Adaptation-Aware Architecture Modeling and Analysis of Energy Efficiency for Software Systems

This thesis presents an approach for the design time analysis of energy efficiency for static and self-adaptive software systems. The quality characteristics of a software system, such as performance and operating costs, strongly depend upon its architecture. Software architecture is a high-level view on software artifacts that reflects essential quality characteristics of a system under design. Design decisions made on an architectural level have a decisive impact on the quality of a system. Revising architectural design decisions late into development requires significant effort. Architectural analyses allow software architects to reason about the impact of design decisions on quality, based on an architectural description of the system. An essential quality goal is the reduction of cost while maintaining other quality goals. Power consumption accounts for a significant part of the Total Cost of Ownership (TCO) of data centers. In 2010, data centers contributed 1.3% of the world-wide power consumption. However, reasoning on the energy efficiency of software systems is excluded from the systematic analysis of software architectures at design time. Energy efficiency can only be evaluated once the system is deployed and operational. One approach to reduce power consumption or cost is the introduction of self-adaptivity to a software system. Self-adaptive software systems execute adaptations to provision costly resources dependent on user load. The execution of reconfigurations can increase energy efficiency and reduce cost. If performed improperly, however, the additional resources required to execute a reconfiguration may exceed their positive effect. Existing architecture-level energy analysis approaches offer limited accuracy or only consider a limited set of system features, e.g., the used communication style. Predictive approaches from the embedded systems and Cloud Computing domain operate on an abstraction that is not suited for architectural analysis. The execution of adaptations can consume additional resources. The additional consumption can reduce performance and energy efficiency. Design time quality analyses for self-adaptive software systems ignore this transient effect of adaptations. This thesis makes the following contributions to enable the systematic consideration of energy efficiency in the architectural design of self-adaptive software systems: First, it presents a modeling language that captures power consumption characteristics on an architectural abstraction level. Second, it introduces an energy efficiency analysis approach that uses instances of our power consumption modeling language in combination with existing performance analyses for architecture models. The developed analysis supports reasoning on energy efficiency for static and self-adaptive software systems. Third, to ease the specification of power consumption characteristics, we provide a method for extracting power models for server environments. The method encompasses an automated profiling of servers based on a set of restrictions defined by the user. A model training framework extracts a set of power models specified in our modeling language from the resulting profile. The method ranks the trained power models based on their predicted accuracy. Lastly, this thesis introduces a systematic modeling and analysis approach for considering transient effects in design time quality analyses. The approach explicitly models inter-dependencies between reconfigurations, performance and power consumption. We provide a formalization of the execution semantics of the model. Additionally, we discuss how our approach can be integrated with existing quality analyses of self-adaptive software systems. We validated the accuracy, applicability, and appropriateness of our approach in a variety of case studies. The first two case studies investigated the accuracy and appropriateness of our modeling and analysis approach. The first study evaluated the impact of design decisions on the energy efficiency of a media hosting application. The energy consumption predictions achieved an absolute error lower than 5.5% across different user loads. Our approach predicted the relative impact of the design decision on energy efficiency with an error of less than 18.94%. The second case study used two variants of the Spring-based community case study system PetClinic. The case study complements the accuracy and appropriateness evaluation of our modeling and analysis approach. We were able to predict the energy consumption of both variants with an absolute error of no more than 2.38%. In contrast to the first case study, we derived all models automatically, using our power model extraction framework, as well as an extraction framework for performance models. The third case study applied our model-based prediction to evaluate the effect of different self-adaptation algorithms on energy efficiency. It involved scientific workloads executed in a virtualized environment. Our approach predicted the energy consumption with an error below 7.1%, even though we used coarse grained measurement data of low accuracy to train the input models. The fourth case study evaluated the appropriateness and accuracy of the automated model extraction method using a set of Big Data and enterprise workloads. Our method produced power models with prediction errors below 5.9%. A secondary study evaluated the accuracy of extracted power models for different Virtual Machine (VM) migration scenarios. The results of the fifth case study showed that our approach for modeling transient effects improved the prediction accuracy for a horizontally scaling application. Leveraging the improved accuracy, we were able to identify design deficiencies of the application that otherwise would have remained unnoticed

A framework for modelling embodied product energy to support energy efficient manufacturing

