An optimized cost-based data allocation model for heterogeneous distributed computing systems

Continuous attempts have been made to improve the flexibility and effectiveness of distributed computing systems. Extensive effort in the fields of connectivity technologies, network programs, high processing components, and storage helps to improvise results. However, concerns such as slowness in response, long execution time, and long completion time have been identified as stumbling blocks that hinder performance and require additional attention. These defects increased the total system cost and made the data allocation procedure for a geographically dispersed setup difficult. The load-based architectural model has been strengthened to improve data allocation performance. To do this, an abstract job model is employed, and a data query file containing input data is processed on a directed acyclic graph. The jobs are executed on the processing engine with the lowest execution cost, and the system's total cost is calculated. The total cost is computed by summing the costs of communication, computation, and network. The total cost of the system will be reduced using a Swarm intelligence algorithm. In heterogeneous distributed computing systems, the suggested approach attempts to reduce the system's total cost and improve data distribution. According to simulation results, the technique efficiently lowers total system cost and optimizes partitioned data allocation

A Comparison of wide area network performance using virtualized and non-virtualized client architectures

The goal of this thesis is to determine if there is a significant performance difference between two network computer architecture models. The study will measure latency and throughput for both client-server and virtualized client architectures. In the client server environment, the client computer performs a significant portion of the work and frequently requires downloading uploading files to and from a remote location. Virtual client architecture turns the client machine into a terminal, sending only keystrokes and mouse clicks and receiving only display pixel or sound changes. I accomplished the goal of comparing these architectures by comparing completion times for ping reply, file download, a small set of common work tasks, and a moderately large SQL database query. I compared these tasks using simulated wide area network, local area network, and virtual client network architectures. The study limits the architecture to one where the virtual client and server are in the same data center

Energy-efficient Transitional Near-* Computing

Studies have shown that communication networks, devices accessing the Internet, and data centers account for 4.6% of the worldwide electricity consumption. Although data centers, core network equipment, and mobile devices are getting more energy-efficient, the amount of data that is being processed, transferred, and stored is vastly increasing. Recent computer paradigms, such as fog and edge computing, try to improve this situation by processing data near the user, the network, the devices, and the data itself. In this thesis, these trends are summarized under the new term near-* or near-everything computing. Furthermore, a novel paradigm designed to increase the energy efficiency of near-* computing is proposed: transitional computing. It transfers multi-mechanism transitions, a recently developed paradigm for a highly adaptable future Internet, from the field of communication systems to computing systems. Moreover, three types of novel transitions are introduced to achieve gains in energy efficiency in near-* environments, spanning from private Infrastructure-as-a-Service (IaaS) clouds, Software-defined Wireless Networks (SDWNs) at the edge of the network, Disruption-Tolerant Information-Centric Networks (DTN-ICNs) involving mobile devices, sensors, edge devices as well as programmable components on a mobile System-on-a-Chip (SoC). Finally, the novel idea of transitional near-* computing for emergency response applications is presented to assist rescuers and affected persons during an emergency event or a disaster, although connections to cloud services and social networks might be disturbed by network outages, and network bandwidth and battery power of mobile devices might be limited

