Orchestrating datacenters and networks to facilitate the telecom cloud

In the Internet of services, information technology (IT) infrastructure providers play a critical role in making the services accessible to end-users. IT infrastructure providers host platforms and services in their datacenters (DCs). The cloud initiative has been accompanied by the introduction of new computing paradigms, such as Infrastructure as a Service (IaaS) and Software as a Service (SaaS), which have dramatically reduced the time and costs required to develop and deploy a service. However, transport networks become crucial to make services accessible to the user and to operate DCs. Transport networks are currently configured with big static fat pipes based on capacity over-provisioning aiming at guaranteeing traffic demand and other parameters committed in Service Level Agreement (SLA) contracts. Notwithstanding, such over-dimensioning adds high operational costs for DC operators and service providers. Therefore, new mechanisms to provide reconfiguration and adaptability of the transport network to reduce the amount of over-provisioned bandwidth are required. Although cloud-ready transport network architecture was introduced to handle the dynamic cloud and network interaction and Elastic Optical Networks (EONs) can facilitate elastic network operations, orchestration between the cloud and the interconnection network is eventually required to coordinate resources in both strata in a coherent manner. In addition, the explosion of Internet Protocol (IP)-based services requiring not only dynamic cloud and network interaction, but also additional service-specific SLA parameters and the expected benefits of Network Functions Virtualization (NFV), open the opportunity to telecom operators to exploit that cloud-ready transport network and their current infrastructure, to efficiently satisfy network requirements from the services. In the telecom cloud, a pay-per-use model can be offered to support services requiring resources from the transport network and its infrastructure. In this thesis, we study connectivity requirements from representative cloud-based services and explore connectivity models, architectures and orchestration schemes to satisfy them aiming at facilitating the telecom cloud. The main objective of this thesis is demonstrating, by means of analytical models and simulation, the viability of orchestrating DCs and networks to facilitate the telecom cloud. To achieve the main goal we first study the connectivity requirements for DC interconnection and services on a number of scenarios that require connectivity from the transport network. Specifically, we focus on studying DC federations, live-TV distribution, and 5G mobile networks. Next, we study different connectivity schemes, algorithms, and architectures aiming at satisfying those connectivity requirements. In particular, we study polling-based models for dynamic inter-DC connectivity and propose a novel notification-based connectivity scheme where inter-DC connectivity can be delegated to the network operator. Additionally, we explore virtual network topology provisioning models to support services that require service-specific SLA parameters on the telecom cloud. Finally, we focus on studying DC and network orchestration to fulfill simultaneously SLA contracts for a set of customers requiring connectivity from the transport network.En la Internet de los servicios, los proveedores de recursos relacionados con tecnologías de la información juegan un papel crítico haciéndolos accesibles a los usuarios como servicios. Dichos proveedores, hospedan plataformas y servicios en centros de datos. La oferta plataformas y servicios en la nube ha introducido nuevos paradigmas de computación tales como ofrecer la infraestructura como servicio, conocido como IaaS de sus siglas en inglés, y el software como servicio, SaaS. La disponibilidad de recursos en la nube, ha contribuido a la reducción de tiempos y costes para desarrollar y desplegar un servicio. Sin embargo, para permitir el acceso de los usuarios a los servicios así como para operar los centros de datos, las redes de transporte resultan imprescindibles. Actualmente, las redes de transporte están configuradas con conexiones estáticas y su capacidad sobredimensionada para garantizar la demanda de tráfico así como los distintos parámetros relacionados con el nivel de servicio acordado. No obstante, debido a que el exceso de capacidad en las conexiones se traduce en un elevado coste tanto para los operadores de los centros de datos como para los proveedores de servicios, son necesarios nuevos mecanismos que permitan adaptar y reconfigurar la red de forma eficiente de acuerdo a las nuevas necesidades de los servicios a los que dan soporte. A pesar de la introducción de arquitecturas que permiten la gestión de redes de transporte y su interacción con los servicios en la nube de forma dinámica, y de la irrupción de las redes ópticas elásticas, la orquestación entre la nube y la red es necesaria para coordinar de forma coherente los recursos en los distintos estratos. Además, la explosión de servicios basados el Protocolo de Internet, IP, que requieren tanto interacción dinámica con la red como parámetros particulares en los niveles de servicio además de los habituales, así como los beneficios que se esperan de la virtualización de funciones de red, representan una oportunidad para los operadores de red para explotar sus recursos y su infraestructura. La nube de operador permite ofrecer recursos del operador de red a los servicios, de forma similar a un sistema basado en pago por uso. En esta Tesis, se estudian requisitos de conectividad de servicios basados en la nube y se exploran modelos de conectividad, arquitecturas y modelos de orquestación que contribuyan a la realización de la nube de operador. El objetivo principal de esta Tesis es demostrar la viabilidad de la orquestación de centros de datos y redes para facilitar la nube de operador, mediante modelos analíticos y simulaciones. Con el fin de cumplir dicho objetivo, primero estudiamos los requisitos de conectividad para la interconexión de centros de datos y servicios en distintos escenarios que requieren conectividad en la red de transporte. En particular, nos centramos en el estudio de escenarios basados en federaciones de centros de datos, distribución de televisión en directo y la evolución de las redes móviles hacia 5G. A continuación, estudiamos distintos modelos de conectividad, algoritmos y arquitecturas para satisfacer los requisitos de conectividad. Estudiamos modelos de conectividad basados en sondeos para la interconexión de centros de datos y proponemos un modelo basado en notificaciones donde la gestión de la conectividad entre centros de datos se delega al operador de red. Estudiamos la provisión de redes virtuales para soportar en la nube de operador servicios que requieren parámetros específicos en los acuerdos de nivel de servicio además de los habituales. Finalmente, nos centramos en el estudio de la orquestación de centros de datos y redes con el objetivo de satisfacer de forma simultánea requisitos para distintos servicios.Postprint (published version