This thesis reports on the research undertaken to minimise energy consumption within the production phase of a product lifecycle through modelling, monitoring and improved control of energy use within manufacturing facilities. The principle objective of this research is to develop a framework which integrates energy data at plant and process levels within a manufacturing system so as to establish how much energy is required to manufacture a unit product. The research contributions are divided into four major parts. The first reviews relevant literature in energy trends, related governmental policies, and energy tools and software. The second introduces an Embodied Product Energy framework which categorises energy consumption within a production facility into direct and indirect energy required to manufacture a product. The third describes the design and implementation of a simulation model based on this framework to support manufacturing and design decisions for improved energy efficiency through the use of what-if scenario planning. The final part outlines the utilisation of this energy simulation model to support a Design for Energy Minimisation methodology which incorporates energy considerations within the design process. The applicability of the research concepts have been demonstrated via two case studies. The detailed analysis of energy consumption from a product viewpoint provides greater insight into inefficiencies of processes and associated supporting activities, thereby highlighting opportunities for optimisation of energy consumption via operational or design improvements. Although the research domain for this thesis is limited to the production phase, the flexibility offered by the energy modelling framework and associated simulation tool allow for their employment other product lifecycle phases. In summary, the research has concluded that investment in green sources of power generation alone is insufficient to deal with the rapid rise in energy demand, and has highlighted the paramount importance of energy rationalisation and optimisation within the manufacturing industry

Energy refurbishment planning of Italian school buildings using data-driven predictive models

In the current practice, the design of energy refurbishment interventions for existing buildings is typically addressed by performing time-consuming software-based numerical simulations. However, this approach may be not suitable for preliminary assessment studies, especially when large building portfolios are involved. Therefore, this research work aims at developing simplified data-driven predictive models to estimate the energy consumption of existing school buildings in Italy and support the decision-making process in energy refurbishment intervention planning at a large scale. To accomplish this, an extensive database is assembled through comprehensive on-site surveys of school buildings in Southern Italy. For each school, a Building Information Modelling (BIM) model is developed and validated considering real energy consumption data. These BIM models serve in the design of suitable energy refurbishment interventions. Moreover, a comprehensive parametric investigation based on refined energy analyses is carried out to significantly improve and integrate the dataset. To derive the predictive models, firstly the most relevant parameters for energy consumption are identified by performing sensitivity analyses. Based on these findings, predictive models are generated through a multiple linear regression method. The suggested models provide an estimation of the energy consumption of the “as-built” configuration, as well as the costs and benefits of alternative energy refurbishment scenarios. The reliability of the proposed simplified relationships is substantiated through a statistical analysis of the main error indices. Results highlight that the building's shape factor (i.e., the ratio between the building's envelope area and its volume) and the area-weighted average of the thermal properties of the building envelope significantly affect both the energy consumption of school buildings and the achievable savings through retrofitting interventions. Finally, a framework for the preliminary design of energy refurbishment of buildings, based on the implementation of the herein developed predictive model, is proposed and illustrated through a worked example application. Worth noting that, while the proposed approach is currently limited to school buildings, the methodology can conceptually be extended to any building typology, provided that suitable data on energy consumption are available

A framework for modelling embodied product energy to support energy efficient manufacturing

This thesis reports on the research undertaken to minimise energy consumption within the production phase of a product lifecycle through modelling, monitoring and improved control of energy use within manufacturing facilities. The principle objective of this research is to develop a framework which integrates energy data at plant and process levels within a manufacturing system so as to establish how much energy is required to manufacture a unit product. The research contributions are divided into four major parts. The first reviews relevant literature in energy trends, related governmental policies, and energy tools and software. The second introduces an Embodied Product Energy framework which categorises energy consumption within a production facility into direct and indirect energy required to manufacture a product. The third describes the design and implementation of a simulation model based on this framework to support manufacturing and design decisions for improved energy efficiency through the use of what-if scenario planning. The final part outlines the utilisation of this energy simulation model to support a Design for Energy Minimisation methodology which incorporates energy considerations within the design process. The applicability of the research concepts have been demonstrated via two case studies. The detailed analysis of energy consumption from a product viewpoint provides greater insight into inefficiencies of processes and associated supporting activities, thereby highlighting opportunities for optimisation of energy consumption via operational or design improvements. Although the research domain for this thesis is limited to the production phase, the flexibility offered by the energy modelling framework and associated simulation tool allow for their employment other product lifecycle phases. In summary, the research has concluded that investment in green sources of power generation alone is insufficient to deal with the rapid rise in energy demand, and has highlighted the paramount importance of energy rationalisation and optimisation within the manufacturing industry.EThOS - Electronic Theses Online ServiceGBUnited Kingdo

