Integrated IT and SDN Orchestration of multi-domain multi-layer transport networks

Telecom operators networks' management and control remains partitioned by technology, equipment supplier and networking layer. In some segments, the network operations are highly costly due to the need of the individual, and even manual, configuration of the network equipment by highly specialized personnel. In multi-vendor networks, expensive and never ending integration processes between Network Management Systems (NMSs) and the rest of systems (OSSs, BSSs) is a common situation, due to lack of adoption of standard interfaces in the management systems of the different equipment suppliers. Moreover, the increasing impact of the new traffic flows introduced by the deployment of massive Data Centers (DCs) is also imposing new challenges that traditional networking is not ready to overcome. The Fifth Generation of Mobile Technology (5G) is also introducing stringent network requirements such as the need of connecting to the network billions of new devices in IoT paradigm, new ultra-low latency applications (i.e., remote surgery) and vehicular communications. All these new services, together with enhanced broadband network access, are supposed to be delivered over the same network infrastructure. In this PhD Thesis, an holistic view of Network and Cloud Computing resources, based on the recent innovations introduced by Software Defined Networking (SDN), is proposed as the solution for designing an end-to-end multi-layer, multi-technology and multi-domain cloud and transport network management architecture, capable to offer end-to-end services from the DC networks to customers access networks and the virtualization of network resources, allowing new ways of slicing the network resources for the forthcoming 5G deployments. The first contribution of this PhD Thesis deals with the design and validation of SDN based network orchestration architectures capable to improve the current solutions for the management and control of multi-layer, multi-domain backbone transport networks. These problems have been assessed and progressively solved by different control and management architectures which has been designed and evaluated in real evaluation environments. One of the major findings of this work has been the need of developed a common information model for transport network's management, capable to describe the resources and services of multilayer networks. In this line, the Control Orchestration Protocol (COP) has been proposed as a first contriution towards an standard management interface based on the main principles driven by SDN. Furthermore, this PhD Thesis introduces a novel architecture capable to coordinate the management of IT computing resources together with inter- and intra-DC networks. The provisioning and migration of virtual machines together with the dynamic reconfiguration of the network has been successfully demonstrated in a feasible timescale. Moreover, a resource optimization engine is introduced in the architecture to introduce optimization algorithms capable to solve allocation problems such the optimal deployment of Virtual Machine Graphs over different DCs locations minimizing the inter-DC network resources allocation. A baseline blocking probability results over different network loads are also presented. The third major contribution is the result of the previous two. With a converged cloud and network infrastructure controlled and operated jointly, the holistic view of the network allows the on-demand provisioning of network slices consisting of dedicated network and cloud resources over a distributed DC infrastructure interconnected by an optical transport network. The last chapters of this thesis discuss the management and orchestration of 5G slices based over the control and management components designed in the previous chapters. The design of one of the first network slicing architectures and the deployment of a 5G network slice in a real Testbed, is one of the major contributions of this PhD Thesis.La gestión y el control de las redes de los operadores de red (Telcos), todavía hoy, está segmentado por tecnología, por proveedor de equipamiento y por capa de red. En algunos segmentos (por ejemplo en IP) la operación de la red es tremendamente costosa, ya que en muchos casos aún se requiere con guración individual, e incluso manual, de los equipos por parte de personal altamente especializado. En redes con múltiples proveedores, los procesos de integración entre los sistemas de gestión de red (NMS) y el resto de sistemas (p. ej., OSS/BSS) son habitualmente largos y extremadamente costosos debido a la falta de adopción de interfaces estándar por parte de los diferentes proveedores de red. Además, el impacto creciente en las redes de transporte de los nuevos flujos de tráfico introducidos por el despliegue masivo de Data Centers (DC), introduce nuevos desafíos que las arquitecturas de gestión y control de las redes tradicionales no están preparadas para afrontar. La quinta generación de tecnología móvil (5G) introduce nuevos requisitos de red, como la necesidad de conectar a la red billones de dispositivos nuevos (Internet de las cosas - IoT), aplicaciones de ultra baja latencia (p. ej., cirugía a distancia) y las comunicaciones vehiculares. Todos estos servicios, junto con un acceso mejorado a la red de banda