NFV orchestration in edge and fog scenarios

Mención Internacional en el título de doctorLas infraestructuras de red actuales soportan una variedad diversa de servicios como video bajo demanda, video conferencias, redes sociales, sistemas de educación, o servicios de almacenamiento de fotografías. Gran parte de la población mundial ha comenzado a utilizar estos servicios, y los utilizan diariamente. Proveedores de Cloud y operadores de infraestructuras de red albergan el tráfico de red generado por estos servicios, y sus tareas de gestión no solo implican realizar el enrutamiento del tráfico, sino también el procesado del tráfico de servicios de red. Tradicionalmente, el procesado del tráfico ha sido realizado mediante aplicaciones/ programas desplegados en servidores que estaban dedicados en exclusiva a tareas concretas como la inspección de paquetes. Sin embargo, en los últimos anos los servicios de red se han virtualizado y esto ha dado lugar al paradigma de virtualización de funciones de red (Network Function Virtualization (NFV) siguiendo las siglas en ingles), en el que las funciones de red de un servicio se ejecutan en contenedores o máquinas virtuales desacopladas de la infraestructura hardware. Como resultado, el procesado de tráfico se ha ido haciendo más flexible gracias al laxo acople del software y hardware, y a la posibilidad de compartir funciones de red típicas, como firewalls, entre los distintos servicios de red. NFV facilita la automatización de operaciones de red, ya que tareas como el escalado, o la migración son típicamente llevadas a cabo mediante un conjunto de comandos previamente definidos por la tecnología de virtualización pertinente, bien mediante contenedores o máquinas virtuales. De todos modos, sigue siendo necesario decidir el en rutamiento y procesado del tráfico de cada servicio de red. En otras palabras, que servidores tienen que encargarse del procesado del tráfico, y que enlaces de la red tienen que utilizarse para que las peticiones de los usuarios lleguen a los servidores finales, es decir, el conocido como embedding problem. Bajo el paraguas del paradigma NFV, a este problema se le conoce en inglés como Virtual Network Embedding (VNE), y esta tesis utiliza el termino “NFV orchestration algorithm” para referirse a los algoritmos que resuelven este problema. El problema del VNE es NP-hard, lo cual significa que que es imposible encontrar una solución optima en un tiempo polinómico, independientemente del tamaño de la red. Como consecuencia, la comunidad investigadora y de telecomunicaciones utilizan heurísticos que encuentran soluciones de manera más rápida que productos para la resolución de problemas de optimización. Tradicionalmente, los “NFV orchestration algorithms” han intentado minimizar los costes de despliegue derivados de las soluciones asociadas. Por ejemplo, estos algoritmos intentan no consumir el ancho de banda de la red, y usar rutas cortas para no utilizar tantos recursos. Además, una tendencia reciente ha llevado a la comunidad investigadora a utilizar algoritmos que minimizan el consumo energético de los servicios desplegados, bien mediante la elección de dispositivos con un consumo energético más eficiente, o mediante el apagado de dispositivos de red en desuso. Típicamente, las restricciones de los problemas de VNE se han resumido en un conjunto de restricciones asociadas al uso de recursos y consumo energético, y las soluciones se diferenciaban por la función objetivo utilizada. Pero eso era antes de la 5a generación de redes móviles (5G) se considerase en el problema de VNE. Con la aparición del 5G, nuevos servicios de red y casos de uso entraron en escena. Los estándares hablaban de comunicaciones ultra rápidas y fiables (Ultra-Reliable and Low Latency Communications (URLLC) usando las siglas en inglés) con latencias por debajo de unos pocos milisegundos y fiabilidades del 99.999%, una banda ancha mejorada (enhanced Mobile Broadband (eMBB) usando las siglas en inglés) con notorios incrementos en el flujo de datos, e incluso la consideración de comunicaciones masivas entre maquinas (Massive Machine-Type Communications (mMTC) usando las siglas en inglés) entre dispositivos IoT. Es más, paradigmas como edge y fog computing se incorporaron a la tecnología 5G, e introducían la idea de tener dispositivos de computo más cercanos al usuario final. Como resultado, el problema del VNE tenía que incorporar los nuevos requisitos como restricciones a tener en cuenta, y toda solución debía satisfacer bajas latencias, alta fiabilidad, y mayores tasas de transmisión. Esta tesis estudia el problema des VNE, y propone algunos heurísticos que lidian con las restricciones asociadas a servicios 5G en escenarios edge y fog, es decir, las soluciones propuestas se encargan de asignar funciones virtuales de red a servidores, y deciden el enrutamiento del trafico en las infraestructuras 5G con dispositivos edge y fog. Para evaluar el rendimiento de las soluciones propuestas, esta tesis estudia en primer lugar la generación de grafos que representan redes 5G. Los mecanismos propuestos para la generación de grafos sirven para representar distintos escenarios 5G. En particular, escenarios de federación en los que varios dominios comparten recursos entre ellos. Los grafos generados también representan servidores en el edge, así como dispositivos fog con una batería limitada. Además, estos grafos tienen en