Medida del consumo de energía en la descodificación de vídeos

Este proyecto se encuentra adscrito a la línea de investigación de optimización de consumo en terminales multimedia móviles que el Grupo de Diseño Electrónico y Microelectrónico (GDEM) de la UPM (Universidad Politécnica de Madrid) está llevando a cabo. Los sistemas empotrados móviles (Smartphone, Tablet,...) están alimentados con baterías. En este tipo de sistemas, una de las aplicaciones que más rápidamente consume energía es la descodificación de secuencias de vídeo. En este trabajo, queremos medir el consumo de energía de distintos descodificadores de vídeo para distintas secuencias, con el objetivo de entender mejor cómo se consume esta energía y poder encontrar diferentes métodos que lo reduzcan. Para ello comenzaremos describiendo nuestro entorno de trabajo, tanto el hardware como el software utilizado. Respeto al hardware cabe destacar el uso de una PandaBoard y un Smart Power de Odroid, entre otros muchos elementos utilizados, los cuales serán debidamente explicados en las siguientes páginas de este proyecto. Mientras que para el software destaca el uso de dos tipos de descodificadores uno CBP y otro PHP, los cuales serán descritos en profundidad en los siguientes capítulos de este documento. Este entorno de trabajo nos servirá para el estudio de las diferentes secuencias de vídeo, cuya codificación ha sido llevada en paralelo con otro proyecto que se está realizando en el grupo de GDEM de la UPM, y cuyo objetivo es el estudio de la calidad subjetiva durante la descodificación del mismo conjunto de secuencias de vídeo. Todas estas secuencias de vídeo han sido codificadas con diferentes parámetros de calidad y diversas estructuras de imágenes, para obtener así un banco de pruebas lo más amplio posible. Gracias a la obtención de estas secuencias de vídeo y utilizando nuestro entorno de trabajo, pasaremos a estudiar el consumo de energía que se produce al descodificar una a una todas las posibles secuencias de vídeo, dependiendo todo esto de su estructura de imágenes, su calidad y por supuesto, el descodificador utilizado en cada caso. Para terminar, se mostrará una comparativa entre los diferentes resultados obtenidos y se hará una discusión de estos, obteniendo en este caso, un resumen de los datos más significativos, así como las conclusiones más importantes obtenidas durante todo este trabajo. Al término de este proyecto y en unión con el estudio que se está llevando a cabo en paralelo sobre la calidad subjetiva, queda como línea futura de investigación encontrar el compromiso entre el consumo de energía de diferentes secuencias de vídeo y la calidad subjetiva de dichas secuencias. ABSTRACT. This project is assigned to the research line on consumption optimization in mobile multimedia terminals carried out by the Group of Electronic Design and Microelectronics (GDEM) of the Polytechnic University of Madrid (UPM). Embedded mobile systems (smartphones, tablets...) are powered by batteries. In such systems, one of the applications that more rapidly consumes power is the decoding of video streams. In this work, we measure the power consumption of different video decoders for different streams, in order to better understand how this energy is consumed and to find different methods to reduce it. To this end, we start by describing our working environment, both hardware and software used. As for the hardware, it is worth mentioning the use of PandaBoard and Smart Power Odroid, among many other elements, which will be duly explained in the following pages of this project. As for the software, we highlight the use of two types of decoders, CBP and PHP, which will be described in detail in the following chapters of this document. This working environment will help us to study different video streams, whose coding has been perfor-med in parallel under another project that is being carried out in the GDEM group of the UPM, and whose objective is the study of subjective quality for decoding the same set of video streams. All these video streams have been encoded with different quality parameters and image structures in order to obtain the widest set of samples. Thanks to the production of these video streams and the use of our working environment, we study the power consumption that occurs when decoding one by one all possible video streams, depending on the image structure, their quality and, of course, the decoder used in each case. Finally, we show a comparison between the different results and a discussion of these, obtaining a sum-mary of the most significant data and the main conclusions obtained during this project. Upon completion of this project and in conjunction with the project on the study of subjective quality that is being carried out in parallel, a future line of research could consist in finding the compromise between power consumption of different video streams and the subjective quality of these.

Meter data management for smart monitoring power networks

The electrical power distribution and commercialization scenario is evolving worldwide, and electricity companies, faced with the challenge of new information requirements, are demanding IT solutions to deal with the smart monitoring of power networks. Two main challenges arise from data management and smart monitoring of power networks: real-time data acquisition and big data processing over short time periods. We present a solution in the form of a system architecture that conveys real time issues and has the capacity for big data management.

Smart meter privacy by suprression of low power frequency components

This paper focuses on the problems associated with privacy protection in smart grid. We will give an overview of a possible realization of a privacy-preserving approach that encompasses privacy-utility tradeoff into a single model. This approach proposes suppression of low power frequency components as a solution to reduce the amount of information leakage from smart meter readings. We will consider the applicability of the procedure to hide the appliance usage with respect to the type of home devices.

