμένη διάταξη μιμείται ένα πραγματικό δίκτυο, το οποίο διαθέτει δυνατότητες αυτο-οργάνωσης και αυτο-βελτίωσης, προσομοιώνοντας τη λειτουργία του 5G δικτύου. Το συγκεκριμένο εργαλείο είναι επίσης ικανό να παράσχει KPI μετρικές του 5G δικτύου κάτω από πραγματικές συνθήκες ενόσω αληθινές δικτυακές συσκευές είναι συνδεδεμένες σε αυτό. Η δομή της παρούσας διπλωματικής εργασίας αναλύεται σε πέντε κεφάλαια. Το πρώτο κεφάλαιο παρουσιάζει τις προκλήσεις που σύντομα θα κληθούν να αντιμετωπίσουν τα δίκτυα κινητών επικοινωνιών και πώς αυτές μπορούν να καλυφθούν με την τεχνολογία του 5G. Το δεύτερο κεφάλαιο εισάγει την τάση στην αγορά των κινητών επικοινωνιών που διαφένεται πίσω από την επερχόμενη άφιξη του 5G, αποκαλύπτοντας το επιχειρηματικό πλαίσιο για επιχειρήσεις, καταναλωτές και συνεργασίες όπως επίσης και κάποιες περιπτώσεις χρήσης που αντικατοπτρίζουν την διαρκή εξέλιξη στις ευρυζωνικές υπηρεσίες κινητών επικοινωνιών. Το τρίτο κεφάλαιο εμπεριέχει μια μικρή επισκόπηση των τρέχοντων έργων πάνω στο 5G, τα οποία ξεκίνησαν υπό την αιγίδα της Ευρωπαϊκής Επιτροπής με τη συνεργασία προμηθευτών τεχνολογίας επικοινωνιών, παρόχων υπηρεσιών, μικρομεσαίων επιχειρήσεων και πανεπιστημίων. Γίνεται επίσης αναφορά στις βασικές τεχνολογίες του 5G και στις δραστηριότητες προτυποποίησής του. Προχωρώντας στο τέταρτο κεφάλαιο, περιγράφουμε σε βάθος την αρχιτεκτονική του 5G δικτύου, αναλύοντας τα SDN, NFV, MANO και εξετάζουμε πώς αυτά συνεισφέρουν στη βιωσιμότητα του δικτύου. Τέλος, στο πέμπτο κεφάλαιο εισάγουμε μια καινοτόμο ιδέα που αναπτύξαμε στο εργαστήριο δικτύων του πανεπιστημίου μας, ένα πλήρως αυτόνομο δικτυακό εργαλείο, το “Network in a box”. Παρουσιάζουμε σε βάθος πώς αυτός ο server μπορεί να εγκατασταθεί και να λειτουργήσει καθώς και τις δυνατότητές του κάτω από πραγματικές συνθήκες λειτουργίας του δικτύου, ενώ λαμβάνουν χώρα υποβάθμιση ποιότητας ή μη-διαθεσιμότητα στις δικτυακές ζεύξεις, παρέχοντας επίσης μετρικές από τη λειτουργία του δικτύου σε πραγματικό χρόνο.As the demand in mobile broadband is tremendously increased and the heterogeneity of the services to be covered is growing rapidly, current mobile networks are close to their limits imposing the need of an evolution which is going to be introduced by the next generation technology, the ITU IMT-2020, well known as 5G. 5G brings all those capabilities required to cover the increased mobile broadband needs, support the Internet of Things and bind heterogeneous services in different industries. This diploma thesis aims at presenting the “Network in a box”, an innovative tool we developed which is based on the key 5G principles, SDN and NFV. With Software Defined Networking (SDN) being the new approach in mobile networks, control and data plane are decoupled providing the ability to make any control related decisions centrally and transform legacy network devices to simple forwarding elements. This testbed is a portable emulated network device which is self-managed and self-optimised and can be connected between any real network devices, emulating how the 5G network will perform. This plug & play black-box testbed is also capable of providing KPI metrics of the 5G network under real circumstances when real network devices are connected to it. The structure of this diploma thesis is decomposed in five chapters. Chapter 1 presents the challenges mobile networks will shortly face due to the growing heterogeneous demands in communications towards the year 2020 and beyond and how these can be met with the upcoming 5G technology. Chapter 2 introduces the market trend behind the new era of 5G, revealing the business context for enterprises, consumers, verticals and partnerships as well as some use cases which reflect the continuous mobile broadband evolution. Chapter 3 includes a short overview of the ongoing 5G projects, initiated under the umbrella of the European Commission, with the collaboration of communications technology vendors, telecommunications operators, service providers, small and medium-sized enterprises (SMEs) and universities. There is also a reference in 5G key enabling technologies and standardisation activities as we move towards the next generation mobile networks technology. Moving forward, chapter 4 describes in detail the technological components of 5G network architecture such as SDN, NFV, MANO and examines how these 5G key enabling technologies contribute to the overall networks’ sustainability. Finally, in chapter 5 we introduce an innovative idea developed in our university’s communications network research laboratory, an autonomous emulated portable network testbed, the “Network in a box”. We present in-depth how this portable server is deployed, operates and demonstrate the way it can be connected to real network elements emulating a real 5G end-to-end customer network. Moreover, in this last chapter we present “Network in a box” capabilities under real network circumstances when link degradations or failures take place, providing also real-time network metrics