cuenta los requisitos de estándares, y la demanda que se espera en las redes 5G. La generación de grafos propuesta sirve para representar escenarios federación en los que varios dominios comparten recursos entre ellos, y redes 5G con servidores edge, así como dispositivos fog estáticos o móviles con una batería limitada. Los grafos generados para infraestructuras 5G tienen en cuenta los requisitos de estándares, y la demanda de red que se espera en las redes 5G. Además, los grafos son diferentes en función de la densidad de población, y el área de estudio, es decir, si es una zona industrial, una autopista, o una zona urbana. Tras detallar la generación de grafos que representan redes 5G, esta tesis propone algoritmos de orquestación NFV para resolver con el problema del VNE. Primero, se centra en escenarios federados en los que los servicios de red se tienen que asignar no solo a la infraestructura de un dominio, sino a los recursos compartidos en la federación de dominios. Dos problemas diferentes han sido estudiados, uno es el problema del VNE propiamente dicho sobre una infraestructura federada, y el otro es la delegación de servicios de red. Es decir, si un servicio de red se debe desplegar localmente en un dominio, o en los recursos compartidos por la federación de dominios; a sabiendas de que el último caso supone el pago de cuotas por parte del dominio local a cambio del despliegue del servicio de red. En segundo lugar, esta tesis propone OKpi, un algoritmo de orquestación NFV para conseguir la calidad de servicio de las distintas slices de las redes 5G. Conceptualmente, el slicing consiste en partir la red de modo que cada servicio de red sea tratado de modo diferente dependiendo del trozo al que pertenezca. Por ejemplo, una slice de eHealth reservara los recursos de red necesarios para conseguir bajas latencias en servicios como operaciones quirúrgicas realizadas de manera remota. Cada trozo (slice) está destinado a unos servicios específicos con unos requisitos muy concretos, como alta fiabilidad, restricciones de localización, o latencias de un milisegundo. OKpi es un algoritmo de orquestación NFV que consigue satisfacer los requisitos de servicios de red en los distintos trozos, o slices de la red. Tras presentar OKpi, la tesis resuelve el problema del VNE en redes 5G con dispositivos fog estáticos y móviles. El algoritmo de orquestación NFV presentado tiene en cuenta las limitaciones de recursos de computo de los dispositivos fog, además de los problemas de falta de cobertura derivados de la movilidad de los dispositivos. Para concluir, esta tesis estudia el escalado de servicios vehiculares Vehicle-to-Network (V2N), que requieren de bajas latencias para servicios como la prevención de choques, avisos de posibles riesgos, y conducción remota. Para estos servicios, los atascos y congestiones en la carretera pueden causar el incumplimiento de los requisitos de latencia. Por tanto, es necesario anticiparse a esas circunstancias usando técnicas de series temporales que permiten saber el tráfico inminente en los siguientes minutos u horas, para así poder escalar el servicio V2N adecuadamente.Current network infrastructures handle a diverse range of network services such as video on demand services, video-conferences, social networks, educational systems, or photo storage services. These services have been embraced by a significant amount of the world population, and are used on a daily basis. Cloud providers and Network operators’ infrastructures accommodate the traffic rates that the aforementioned services generate, and their management tasks do not only involve the traffic steering, but also the processing of the network services’ traffic. Traditionally, the traffic processing has been assessed via applications/programs deployed on servers that were exclusively dedicated to a specific task as packet inspection. However, in recent years network services have stated to be virtualized and this has led to the Network Function Virtualization (Network Function Virtualization (NFV)) paradigm, in which the network functions of a service run on containers or virtual machines that are decoupled from the hardware infrastructure. As a result, the traffic processing has become more flexible because of the loose coupling between software and hardware, and the possibility of sharing common network functions, as firewalls, across multiple network services. NFV eases the automation of network operations, since scaling and migrations tasks are typically performed by a set of commands predefined by the virtualization technology, either containers or virtual machines. However, it is still necessary to decide the traffic steering and processing of every network service. In other words, which servers will hold the traffic processing, and which are the network links to be traversed so the users’ requests reach the final servers, i.e., the network embedding problem. Under the umbrella of NFV, this problem is known as Virtual Network Embedding (VNE), and this thesis refers as “NFV orchestration algorithms” to those algorithms solving such a problem. The VNE problem is a NP-hard, meaning that it is impossible to find optimal solutions in polynomial time, no matter the network size. As a consequence, the research and telecommunications community rely on heuristics that find solutions quicker than a commodity optimization solver. Traditionally, NFV