Ubiquitous green computing techniques for high demand applications in smart environments

Ubiquitous sensor network deployments, such as the ones found in Smart cities and Ambient intelligence applications, require constantly increasing high computational demands in order to process data and offer services to users. The nature of these applications imply the usage of data centers. Research has paid much attention to the energy consumption of the sensor nodes in WSNs infrastructures. However, supercomputing facilities are the ones presenting a higher economic and environmental impact due to their very high power consumption. The latter problem, however, has been disregarded in the field of smart environment services. This paper proposes an energy-minimization workload assignment technique, based on heterogeneity and application-awareness, that redistributes low-demand computational tasks from high-performance facilities to idle nodes with low and medium resources in the WSN infrastructure. These non-optimal allocation policies reduce the energy consumed by the whole infrastructure and the total execution time.

Power management techniques in an FPGA-Based WSN node for high performance application

In this work, the power management techniques implemented in a high-performance node for Wireless Sensor Networks (WSN) based on a RAM-based FPGA are presented. This new node custom architecture is intended for high-end WSN applications that include complex sensor management like video cameras, high compute demanding tasks such as image encoding or robust encryption, and/or higher data bandwidth needs. In the case of these complex processing tasks, yet maintaining low power design requirements, it can be shown that the combination of different techniques such as extensive HW algorithm mapping, smart management of power islands to selectively switch on and off components, smart and low-energy partial reconfiguration, an adequate set of save energy modes and wake up options, all combined, may yield energy results that may compete and improve energy usage of typical low power microcontrollers used in many WSN node architectures. Actually, results show that higher complexity tasks are in favor of HW based platforms, while the flexibility achieved by dynamic and partial reconfiguration techniques could be comparable to SW based solutions.

Middleware architectures for the Smart Grid : survey and challenges in the foreseeable future

The traditional power grid is just a one-way supplier that gets no feedback data about the energy delivered, what tariffs could be the most suitable ones for customers, the shifting daily needs of electricity in a facility, etc. Therefore, it is only natural that efforts are being invested in improving power grid behavior and turning it into a Smart Grid. However, to this end, several components have to be either upgraded or created from scratch. Among the new components required, middleware appears as a critical one, for it will abstract all the diversity of the used devices for power transmission (smart meters, embedded systems, etc.) and will provide the application layer with a homogeneous interface involving power production and consumption management data that were not able to be provided before. Additionally, middleware is expected to guarantee that updates to the current metering infrastructure (changes in service or hardware availability) or any added legacy measuring appliance will get acknowledged for any future request. Finally, semantic features are of major importance to tackle scalability and interoperability issues. A survey on the most prominent middleware architectures for Smart Grids is presented in this paper, along with an evaluation of their features and their strong points and weaknesses.

Large-Scale smart grids as system of systems

Smart Grids are advanced power networks that introduce intelligent management, control, and operation systems to address the new challenges generated by the growing energy demand and the appearance of renewal energies. In the literature, Smart Grids are presented as an exemplar SoS: systems composed of large heterogeneous and independent systems that leverage emergent behavior from their interaction. Smart Grids are currently scaling up the electricity service to millions of customers. These Smart Grids are known as Large-Scale Smart Grids. From the experience in several projects about Large-Scale Smart Grids, this paper defines Large-Scale Smart Grids as a SoS that integrate a set of SoS and conceptualizes the properties of this SoS. In addition, the paper defines the architectural framework for deploying the software architectures of Large-Scale Smart Grid SoS.

Designing and simulating smart grids

Growing energy demands and the increased use of renewal energies have changed the landscape of power networks leading to new challenges. Smart Grids have emerged to cope with these challenges by facilitating the integration of traditional and renewable energy resources in distributed, open, and self-managed ways. Innovative models are needed to design energy infrastructures that can enable self-management of the power grid. Software architectures smoothly integrate the software that provides self-management to Smart Grids and their hardware infrastructures. We present a framework to design the software architectures of autonomous Smart Grids in an intuitive domain-oriented way and to simulate their execution by automatically generating the code from the designed autonomous smart grid architectures.

A semantic middleware architecture focused on data and heterogeneity management within the Smart Grid

There is an increasing tendency of turning the current power grid, essentially unaware of variations in electricity demand and scattered energy sources, into something capable of bringing a degree of intelligence by using tools strongly related to information and communication technologies, thus turning into the so-called Smart Grid. In fact, it could be considered that the Smart Grid is an extensive smart system that spreads throughout any area where power is required, providing a significant optimization in energy generation, storage and consumption. However, the information that must be treated to accomplish these tasks is challenging both in terms of complexity (semantic features, distributed systems, suitable hardware) and quantity (consumption data, generation data, forecasting functionalities, service reporting), since the different energy beneficiaries are prone to be heterogeneous, as the nature of their own activities is. This paper presents a proposal on how to deal with these issues by using a semantic middleware architecture that integrates different components focused on specific tasks, and how it is used to handle information at every level and satisfy end user requests.