ancha, deberán ser proporcionados a través de la misma infraestructura de red. Esta tesis doctoral propone una visión holística de los recursos de red y cloud, basada en los principios introducidos por Software Defined Networking (SDN), como la solución para el diseño de una arquitectura de gestión extremo a extremo (E2E) para escenarios de red multi-capa y multi-dominio, capaz de ofrecer servicios de E2E, desde las redes intra-DC hasta las redes de acceso, y ofrecer ademas virtualización de los recursos de la red, permitiendo nuevas formas de segmentación en las redes de transporte y la infrastructura de cloud, para los próximos despliegues de 5G. La primera contribución de esta tesis consiste en la validación de arquitecturas de orquestración de red, basadas en SDN, para la gestión y control de redes de transporte troncales multi-dominio y multi-capa. Estos problemas (gestion de redes multi-capa y multi-dominio), han sido evaluados de manera incremental, mediante el diseño y la evaluación experimental, en entornos de pruebas reales, de diferentes arquitecturas de control y gestión. Uno de los principales hallazgos de este trabajo ha sido la necesidad de un modelo de información común para las interfaces de gestión entre entidades de control SDN. En esta línea, el Protocolo de Control Orchestration (COP) ha sido propuesto como interfaz de gestión de red estándar para redes SDN de transporte multi-capa. Además, en esta tesis presentamos una arquitectura capaz de coordinar la gestión de los recursos IT y red. La provisión y la migración de máquinas virtuales junto con la reconfiguración dinámica de la red, han sido demostradas con éxito en una escala de tiempo factible. Además, la arquitectura incorpora una plataforma para la ejecución de algoritmos de optimización de recursos capaces de resolver diferentes problemas de asignación, como el despliegue óptimo de Grafos de Máquinas Virtuales (VMG) en diferentes DCs que minimizan la asignación de recursos de red. Esta tesis propone una solución para este problema, que ha sido evaluada en terminos de probabilidad de bloqueo para diferentes cargas de red. La tercera contribución es el resultado de las dos anteriores. La arquitectura integrada de red y cloud presentada permite la creación bajo demanda de "network slices", que consisten en sub-conjuntos de recursos de red y cloud dedicados para diferentes clientes sobre una infraestructura común. El diseño de una de las primeras arquitecturas de "network slicing" y el despliegue de un "slice" de red 5G totalmente operativo en un Testbed real, es una de las principales contribuciones de esta tesis.La gestió i el control de les xarxes dels operadors de telecomunicacions (Telcos), encara avui, està segmentat per tecnologia, per proveïdors d’equipament i per capes de xarxa. En alguns segments (Per exemple en IP) l’operació de la xarxa és tremendament costosa, ja que en molts casos encara es requereix de configuració individual, i fins i tot manual, dels equips per part de personal altament especialitzat. En xarxes amb múltiples proveïdors, els processos d’integració entre els Sistemes de gestió de xarxa (NMS) i la resta de sistemes (per exemple, Sistemes de suport d’operacions - OSS i Sistemes de suport de negocis - BSS) són habitualment interminables i extremadament costosos a causa de la falta d’adopció d’interfícies estàndard per part dels diferents proveïdors de xarxa. A més, l’impacte creixent en les xarxes de transport dels nous fluxos de trànsit introduïts pel desplegament massius de Data Centers (DC), introdueix nous desafiaments que les arquitectures de gestió i control de les xarxes tradicionals que no estan llestes per afrontar. Per acabar de descriure el context, la cinquena generació de tecnologia mòbil (5G) també presenta nous requisits de xarxa altament exigents, com la necessitat de connectar a la xarxa milers de milions de dispositius nous, dins el context de l’Internet de les coses (IOT), o les noves aplicacions d’ultra baixa latència (com ara la cirurgia a distància) i les comunicacions vehiculars. Se suposa que tots aquests nous serveis, juntament amb l’accés millorat a la xarxa de banda ampla, es lliuraran a través de la mateixa infraestructura de xarxa. Aquesta tesi doctoral proposa una visió holística dels recursos de xarxa i cloud, basada en els principis introduïts per Software Defined Networking (SDN), com la solució per al disseny de una arquitectura de gestió extrem a extrem per a escenaris de xarxa multi-capa, multi-domini i consistents en múltiples tecnologies de transport. Aquesta arquitectura de gestió i control de xarxes transport i recursos IT, ha de ser capaç d’oferir serveis d’extrem a extrem, des de les xarxes intra-DC fins a les xarxes d’accés dels clients i oferir a més virtualització dels recursos de la xarxa, obrint la porta a noves formes de segmentació a les xarxes de transport i la infrastructura de cloud, pels propers desplegaments de 5G. La primera contribució d’aquesta tesi doctoral consisteix en la validació de diferents arquitectures d’orquestració de xarxa basades en SDN capaces de millorar les solucions existents per a la gestió i control de xarxes de transport troncals multi-domini i multicapa. Aquests problemes (gestió de xarxes multicapa i multi-domini), han estat avaluats de manera incremental, mitjançant el disseny i l’avaluació experimental, en entorns de proves reals, de diferents