orchestration algorithms have tried to minimize the deployment costs derived from their solutions. For example, they try to not exhaust the network bandwidth, and use short paths to use less network resources. Additionally, a recent tendency led the research community towards algorithms that minimize the energy consumption of the deployed services, either by selecting more energy efficient devices or by turning off those network devices that remained unused. VNE problem constraints were typically summarized in a set of resources/energy constraints, and the solutions differed on which objectives functions were aimed for. But that was before 5th generation of mobile networks (5G) were considered in the VNE problem. With the appearance of 5G, new network services and use cases started to emerge. The standards talked about Ultra Reliable Low Latency Communication (Ultra-Reliable and Low Latency Communications (URLLC)) with latencies below few milliseconds and 99.999% reliability, an enhanced mobile broadband (enhanced Mobile Broadband (eMBB)) with significant data rate increases, and even the consideration of massive machine-type communications (Massive Machine-Type Communications (mMTC)) among Internet of Things (IoT) devices. Moreover, paradigms such as edge and fog computing blended with the 5G technology to introduce the idea of having computing devices closer to the end users. As a result, the VNE problem had to incorporate the new requirements as constraints to be taken into account, and every solution should either satisfy low latencies, high reliability, or larger data rates. This thesis studies the VNE problem, and proposes some heuristics tackling the constraints related to 5G services in Edge and fog scenarios, that is, the proposed solutions assess the assignment of Virtual Network Functions to resources, and the traffic steering across 5G infrastructures that have Edge and Fog devices. To evaluate the performance of the proposed solutions, the thesis studies first the generation of graphs that represent 5G networks. The proposed mechanisms to generate graphs serve to represent diverse 5G scenarios. In particular federation scenarios in which several domains share resources among themselves. The generated graphs also represent edge servers, so as fog devices with limited battery capacity. Additionally, these graphs take into account the standard requirements, and the expected demand for 5G networks. Moreover, the graphs differ depending on the density of population, and the area of study, i.e., whether it is an industrial area, a highway, or an urban area. After detailing the generation of graphs representing the 5G networks, this thesis proposes several NFV orchestration algorithms to tackle the VNE problem. First, it focuses on federation scenarios in which network services should be assigned not only to a single domain infrastructure, but also to the shared resources of the federation of domains. Two different problems are studied, one being the VNE itself over a federated infrastructure, and the other the delegation of network services. That is, whether a network service should be deployed in a local domain, or in the pool of resources of the federation domain; knowing that the latter charges the local domain for hosting the network service. Second, the thesis proposes OKpi, a NFV orchestration algorithm to meet 5G network slices quality of service. Conceptually, network slicing consists in splitting the network so network services are treated differently based on the slice they belong to. For example, an eHealth network slice will allocate the network resources necessary to meet low latencies for network services such as remote surgery. Each network slice is devoted to specific services with very concrete requirements, as high reliability, location constraints, or 1ms latencies. OKpi is a NFV orchestration algorithm that meets the network service requirements among different slices. It is based on a multi-constrained shortest path heuristic, and its solutions satisfy latency, reliability, and location constraints. After presenting OKpi, the thesis tackles the VNE problem in 5G networks with static/moving fog devices. The presented NFV orchestration algorithm takes into account the limited computing resources of fog devices, as well as the out-of-coverage problems derived from the devices’ mobility. To conclude, this thesis studies the scaling of Vehicle-to-Network (V2N) services, which require low latencies for network services as collision avoidance, hazard warning, and remote driving. For these services, the presence of traffic jams, or high vehicular traffic congestion lead to the violation of latency requirements. Hence, it is necessary to anticipate to such circumstances by using time-series techniques that allow to derive the incoming vehicular traffic flow in the next minutes or hours, so as to scale the V2N service accordingly.The 5G Exchange (5GEx) project (2015-2018) was an EU-funded project (H2020-ICT-2014-2 grant agreement 671636). The 5G-TRANSFORMER project (2017-2019) is an EU-funded project (H2020-ICT-2016-2 grant agreement 761536). The 5G-CORAL project (2017-2019) is an EU-Taiwan project (H2020-ICT-2016-2 grant agreement 761586).Programa de Doctorado en Ingeniería Telemática por la Universidad Carlos III de MadridPresidente: Ioannis Stavrakakis.- Secretario: Pablo Serrano Yáñez-Mingot.- Vocal: Paul Horatiu Patra