Evaluación del dispositivo Raspberry Pi como elemento de despliegue de servicios en el marco de las Smart Grids

La tendencia actual de las redes de telecomunicaciones conduce a pensar en un futuro basado en el concepto emergente de las Smart Cities¸ que tienen como objetivo el desarrollo urbano basado en un modelo de sostenibilidad que responda a las necesidades crecientes de las ciudades. Dentro de las Smart Cities podemos incluir el concepto de Smart Grid, el cual está referido a sistemas de administración y producción de energía eficientes, que permitan un sistema energético sostenible, y que den cabida a las fuentes de energía renovables. Sistemas de este tipo se muestran a los usuarios como un conjunto de servicios con los que interactuar sin ser tan sólo un mero cliente, sino un agente más del entorno energético. Por otro lado, los sistemas de software distribuidos son cada vez más comunes en una infraestructura de telecomunicaciones cada vez más extensa y con más capacidades. Dentro de este ámbito tecnológico, las arquitecturas orientadas a servicios han crecido exponencialmente sobre todo en el sector empresarial. Con sistemas basados en estas arquitecturas, se pueden ofrecer a empresas y usuarios sistemas software basados en el concepto de servicio. Con la progresión del hardware actual, la miniaturización de los equipos es cada vez mayor, sin renunciar por ello a la potencia que podemos encontrar en sistemas de mayor tamaño. Un ejemplo es el dispositivo Raspberry Pi, que contiene un ordenador plenamente funcional contenido en el tamaño de una cajetilla de tabaco, y con un coste muy reducido. En este proyecto se pretenden aunar los tres conceptos expuestos. De esta forma, se busca utilizar el dispositivo Raspberry Pi como elemento de despliegue integrado en una arquitectura de Smart Grid orientada a servicios. En los trabajos realizados se ha utilizado la propuesta definida por el proyecto de I+D europeo e-GOTHAM, con cuya infraestructura se ha tenido ocasión de realizar diferentes pruebas de las descritas en esta memoria. Aunque esta arquitectura está orientada a la creación de una Smart Grid, lo experimentado en este PFG podría encajar en otro tipo de aplicaciones. Dentro del estudio sobre las soluciones software actuales, se ha trabajado en la evaluación de la posibilidad de instalar un Enterprise Service Bus en el Raspberry Pi y en la optimización de la citada instalación. Una vez conseguida una instalación operativa, se ha desarrollado un controlador de un dispositivo físico (sensor/actuador), denominado Dispositivo Lógico, a modo de prueba de la viabilidad del uso del Raspberry Pi para actuar como elemento en el que instalar aplicaciones en entornos de Smart Grid o Smart Home. El éxito logrado con esta experimentación refuerza la idea de considerar al Raspberry Pi, como un importante elemento a tener en cuenta para el despliegue de servicios de Smart Cities o incluso en otros ámbitos tecnológicos. ABSTRACT. The current trend of telecommunication networks lead to think in a future based on the emerging concept of Smart Cities, whose objective is to ensure the urban development based on a sustainable model to respond the new necessities of the cities. Within the Smart cites we can include the concept of Smart Grid, which is based on management systems and efficient energy production, allowing a sustainable energy producing system, and that includes renewable energy sources. Systems of this type are shown to users as a set of services that allow users to interact with the system not only as a single customer, but also as other energy environment agent. Furthermore, distributed software systems are increasingly common in a telecommunications infrastructure more extensive and with more capabilities. Within this area of technology, service-oriented architectures have grown exponentially especially in the business sector. With systems based on these architectures, can be offered to businesses and users software systems based on the concept of service. With the progression of the actual hardware, the miniaturization of computers is increasing, without sacrificing the power of larger systems. An example is the Raspberry Pi, which contains a fully functional computer contained in the size of a pack of cigarettes, and with a very low cost. This PFG (Proyecto Fin de Grado) tries to combine the three concepts presented. Thus, it is intended to use the Raspberry Pi device as a deployment element integrated into a service oriented Smart Grid architecture. In this PFG, the one proposed in the European R&D e-GOTHAM project has been observed. In addition several tests described herein have been carried out using the infrastructure of that project. Although this architecture is oriented to the creation of a Smart Grid, the experiences reported in this document could fit into other applications. Within the study on current software solutions, it have been working on assessing the possibility of installing an Enterprise Service Bus in the Raspberry Pi and optimizing that facility. Having achieved an operating installation, it has been developed a driver for a physical device (sensor / actuator), called logical device, for testing the feasibility of using the Raspberry Pi to act as an element in which to install applications in Smart Grid and Smart Home Environments. The success of this experiment reinforces the idea of considering the Raspberry Pi as an important element to take into account in the deployment of Smart Cities services or even in other technological fields.