arquitectures de control i gestió. Un dels principals troballes d’aquest treball ha estat la necessitat de dissenyar un model d’informació comú per a les interfícies de gestió de xarxes, capaç de descriure els recursos i serveis de la xarxes transport multicapa. En aquesta línia, el Protocol de Control Orchestration (COP, en les seves sigles en anglès) ha estat proposat en aquesta Tesi, com una primera contribució cap a una interfície de gestió de xarxa estàndard basada en els principis bàsics de SDN. A més, en aquesta tesi presentem una arquitectura innovadora capaç de coordinar la gestió de els recursos IT juntament amb les xarxes inter i intra-DC. L’aprovisionament i la migració de màquines virtuals juntament amb la reconfiguració dinàmica de la xarxa, ha estat demostrat amb èxit en una escala de temps factible. A més, l’arquitectura incorpora una plataforma per a l’execució d’algorismes d’optimització de recursos, capaços de resoldre diferents problemes d’assignació, com el desplegament òptim de Grafs de Màquines Virtuals (VMG) en diferents ubicacions de DC que minimitzen la assignació de recursos de xarxa entre DC. També es presenta una solució bàsica per a aquest problema, així com els resultats de probabilitat de bloqueig per a diferents càrregues de xarxa. La tercera contribució principal és el resultat dels dos anteriors. Amb una infraestructura de xarxa i cloud convergent, controlada i operada de manera conjunta, la visió holística de la xarxa permet l’aprovisionament sota demanda de "network slices" que consisteixen en subconjunts de recursos d’xarxa i cloud, dedicats per a diferents clients, sobre una infraestructura de Data Centers distribuïda i interconnectada per una xarxa de transport òptica. Els últims capítols d’aquesta tesi tracten sobre la gestió i organització de "network slices" per a xarxes 5G en funció dels components de control i administració dissenyats i desenvolupats en els capítols anteriors. El disseny d’una de les primeres arquitectures de "network slicing" i el desplegament d’un "slice" de xarxa 5G totalment operatiu en un Testbed real, és una de les principals contribucions d’aquesta tesi.Postprint (published version

Reconfigurable Optically Interconnected Systems

With the immense growth of data consumption in today's data centers and high-performance computing systems driven by the constant influx of new applications, the network infrastructure supporting this demand is under increasing pressure to enable higher bandwidth, latency, and flexibility requirements. Optical interconnects, able to support high bandwidth wavelength division multiplexed signals with extreme energy efficiency, have become the basis for long-haul and metro-scale networks around the world, while photonic components are being rapidly integrated within rack and chip-scale systems. However, optical and photonic interconnects are not a direct replacement for electronic-based components. Rather, the integration of optical interconnects with electronic peripherals allows for unique functionalities that can improve the capacity, compute performance and flexibility of current state-of-the-art computing systems. This requires physical layer methodologies for their integration with electronic components, as well as system level control planes that incorporates the optical layer characteristics. This thesis explores various network architectures and the associated control plane, hardware infrastructure, and other supporting software modules needed to integrate silicon photonics and MEMS based optical switching into conventional datacom network systems ranging from intra-data center and high-performance computing systems to the metro-scale layer networks between data centers. In each of these systems, we demonstrate dynamic bandwidth steering and compute resource allocation capabilities to enable significant performance improvements. The key accomplishments of this thesis are as follows. In Part 1, we present high-performance computing network architectures that integrate silicon photonic switches for optical bandwidth steering, enabling multiple reconfigurable topologies that results in significant system performance improvements. As high-performance systems rely on increased parallelism by scaling up to greater numbers of processor nodes, communication between these nodes grows rapidly and the interconnection network becomes a bottleneck to the overall performance of the system. It has been observed that many scientific applications operating on high-performance computing systems cause highly skewed traffic over the network, congesting only a small percentage of the total available links while other links are underutilized. This mismatch of the traffic and the bandwidth allocation of the physical layer network presents the opportunity to optimize the bandwidth resource utilization of the system by using silicon photonic switches to perform bandwidth steering. This allows the individual processors to perform at their maximum compute potential and thereby improving the overall system performance. We show various testbeds that integrates both microring resonator and Mach-Zehnder based silicon photonic switches within Dragonfly and Fat-Tree topology networks built with conventional equipment, and demonstrate 30-60% reduction in execution time of real high-performance benchmark applications. Part 2 presents a flexible