A vision-based optical character recognition system for real-time identification of tractors in a port container terminal

Automation has been seen as a promising solution to increase the productivity of modern sea port container terminals. The potential of increase in throughput, work efficiency and reduction of labor cost have lured stick holders to strive for the introduction of automation in the overall terminal operation. A specific container handling process that is readily amenable to automation is the deployment and control of gantry cranes in the container yard of a container terminal where typical operations of truck identification, loading and unloading containers, and job management are primarily performed manually in a typical terminal. To facilitate the overall automation of the gantry crane operation, we devised an approach for the real-time identification of tractors through the recognition of the corresponding number plates that are located on top of the tractor cabin. With this crucial piece of information, remote or automated yard operations can then be performed. A machine vision-based system is introduced whereby these number plates are read and identified in real-time while the tractors are operating in the terminal. In this paper, we present the design and implementation of the system and highlight the major difficulties encountered including the recognition of character information printed on the number plates due to poor image integrity. Working solutions are proposed to address these problems which are incorporated in the overall identification system.postprin

Job shop scheduling with artificial immune systems

The job shop scheduling is complex due to the dynamic environment. When the information of the jobs and machines are pre-defined and no unexpected events occur, the job shop is static. However, the real scheduling environment is always dynamic due to the constantly changing information and different uncertainties. This study discusses this complex job shop scheduling environment, and applies the AIS theory and switching strategy that changes the sequencing approach to the dispatching approach by taking into account the system status to solve this problem. AIS is a biological inspired computational paradigm that simulates the mechanisms of the biological immune system. Therefore, AIS presents appealing features of immune system that make AIS unique from other evolutionary intelligent algorithm, such as self-learning, long-lasting memory, cross reactive response, discrimination of self from non-self, fault tolerance, and strong adaptability to the environment. These features of AIS are successfully used in this study to solve the job shop scheduling problem. When the job shop environment is static, sequencing approach based on the clonal selection theory and immune network theory of AIS is applied. This approach achieves great performance, especially for small size problems in terms of computation time. The feature of long-lasting memory is demonstrated to be able to accelerate the convergence rate of the algorithm and reduce the computation time. When some unexpected events occasionally arrive at the job shop and disrupt the static environment, an extended deterministic dendritic cell algorithm (DCA) based on the DCA theory of AIS is proposed to arrange the rescheduling process to balance the efficiency and stability of the system. When the disturbances continuously occur, such as the continuous jobs arrival, the sequencing approach is changed to the dispatching approach that involves the priority dispatching rules (PDRs). The immune network theory of AIS is applied to propose an idiotypic network model of PDRs to arrange the application of various dispatching rules. The experiments show that the proposed network model presents strong adaptability to the dynamic job shop scheduling environment.postprin