Flexible network management in software defined wireless sensor networks for monitoring application systems

Wireless Sensor Networks (WSNs) are the commonly applied information technologies of modern networking and computing platforms for application-specific systems. Today’s network computing applications are faced with high demand of reliable and powerful network functionalities. Hence, efficient network performance is central to the entire ecosystem, more especially where human life is a concern. However, effective management of WSNs remains a challenge due to problems supplemental to them. As a result, WSNs application systems such as in monitored environments, surveillance, aeronautics, medicine, processing and control, tend to suffer in terms of capacity to support compute intensive services due to limitations experienced on them. A recent technology shift proposes Software Defined Networking (SDN) for improving computing networks as well as enhancing network resource management, especially for life guarding systems. As an optimization strategy, a software-oriented approach for WSNs, known as Software Defined Wireless Sensor Network (SDWSN) is implemented to evolve, enhance and provide computing capacity to these resource constrained technologies. Software developmental strategies are applied with the focus to ensure efficient network management, introduce network flexibility and advance network innovation towards the maximum operation potential for WSNs application systems. The need to develop WSNs application systems which are powerful and scalable has grown tremendously due to their simplicity in implementation and application. Their nature of design serves as a potential direction for the much anticipated and resource abundant IoT networks. Information systems such as data analytics, shared computing resources, control systems, big data support, visualizations, system audits, artificial intelligence (AI), etc. are a necessity to everyday life of consumers. Such systems can greatly benefit from the SDN programmability strategy, in terms of improving how data is mined, analysed and committed to other parts of the system for greater functionality. This work proposes and implements SDN strategies for enhancing WSNs application systems especially for life critical systems. It also highlights implementation considerations for designing powerful WSNs application systems by focusing on system critical aspects that should not be disregarded when planning to improve core network functionalities. Due to their inherent challenges, WSN application systems lack robustness, reliability and scalability to support high computing demands. Anticipated systems must have greater capabilities to ubiquitously support many applications with flexible resources that can be easily accessed. To achieve this, such systems must incorporate powerful strategies for efficient data aggregation, query computations, communication and information presentation. The notion of applying machine learning methods to WSN systems is fairly new, though carries the potential to enhance WSN application technologies. This technological direction seeks to bring intelligent functionalities to WSN systems given the characteristics of wireless sensor nodes in terms of cooperative data transmission. With these technological aspects, a technical study is therefore conducted with a focus on WSN application systems as to how SDN strategies coupled with machine learning methods, can contribute with viable solutions on monitoring application systems to support and provide various applications and services with greater performance. To realize this, this work further proposes and implements machine learning (ML) methods coupled with SDN strategies to; enhance sensor data aggregation, introduce network flexibility, improve resource management, query processing and sensor information presentation. Hence, this work directly contributes to SDWSN strategies for monitoring application systems.Thesis (PhD)--University of Pretoria, 2018.National Research Foundation (NRF)Telkom Centre of ExcellenceElectrical, Electronic and Computer EngineeringPhDUnrestricte

Building the Future Internet through FIRE

The Internet as we know it today is the result of a continuous activity for improving network communications, end user services, computational processes and also information technology infrastructures. The Internet has become a critical infrastructure for the human-being by offering complex networking services and end-user applications that all together have transformed all aspects, mainly economical, of our lives. Recently, with the advent of new paradigms and the progress in wireless technology, sensor networks and information systems and also the inexorable shift towards everything connected paradigm, first as known as the Internet of Things and lately envisioning into the Internet of Everything, a data-driven society has been created. In a data-driven society, productivity, knowledge, and experience are dependent on increasingly open, dynamic, interdependent and complex Internet services. The challenge for the Internet of the Future design is to build robust enabling technologies, implement and deploy adaptive systems, to create business opportunities considering increasing uncertainties and emergent systemic behaviors where humans and machines seamlessly cooperate

Building the Future Internet through FIRE

The Internet as we know it today is the result of a continuous activity for improving network communications, end user services, computational processes and also information technology infrastructures. The Internet has become a critical infrastructure for the human-being by offering complex networking services and end-user applications that all together have transformed all aspects, mainly economical, of our lives. Recently, with the advent of new paradigms and the progress in wireless technology, sensor networks and information systems and also the inexorable shift towards everything connected paradigm, first as known as the Internet of Things and lately envisioning into the Internet of Everything, a data-driven society has been created. In a data-driven society, productivity, knowledge, and experience are dependent on increasingly open, dynamic, interdependent and complex Internet services. The challenge for the Internet of the Future design is to build robust enabling technologies, implement and deploy adaptive systems, to create business opportunities considering increasing uncertainties and emergent systemic behaviors where humans and machines seamlessly cooperate