Wind Flow Simulation over Fish Farm Feed Barge

Master's thesis in Mechanical engineeringThere are approximate over 1000 fish farms in Norway, where half are connected to the grid and the rest are driven by diesel generators. Fish farms use large air compressors to feed the fish, which creates high power consumption. To reduce the diesel consumption and C02 emissions, created by the compressors, there are companies that specialize in providing green energy solutions. Gwind is a Stavanger based energy company that provide off-grid energy for this exact purpose. A master study done by H. Syse showed that a hybrid system with wind turbines, PV, Li-Ion batteries and two diesel generators over a 20-year period would reduce the CO2 emissions and lower the diesel consumption. Investigation of local wind flow and power generation with a wind turbine linked to the fish farm feed barge, was performed using the open source computational fluid dynamics (CFD) software OpenFOAM. The wind turbine is a vertical axis wind turbine (VAWT), modeled by an actuator line model (ALM). The ALM has been implemented with the use of a library called turbinesFoam. A framework for wind flow simulations over fish farm feed barges has been developed. This framework includes a ALM of a VAWT, simulated with OpenFOAM’s pimpleFoam solver, and k-epsilon turbulence model. The inlet is enriched with atmospheric boundary layer. The framework has been used on two fish farm cases, Tallaksholmen and Nordheim. These are owned by Grieg Seafood Rogaland, and in collaboration with Gwind a wind measurement campaign was conducted, and cross-referenced with nearby wind stations to set an approximately real inflow condition. The framework was used to investigate the optimal height placement of the VAWT on Tallaksholmen, coupled with a cost benefit analysis. To show the flexibility of the framework the second fish farm case, Nordheim, was setup and ready to run within a few hours. In this case the performance was increased, as a result of investigating the local wind flow before activating the turbine. Based on the results of this study, it is recommended to install a VAWT on the Tallaksholmen fish farm feed barge. The operational performance should be compared against the simulations to further verify the computational approach

Development of an Integrated Process, Modeling and Simulation Platform for Performance-Based Design of Low-Energy and High IEQ Buildings

The objective of this study was to develop a Virtual Design Studio (VDS) : a software platform for integrated, coordinated and optimized design of green building systems with low energy consumption, high indoor environmental quality (IEQ), and high level of sustainability. The VDS is intended to assist collaborating architects, engineers and project management team members throughout from the early phases to the detailed building design stages. It can be used to plan design tasks and workflow, and evaluate the potential impacts of various green building strategies on the building performance by using the state of the art simulation tools as well as industrial/professional standards and guidelines for green building system design. Based on the review and analysis of existing professional practices in building system design, particularly those used in U.S., Germany and UK, a generic process for performance-based building design, construction and operation was proposed. It included Assess, Define, Design, Apply, and Monitoring (ADDAM) stages. The current VDS focused on the first three stages. The VDS considers the building design as a multi-dimensional process involving multiple design teams, design factors, and design stages. The intersection among these three dimensions defines a specific design task in terms of who , what and when . It also considers building design as a multi-objective process that aims to enhance the five aspects of performance for green building systems: site sustainability, materials and resource efficiency, water utilization efficiency, energy efficiency and impacts to the atmospheric environment, and IEQ. The current VDS development has been limited to the energy efficiency and IEQ performance with particular focus on thermal, air quality and lighting environmental quality because of their strong interaction with the energy performance of buildings. The VDS software framework contains four major functions: 1) Design coordination: It enables users to define tasks using the Input-Process-Output flow approach, which specifies the anticipated activities (i.e., the process), required input and output information, and anticipated interactions with other tasks. It also allows task scheduling to define the work flow, and sharing of the design data and information via internet. 2) Modeling and simulation: It enables users to perform building simulations to predict the energy consumption and IEQ conditions at any of the design stages by using EnergyPlus and a combined heat, air, moisture and pollutant simulation (CHAMPS) model. A method for co-simulation was developed to allow the use of both models at the same time step for the combined energy and indoor air quality analysis. 3) Results visualization: It enables users to display a 3-D geometric design of the building by reading BIM (building information model) file generated by design software such as SketchUp, and the predicted results of heat, air, moisture, pollutant and light distributions in the building. 4) Performance evaluation: It enables the users to compare the performance of a proposed building design against a reference building that is defined for the same type of buildings under the same climate condition, and predict the percent of improvements over the minimum requirements specified in ASHRAE Standard 55-2010, 62.1-2010 and 90.1-2010. An approach was developed to estimate the potential impact of a design factor on the whole building performance, and hence can assist the user to identify areas that have most pay back for investment. The VDS software was developed by using C++ with the conventional Model, View and Control (MVC) software architecture. The software has been verified by using a simple 3-zone case building. The application of the VDS concepts and framework for building design and performance analysis has been illustrated by using a medium size five story office building that received the LEED Platinum Certification from USGBC