Scale-Out Processors

Global-scale online services, such as Google’s Web search and Facebook’s social networking, run in large-scale datacenters. Due to their massive scale, these services are designed to scale out (or distribute) their respective loads and datasets across thousands of servers in datacenters. The growing demand for online services forced service providers to build networks of datacenters, which require an enormous capital outlay for infrastructure, hardware, and power consumption. Consequently, efficiency has become a major concern in the design and operation of such datacenters, with processor efficiency being of, utmost importance, due to the significant contribution of processors to the overall datacenter performance and cost. Scale-out workloads, which are behind today’s online services, serve independent requests, and have large instruction footprints and little data locality. As such, they benefit from processor designs that feature many cores and a modestly sized Last-Level Cache (LLC), a fast access path to the LLC, and high-bandwidth interfaces to memory. Existing server-class processors with large LLCs and a handful of aggressive out-of-order cores are inefficient in executing scale-out workloads. Moreover, the scaling trajectory for these processors leads to even lower efficiency in future technology nodes. This thesis presents a family of throughput-optimal processors, called Scale-Out Processors, for the efficient execution of scale-out workloads. A unique feature of Scale-Out Processors is that they consist of multiple stand-alone modules, called pods, wherein each module is a server running an operating system and a full software stack. To design a throughput-optimal processor, we developed a methodology based on performance density, defined as throughput per unit area, to quantify how effectively an architecture uses the silicon real estate. The proposed methodology derives a performance-density optimal processor building block (i.e., pod), which tightly couples a number of cores to a small LLC via a fast interconnect. Scale-Out Processors simply consist of multiple pods with no inter-pod connectivity or coherence. Moreover, they deliver the highest throughput in today’s technology and afford near-ideal scalability as process technology advances. We demonstrate that Scale-Out Processors improve datacenters’ efficiency by 4.4x-7.1x over datacenters designed using existing server-class processors

A framework for Traffic Engineering in software-defined networks with advance reservation capabilities

298 p.En esta tesis doctoral se presenta una arquitectura software para facilitar la introducción de técnicas de ingeniería de tráfico en redes definidas por software. La arquitectura ha sido diseñada de forma modular, de manera que soporte múltiples casos de uso, incluyendo su aplicación en redes académicas. Cabe destacar que las redes académicas se caracterizan por proporcionar servicios de alta disponibilidad, por lo que la utilización de técnicas de ingeniería de tráfico es de vital importancia a fin de garantizar la prestación del servicio en los términos acordados. Uno de los servicios típicamente prestados por las redes académicas es el establecimiento de circuitos extremo a extremo con una duración determinada en la que una serie de recursos de red estén garantizados, conocido como ancho de banda bajo demanda, el cual constituye uno de los casos de uso en ingeniería de tráfico más desafiantes. Como consecuencia, y dado que esta tesis doctoral ha sido co-financiada por la red académica GÉANT, la arquitectura incluye soporte para servicios de reserva avanzada. La solución consiste en una gestión de los recursos de red en función del tiempo, la cual mediante el empleo de estructuras de datos y algoritmos específicamente diseñados persigue la mejora de la utilización de los recursos de red a la hora de prestar este tipo de servicios. La solución ha sido validada teniendo en cuenta los requisitos funcionales y de rendimiento planteados por la red GÉANT. Así mismo, cabe destacar que la solución será utilizada en el despliegue piloto del nuevo servicio de ancho de banda bajo demanda de la red GÉANT a finales del 2017

RFID Technology in Intelligent Tracking Systems in Construction Waste Logistics Using Optimisation Techniques

Construction waste disposal is an urgent issue for protecting our environment. This paper proposes a waste management system and illustrates the work process using plasterboard waste as an example, which creates a hazardous gas when land filled with household waste, and for which the recycling rate is less than 10% in the UK. The proposed system integrates RFID technology, Rule-Based Reasoning, Ant Colony optimization and knowledge technology for auditing and tracking plasterboard waste, guiding the operation staff, arranging vehicles, schedule planning, and also provides evidence to verify its disposal. It h relies on RFID equipment for collecting logistical data and uses digital imaging equipment to give further evidence; the reasoning core in the third layer is responsible for generating schedules and route plans and guidance, and the last layer delivers the result to inform users. The paper firstly introduces the current plasterboard disposal situation and addresses the logistical problem that is now the main barrier to a higher recycling rate, followed by discussion of the proposed system in terms of both system level structure and process structure. And finally, an example scenario will be given to illustrate the system’s utilization