Ferrimagnetic rare-earth-transition-metal heterostructures: implications for future data storage, sensors, and unconventional computing

In this work, different ferrimagnetic rare-earth-transition-metal heterostructures are investigated. The findings provide implications for future data storage, sensor, and unconventional computing devices. In the first part, ferri- and ferromagnetic films are exchange-coupled and studied as potential composite media for magnetic recording technologies. For this, the underlying individual layers are examined, too. Within this study, the influence of Pd and Pt insertion layers in ferromagnetic Co/Ni multilayers is investigated. In these systems, the maximum effective magnetic anisotropy is more than doubled by the introduced insertion layers, while the initial saturation magnetization and Curie temperature are reduced. Further, amorphous Tb-FeCo alloys and multilayers are studied as the second building block of the desired composite medium. In particular, the structural and magnetic properties are analyzed upon post-annealing. At temperatures above 400 K, irreversible effects on the structural properties are found, which also influence the magnetic properties. It is shown that these changes in properties cannot be prevented by tuning the composition or by a multilayer structure of the film. However, key insights on the structural and magnetic properties upon annealing are provided for future high-temperature devices. Afterward, the exchange-coupled ferrimagnetic/ferromagnetic bilayer is studied. Measurements on the dependency on temperature, the ferrimagnetic composition, and the thickness of the ferromagnet are carried out. Two distinct magnetic reversal mechanisms are revealed. The reversal characteristics depend critically on the thickness of the ferromagnetic layer. The underlying microscopic origin is revealed by high-resolution magnetic force microscopy. Above a certain thickness of the ferromagnet, the switching process is driven by in-plane domain wall propagation. In contrast, thinner ferromagnetic layers exhibit a nucleation-dominated reversal due to grain-to-grain variations in magnetic anisotropy. Although the realization of an exchange-coupled composite medium for magnetic recording can not be achieved, insights for the future realization of sub micron high energy density permanent magnets and spintronic devices are gained. In the second part of this work, topologically protected spin structures, including skyrmions and antiskyrmions, are investigated in Fe/Gd-based multilayers. Particularly in coexisting phases, different topologically protected magnetic quasi-particles may show fascinating physics and potential for spintronic devices. While skyrmions are observed in a wide range of materials, until now, antiskyrmions have been exclusive to materials with D2d or S4 symmetry. In this work, first and second-order antiskyrmions are stabilized for the first time by magnetic dipole-dipole interaction. Using Lorentz transmission electron microscopy imaging, coexisting first- and second-order antiskyrmions, Bloch skyrmions, and type-2 bubbles are observed, and the range of material properties and magnetic fields where the different spin objects form and dissipate is determined. The discovered phase pocket of metastable antiskyrmions for low saturation magnetization and uniaxial magnetic anisotropy values is confirmed by micromagnetic simulations and represents a recipe, which has to be satisfied for the stabilization of antiskyrmions by dipole-dipole interaction in other material systems. Furthermore, the nucleation process of the spin objects and the influence of an in-plane magnetic field are studied. Additionally, post-deposition techniques are employed to locally change the anisotropy of the samples and influence the nucleation and stability range of the spin objects. The gained knowledge significantly simplifies future investigations of antiskyrmions. Moreover, the coexisting phases of different topologically protected spin objects and their controlled nucleation provide great potential for further studies on magnetic quasi-particle interactions, spin dynamics, as well as for possible future applications in spintronics, namely the racetrack memory, skyrmionic interconnections, skyrmion-based unconventional computing, and sensor devices