Business models in the Smart Grid: challenges, opportunities and proposals for prosumer profitability.

Considering that non-renewable energy resources are dwindling, the smart grid turns out to be one of the most promising and compelling systems for the future of energy. Not only does it combine efficient energy consumption with avant-garde technologies related to renewable energies, but it is also capable of providing several beneficial utilities, such as power monitoring and data provision. When smart grid end users turn into prosumers, they become arguably the most important value creators within the smart grid and a decisive agent of change in terms of electricity usage. There is a plethora of research and development areas related to the smart grid that can be exploited for new business opportunities, thus spawning another branch of the so-called ?green economy? focused on turning smart energy usage into a profitable business. This paper deals with emerging business models for smart grid prosumers, their strengths and weaknesses and puts forward new prosumer-oriented business models, along with their value propositions.

Building an ontology catalogue for smart cities

Apart from providing semantics and reasoning power to data, ontologies enable and facilitate interoperability across heterogeneous systems or environments. A good practice when developing ontologies is to reuse as much knowledge as possible in order to increase interoperability by reducing heterogeneity across models and to reduce development effort. Ontology registries, indexes and catalogues facilitate the task of finding, exploring and reusing ontologies by collecting them from different sources. This paper presents an ontology catalogue for the smart cities and related domains. This catalogue is based on curated metadata and incorporates ontology evaluation features. Such catalogue represents the first approach within this community and it would be highly useful for new ontology developments or for describing and annotating existing ontologies.

Distribution of microservices for hardware interoperability in the Smart Grid

Due to the significant increase of population and their natural desire of improving their standard of living, usage of energy extracted from world commodities, especially shaped as electricity, has increased in an intense manner during the last decades. This fact brings up a challenge with a complicated solution, which is how to guarantee that there will be enough energy so as to satisfy the energy demand of the world population. Among all the possible solutions that can be adopted to mitigate this problem one of them is almost of mandatory adoption, which consists of rationalizing energy utilization, in a way that its wasteful usage is minimized and it can be leveraged during a longer period of time. One of the ways to achieve it is by means of the improvement of the power distribution grid, so that it will be able to react in a more efficient manner against common issues, such as energy demand peaks or inaccurate electricity consumption forecasts. However, in order to be able to implement this improvement it is necessary to use technologies from the ICT (Information and Communication Technologies) sphere that often present challenges in some key areas: advanced metering infrastructure integration, interoperability and interconnectivity of the devices, interfaces to offer the applications, security measures design, etc. All these challenges may imply slowing down the adoption of the smart grid as a system to prolong the lifespan and utilization of the available energy. A proposal for an intermediation architecture that will make possible solving these challenges is put forward in this Master Thesis. Besides, one implementation and the tests that have been carried out to know the performance of the presented concepts have been included as well, in a way that it can be proved that the challenges set out by the smart grid can be resolved. RESUMEN. Debido al incremento significativo de la población y su deseo natural de mejorar su nivel de vida, la utilización de la energía extraída de las materias primas mundiales, especialmente en forma de electricidad, ha aumentado de manera intensa durante las últimas décadas. Este hecho plantea un reto de solución complicada, el cual es cómo garantizar que se dispondrá de la energía suficiente como para satisfacer la demanda energética de la población mundial. De entre todas las soluciones posibles que se pueden adoptar para mitigar este problema una de ellas es de casi obligatoria adopción, la cual consiste en racionalizar la utilización de la energía, de tal forma que se minimice su malgasto y pueda aprovecharse durante más tiempo. Una de las maneras de conseguirlo es mediante la mejora de la red de distribución de electricidad para que ésta pueda reaccionar de manera más eficaz contra problemas comunes, tales como los picos de demanda de energía o previsiones imprecisas acerca del consumo de electricidad. Sin embargo, para poder implementar esta mejora es necesario utilizar tecnologías del ámbito de las TIC (Tecnologías de la Información y la Comunicación) que a menudo presentan problemas en algunas áreas clave: integración de infraestructura de medición avanzada, interoperabilidad e interconectividad de los dispositivos, interfaces que ofrecer a las aplicaciones, diseño de medidas de seguridad, etc. Todos estos retos pueden implicar una ralentización en la adopción de la red eléctrica inteligente como un sistema para alargar la vida y la utilización de la energía disponible. En este Trabajo Fin de Máster se sugiere una propuesta para una arquitectura de intermediación que posibilite la resolución de estos retos. Además, una implementación y las pruebas que se han llevado a cabo para conocer el rendimiento de los conceptos presentados también han sido incluidas, de tal forma que se demuestre que los retos que plantea la red eléctrica inteligente pueden ser solventados.