Abordagem de Anotações para o Suporte da Gestão Energética de Software em Modelos AMALTHEA

The automotive industry is continuously introducing innovative software features to provide more efficient, safe, and comfortable solutions. Despite the several benefits to the consumer, the evolution of automotive software is also reflected in several challenges, presenting a growing complexity that hinders its development and integration. The adoption of standards and appropriate development methods becomes essential to meet the requirements of the industry. Furthermore, the expansion of automotive software systems is also driving a considerable growth in the number of electronic components installed in a vehicle, which has a significant impact on the electric energy consumption. Thus, the focus on non-functional energy requirements has become increasingly important. This work presents a study focused on the evolution of automotive software considering the development standards, methodologies, as well as approaches for energy requirements management. We propose an automatic and self-contained approach for the support of energy properties management, adopting the model-based open-source framework AMALTHEA. From the analysis of execution or simulation traces, the energy consumption estimation is provided at a fine-grained level and annotated in AMALTHEA models. Thus, we enable the energy analysis and management of the system throughout the entire lifecycle. Additionally, this solution is in line with the AUTOSAR Adaptive standard, allowing the development of energy management strategies for automatic, dynamic, and adaptive systems.A indústria automotiva encontra-se constantemente a introduzir funcionalidades inovadoras através de software, para oferecer soluções mais eficientes, seguras e confortáveis. Apesar dos diversos benefícios para o consumidor, a evolução do software automóvel também se reflete em diversos desafios, apresentando uma crescente complexidade que dificulta o seu desenvolvimento e integração. Desta forma, a adoção de normas e metodologias adequadas para o seu desenvolvimento torna-se essencial para cumprir os requisitos do setor. Adicionalmente, esta expansão das funcionalidades suportadas por software é fonte de um aumento considerável do número de componentes eletrónicos instalados em automóveis. Consequentemente, existe um impacto significativo no consumo de energia elétrica dos sistemas automóveis, sendo cada vez mais relevante o foco nos requisitos não-funcionais deste domínio. Este trabalho apresenta um estudo focado na evolução do software automotivo tendo em conta os padrões e metodologias de desenvolvimento desta área, bem como abordagens para a gestão de requisitos de energia. Através da adoção da ferramenta AMALTHEA, uma plataforma open-source de desenvolvimento baseado em modelos, é proposta uma abordagem automática e independente para a análise de propriedades energéticas. A partir da análise de traços de execução ou de simulação, é produzida uma estimativa pormenorizada do consumo de energia, sendo esta anotada em modelos AMALTHEA. Desta forma, torna-se possível a análise e gestão energética ao longo de todo o ciclo de vida do sistema. Salienta-se que a solução se encontra alinhada com a norma AUTOSAR Adaptive, permitindo o desenvolvimento de estratégias para a gestão energética de sistemas automáticos, dinâmicos e adaptativos

Decentralised electricity generation through rooftop solar photovoltaics (PVs) in Zambia : a case study of the engineering institute of Zambia (EIZ) office building project, Lusaka

A research report submitted to the Faculty of Engineering and the Built Environment at the University of the Witwatersrand, in partial fulfillment of the requirements for the degree of Master of Architecture (Sustainable and Energy Efficient Cities) Johannesburg, May 2018.Whereas there has been significant study and development of national strategic plans on electricity generation from renewable energy in general in Zambia, specific studies and research on decentralised electricity generation via rooftop solar PVs from buildings and their potential to enhance Zambia’s electricity generation goals have not systematically been done. The study applies a case study of the Engineering Institute of Zambia office building that is at construction stage but is determined to incorporate a rooftop solar PV system. Using DesignBuilder and Energyplus simulation software, the building was modelled and analysed for this potential. In addition, based on interview data from various experts and secondary data from national plans, the study evaluated policy, regulatory and market frameworks which could catalyse the increased deployment of such systems in Zambia. Using financial analysis tools of payback period, return on investment and net present value the study undertook a number of business case scenarios in order to conceptualize a responsive business model. The study finds that from the initial estimate, the available roof space had the capacity to net out the baseline annual electricity consumption of 287,707kWh and generate a surplus of 63,519kWh/year before optimisation. Optimisation of the baseline consumption through a combination of two viable energy efficiency interventions reduced the baseline annual consumption by 35% to 186,904kWh with related payback period of nine years, ROI of 518% over a 25 year analysis period and a NPV of 623,344.00 ZMK. Based on these findings, three business case scenarios for the solar PV system were analysed and two out of the three were adopted. One scenario assumed a net-zero building and another one assumed that the surplus electricity generated on non-business days is exported to the grid were adopted. Following this finding, a business model centred on an integrated energy service company (IESCo) was identified as the most appropriate model to respond to the uptake barriers of this technology and thus leverage on the emerging progressive support mechanisms. The overall findings of the study thus support the working hypothesis of the study which deemed that through the framework of a responsive business model, decentralised electricity generation through rooftop solar PV can greatly enhance energy security and mitigate GHG-emission for Zambia.MT 201