Dynamic deployment of applications in wireless sensor networks

Over the past decades, the progress inWirelss Sensor Network (WSN) technology, both in terms of processing capability and energy consumption reduction, has evolved WSNs into complex systems that can gather information about the monitored environment and make prompt and intelligent decisions. In the beginning, military applications drove the research and development of WSNs, with large-scale acoustic systems for underwater surveillance, radar systems for the collection of data on air targets, and Unattended Ground Sensor (UGS) systems for ground target detection. Typical civil WSNs are basically not complex monitoring systems, whose applications encompass environment and habitat monitoring, infrastructure security and terror threat alerts, industrial sensing for machine health monitoring, and traffic control. In these WSNs, sensors gather the required information, mostly according to a fixed temporal schedule, and send it to the sink, which interfaces with a server or a computer. Only at this point data from sensors can be processed, before being stored. Recent advances in Micro-Eletro-Mechanical Systems (MEMS), low power transceivers and microprocessor dimensions have led to cost effective tiny sensor devices that combine sensing with computation, storage and communication. These developments have contributed to the efforts on interfacing WSNs with other technologies, enabling them to be one of the pillars of the Internet of Things (IoT) paradigm. In this context, WSNs take a key role in application areas such as domotics, assisted living, e-health, enhanced learning automation and industrial manufacturing logistics, business/process management, and intelligent transportation of people and goods. In doing so, a horizontal ambient intelligent infrastructure is made possible, wherein the sensing, computing and communicating tasks can be completed using programmable middleware that enables quick deployment of different applications and services. One of the major issues with WSNs is the energy scarcity, due to the fact that sensors are mainly battery powered. In several cases, nodes are deployed in hostile or unpractical environments, such as underground or underwater, where replacing battery could be an unfeasible operation. Therefore, extending the network lifetime is a crucial concern. Lifetime improvement has been approached by many recent studies, from different points of view, including node deployment, routing schemes, and data aggregation Recently, with the consistent increase in WSN application complexity, the way distributed applications are deployed in WSNs is another important component that affects the network lifetime. For instance, incorrect execution of data processing in some nodes or the transmission of big amounts of data with low entropy in some nodes could heavily deplete battery energy without any benefit. Indeed, application tasks are usually assigned statically to WSN nodes, which is an approach in contrast with the dynamic nature of future WSNs, where nodes frequently join and leave the network and applications change over the time. This brings to issue talked in this thesis, which is defined as follows. Dynamic deployment of distributed applications in WSNs: given the requirements of WSN applications, mostly in terms of execution time and data processing, the optimal allocation of tasks among the nodes should be identified so as to reach the application target and to satisfy the requirements while optimizing the network performance in terms of network lifetime. This issue should be continuously addressed to dynamically adapt the system to changes in terms of application requirements and network topology

Intelligent based Packet Scheduling Scheme using Internet Protocol/Multi-Protocol Label Switching (IP/MPLS) Technology for 5G. Design and Investigation of Bandwidth Management Technique for Service-Aware Traffic Engineering using Internet Protocol/Multi-Protocol Label Switching (IP/MPLS) for 5G