network architecture and control plane that enables autonomous bandwidth steering and IT resource provisioning capabilities between metro-scale geographically distributed data centers. It uses a software-defined control plane to autonomously provision both network and IT resources to support different quality of service requirements and optimizes resource utilization under dynamically changing load variations. By actively monitoring both the bandwidth utilization of the network and CPU or memory resources of the end hosts, the control plane autonomously provisions background or dynamic connections with different levels of quality of service using optical MEMS switching, as well as initializing live migrations of virtual machines to consolidate or distribute workload. Together these functionalities provide flexibility and maximize efficiency in processing and transferring data, and enables energy and cost savings by scaling down the system when resources are not needed. An experimental testbed of three data center nodes was built to demonstrate the feasibility of these capabilities. Part 3 presents Lightbridge, a communications platform specifically designed to provide a more seamless integration between processor nodes and an optically switched network. It addresses some of the crucial issues faced by the works presented in the previous chapters related to optical switching. When optical switches perform switching operations, they change the physical topology of the network, and they lack the capability to buffer packets, resulting in certain optical circuits being unavailable. This prompts the question of whether it is safe to transmit packets by end hosts at any given time. Lightbridge was developed to coordinate switching and routing of optical circuits across the network, by having the processors gain information about the current state of the optical network before transmitting packets, and being able to buffer packets when the optical circuit is not available. This part describes details of Lightbridge which is constituted by a loadable Linux kernel module along with other supporting modifications to the Linux kernel in order to achieve the necessary functionalities

Energy-efficient Communications in Cloud, Mobile Cloud and Fog Computing

This thesis studies the problem of energy efficiency of communications in distributed computing paradigms, including cloud computing, mobile cloud computing and fog/edge computing. Distributed computing paradigms have significantly changed the way of doing business. With cloud computing, companies and end users can access the vast majority services online through a virtualized environment in a pay-as-you-go basis. %Three are the main services typically consumed by cloud users are Infrastructure as a Service (IaaS), Platform as a Service (PaaS) and Software as a Service (SaaS). Mobile cloud and fog/edge computing are the natural extension of the cloud computing paradigm for mobile and Internet of Things (IoT) devices. Based on offloading, the process of outsourcing computing tasks from mobile devices to the cloud, mobile cloud and fog/edge computing paradigms have become popular techniques to augment the capabilities of the mobile devices and to reduce their battery drain. Being equipped with a number of sensors, the proliferation of mobile and IoT devices has given rise to a new cloud-based paradigm for collecting data, which is called mobile crowdsensing as for proper operation it requires a large number of participants. A plethora of communication technologies is applicable to distributing computing paradigms. For example, cloud data centers typically implement wired technologies while mobile cloud and fog/edge environments exploit wireless technologies such as 3G/4G, WiFi and Bluetooth. Communication technologies directly impact the performance and the energy drain of the system. This Ph.D. thesis analyzes from a global perspective the efficiency in using energy of communications systems in distributed computing paradigms. In particular, the following contributions are proposed: - A new framework of performance metrics for communication systems of cloud computing data centers. The proposed framework allows a fine-grain analysis and comparison of communication systems, processes, and protocols, defining their influence on the performance of cloud applications. - A novel model for the problem of computation offloading, which describes the workflow of mobile applications through a new Directed Acyclic Graph (DAG) technique. This methodology is suitable for IoT devices working in fog computing environments and was used to design an Android application, called TreeGlass, which performs recognition of trees using Google Glass. TreeGlass is evaluated experimentally in different offloading scenarios by measuring battery drain and time of execution as key performance indicators. - In mobile crowdsensing systems, novel performance metrics and a new framework for data acquisition, which exploits a new policy for user recruitment. Performance of the framework are validated through CrowdSenSim, which is a new simulator designed for mobile crowdsensing activities in large scale urban scenarios

Stochastische Analyse und lernbasierte Algorithmen zur Ressourcenbereitstellung in optischen Netzwerken