Multi-Protocol Label Switching (MPLS) makes use of traffic engineering (TE) techniques and a variety of protocols to establish pre-determined highly efficient routes in Wide Area Network (WAN). Unlike IP networks in which routing decision has to be made through header analysis on a hop-by-hop basis, MPLS makes use of a short bit sequence that indicates the forwarding equivalence class (FEC) of a packet and utilises a predefined routing table to handle packets of a specific FEC type. Thus header analysis of packets is not required, resulting in lower latency. In addition, packets of similar characteristics can be routed in a consistent manner. For example, packets carrying real-time information can be routed to low latency paths across the networks. Thus the key success to MPLS is to efficiently control and distribute the bandwidth available between applications across the networks. A lot of research effort on bandwidth management in MPLS networks has already been devoted in the past. However, with the imminent roll out of 5G, MPLS is seen as a key technology for mobile backhaul. To cope with the 5G demands of rich, context aware and multimedia-based user applications, more efficient bandwidth management solutions need to be derived. This thesis focuses on the design of bandwidth management algorithms, more specifically QoS scheduling, in MPLS network for 5G mobile backhaul. The aim is to ensure the reliability and the speed of packet transfer across the network. As 5G is expected to greatly improve the user experience with innovative and high quality services, users’ perceived quality of service (QoS) needs to be taken into account when deriving such bandwidth management solutions. QoS expectation from users are often subjective and vague. Thus this thesis proposes the use of fuzzy logic based solution to provide service aware and user-centric bandwidth management in order to satisfy requirements imposed by the network and users. Unfortunately, the disadvantage of fuzzy logic is scalability since dependable fuzzy rules and membership functions increase when the complexity of being modelled increases. To resolve this issue, this thesis proposes the use of neuro-fuzzy to solicit interpretable IF-THEN rules.The algorithms are implemented and tested through NS2 and Matlab simulations. The performance of the algorithms are evaluated and compared with other conventional algorithms in terms of average throughput, delay, reliability, cost, packet loss ratio, and utilization rate. Simulation results show that the neuro-fuzzy based algorithm perform better than fuzzy and other conventional packet scheduling algorithms using IP and IP over MPLS technologies.Tertiary Education Trust Fund (TETFUND

Physical Layer Aware Optical Networks

This thesis describes novel contributions in the field of physical layer aware optical networks. IP traffic increase and revenue compression in the Telecom industry is putting a lot of pressure on the optical community to develop novel solutions that must both increase total capacity while being cost effective. This requirement is pushing operators towards network disaggregation, where optical network infrastructure is built by mix and match different physical layer technologies from different vendors. In such a novel context, every equipment and transmission technique at the physical layer impacts the overall network behavior. Hence, methods giving quantitative evaluations of individual merit of physical layer equipment at network level are a firm request during network design phases as well as during network lifetime. Therefore, physical layer awareness in network design and operation is fundamental to fairly assess the potentialities, and exploit the capabilities of different technologies. From this perspective, propagation impairments modeling is essential. In this work propagation impairments in transparent optical networks are summarized, with a special focus on nonlinear effects. The Gaussian Noise model is reviewed, then extended for wideband scenarios. To do so, the impact of polarization mode dispersion on nonlinear interference (NLI) generation is assessed for the first time through simulation, showing its negligible impact on NLI generation. Thanks to this result, the Gaussian Noise model is generalized to assess the impact of space and frequency amplitude variations along the fiber, mainly due to stimulated Raman scattering, on NLI generation. The proposed Generalized GN (GGN) model is experimentally validated on a setup with commercial linecards, compared with other modeling options, and an example of application is shown. Then, network-level power optimization strategies are discussed, and the Locally Optimization Global Optimization (LOGO) approach reviewed. After that, a novel framework of analysis for optical networks that leverages detailed propagation impairment modeling called the Statistical Network Assessment Process (SNAP) is presented. SNAP is motivated by the need of having a general framework to assess the impact of different physical layer technologies on network performance, without relying on rigid optimization approaches, that are not well-suited for technology comparison. Several examples of applications of SNAP are given, including comparisons of transceivers, amplifiers and node technologies. SNAP is also used to highlight topological bottlenecks in progressively loaded network scenarios and to derive possible solutions for them. The final work presented in this thesis is related to the implementation of a vendor agnostic quality of transmission estimator for multi-vendor optical networks developed in the context of the Physical Simulation Environment group of the Telecom Infra Project. The implementation of a module based on the GN model is briefly described, then results of a multi-vendor experimental validation performed in collaboration with Microsoft are shown