The unprecedented growth in Internet traffic has driven the innovations in provisioning of optical resources as per the need of bandwidth demands such that the resource utilization and spectrum efficiency could be maximized. With the advent of the next generation flexible optical transponders and switches, the flexible-grid-based elastic optical network (EON) is foreseen as an alternative to the widely deployed fixed-grid-based wavelength division multiplexing networks. At the same time, the flexible resource provisioning also raises new challenges for EONs. One such challenge is the spectrum fragmentation. As network traffic varies over time, spectrum gets fragmented due to the setting up and tearing down of non-uniform bandwidth requests over aligned (i.e., continuous) and adjacent (i.e., contiguous) spectrum slices, which leads to a non-optimal spectrum allocation, and generally results in higher blocking probability and lower spectrum utilization in EONs. To address this issue, the allocation and reallocation of optical resources are required to be modeled accurately, and managed efficiently and intelligently. The modeling of routing and spectrum allocation in EONs with the spectrum contiguity and spectrum continuity constraints is well-investigated, but existing models do not consider the fragmentation issue resulted by these constraints and non-uniform bandwidth demands. This thesis addresses this issue and considers both the constraints to computing exact blocking probabilities in EONs with and without spectrum conversion, and with spectrum reallocation (known as defragmentation) for the first time using the Markovian approach. As the exact network models are not scalable with respect to the network size and capacity, this thesis proposes load-independent and load-dependent approximate models to compute approximate blocking probabilities in EONs. Results show that the connection blocking due to fragmentation can be reduced by using a spectrum conversion or a defragmentation approach, but it can not be eliminated in a mesh network topology. This thesis also deals with the important network resource provisioning task in EONs. To this end, it first presents algorithmic solutions to efficiently allocate and reallocate spectrum resources using the fragmentation factor along spectral, time, and spatial dimensions. Furthermore, this thesis highlights the role of machine learning techniques in alleviating issues in static provisioning of optical resources, and presents two use-cases: handling time-varying traffic in optical data center networks, and reducing energy consumption and allocating spectrum proportionately to traffic classes in fiber-wireless networks.Die flexible Nutzung des Spektrums bringt in Elastischen Optischen Netze (EON) neue Herausforderungen mit sich, z.B., die Fragmentierung des Spektrums. Die Fragmentierung entsteht dadurch, dass die Netzwerkverkehrslast sich im Laufe der Zeit ändert und so wird das Spektrum aufgrund des Verbindungsaufbaus und -abbaus fragmentiert. Das für eine Verbindung notwendige Spektrum wird durch aufeinander folgende (kontinuierliche) und benachbarte (zusammenhängende) Spektrumsabschnitte (Slots) gebildet. Dies führt nach den zahlreichen Reservierungen und Freisetzungen des Spektrums zu einer nicht optimalen Zuordnung, die in einer höheren Blockierungs-wahrscheinlichkeit der neuen Verbindungsanfragen und einer geringeren Auslastung von EONs resultiert. Um dieses Problem zu lösen, müssen die Zuweisung und Neuzuordnung des Spektrums in EONs genau modelliert und effizient sowie intelligent verwaltet werden. Diese Arbeit beschäftigt sich mit dem Fragmentierungsproblem und berücksichtigt dabei die beiden Einschränkungen: Kontiguität und Kontinuität. Unter diesen Annahmen wurden analytische Modelle zur Berechnung einer exakten Blockierungswahrscheinlichkeit in EONs mit und ohne Spektrumskonvertierung erarbeitet. Außerdem umfasst diese Arbeit eine Analyse der Blockierungswahrscheinlichkeit im Falle einer Neuzuordnung des Sprektrums (Defragmentierung). Diese Blockierungsanalyse wird zum ersten Mal mit Hilfe der Markov-Modelle durchgeführt. Da die exakten analytischen Modelle hinsichtlich der Netzwerkgröße und -kapazität nicht skalierbar sind, werden in dieser Dissertation verkehrslastunabhängige und verkehrslastabhängige Approximationsmodelle vorgestellt. Diese Modelle bieten eine Näherung der Blockierungswahrscheinlichkeiten in EONs. Die Ergebnisse zeigen, dass die Blockierungswahrscheinlichkeit einer Verbindung aufgrund von einer Fragmentierung des Spektrums durch die Verwendung einer Spektrumkonvertierung oder eines Defragmentierungsverfahrens verringert werden kann. Eine effiziente Bereitstellung der optischen Netzwerkressourcen ist eine wichtige Aufgabe von EONs. Deswegen befasst sich diese Arbeit mit algorithmischen Lösungen, die Spektrumressource mithilfe des Fragmentierungsfaktors von Spektral-, Zeit- und räumlichen Dimension effizient zuweisen und neu zuordnen. Darüber hinaus wird die Rolle des maschinellen Lernens (ML) für eine verbesserte Bereitstellung der optischen Ressourcen untersucht und das ML basierte Verfahren mit der statischen Ressourcenzuweisung verglichen. Dabei werden zwei Anwendungsbeispiele vorgestellt und analysiert: der Umgang mit einer zeitveränderlichen Verkehrslast in optischen Rechenzentrumsnetzen, und eine Verringerung des Energieverbrauchs und die Zuweisung des Spektrums proportional zu Verkehrsklassen in kombinierten Glasfaser-Funknetzwerken