Modeling the Environmental Impact of Sustainability Policies in the Construction Industry Using Agent Based Simulation and Life Cycle Analysis

The construction industry, with its long supply chain and long lifetime of projects, is blamed to be one of the main contributors to environmental concerns including accelerated resource consumption and harmful emissions. Industry stakeholders, including developers, designers, contractors and suppliers, are, therefore, continuing to explore different options to reduce this impact. Various approaches have been adopted in different countries with building rating systems like the Leadership in Energy & Environmental Design (LEED) certification program being the most common way reflecting stakeholders’ efforts to go green. Governments and concerned authorities at national and state levels are expected to foster the trend of sustainable construction by motivating these stakeholders and pursuing policies that would help the green momentum. However, decision makers at such governmental and state levels face a challenge of prioritizing the policies and regulations that should be imposed. The objective of this paper is to present the development of a framework of an Agent Based Model (ABM) that simulates the effect of different possible policies in the construction market using Life Cycle Analysis (LCA), which is to be used by decision makers to assess and prioritize different policies or combination of policies. The framework was developed using Anylogic software and a sample construction market from the state of Qatar was used as an example for implementing the proposed framework. Results of running the model on this sample market illustrate the effectiveness of using this ABM as a support tool for decision makers in the area of sustainable construction

Analysis, characterization and optimization of the energy efficiency on softwarized mobile platforms

Mención Internacional en el título de doctorLa inminente 5ª generación de sistemas móviles (5G) está a punto de revolucionar la industria, trayendo una nueva arquitectura orientada a los nuevos mercados verticales y servicios. Debido a esto, el 5G Infrastructure Public Private Partnership (5G-PPP) ha especificado una lista de Indicadores de Rendimiento Clave (KPI) que todo sistema 5G tiene que soportar, por ejemplo incrementar por 1000 el volumen de datos, de 10 a 100 veces m´as dispositivos conectados o consumos energéticos 10 veces inferiores. Con el fin de conseguir estos requisitos, se espera expandir los despligues actuales usando mas Puntos de Acceso (PoA) incrementando así su densidad con múltiples tecnologías inalámbricas. Esta estrategia de despliegue masivo tiene una contrapartida en la eficiencia energética, generando un conflicto con el KPI de reducir por 10 el consumo energético. En este contexto, la comunidad investigadora ha propuesto nuevos paradigmas para alcanzar los requisitos impuestos para los sistemas 5G, siendo materializados en tecnologías como Redes Definidas por Software (SDN) y Virtualización de Funciones de Red (NFV). Estos nuevos paradigmas son el primer paso hacia la softwarización de los despliegues móviles, incorporando nuevos grados de flexibilidad y reconfigurabilidad de la Red de Acceso Radio (RAN). En esta tesis, presentamos primero un análisis detallado y caracterización de las redes móviles softwarizadas. Consideramos el software como la base de la nueva generación de redes celulares y, por lo tanto, analizaremos y caracterizaremos el impacto en la eficiencia energética de estos sistemas. La primera meta de este trabajo es caracterizar las plataformas software disponibles para Radios Definidas por Software (SDR), centrándonos en las dos soluciones principales de código abierto: OpenAirInterface (OAI) y srsLTE. Como resultado, proveemos una metodología para analizar y caracterizar el rendimiento de estas soluciones en función del uso de la CPU, rendimiento de red, compatibilidad y extensibilidad de dicho software. Una vez hemos entendido qué rendimiento podemos esperar de este tipo de soluciones, estudiamos un prototipo SDR construido con aceleración hardware, que emplea una plataformas basada en FPGA. Este prototipo está diseñado para incluir capacidad de ser consciente de la energía, permiento al sistema ser reconfigurado para minimizar la huella energética cuando sea posible. Con el fin de validar el diseño de nuestro sistema, más tarde presentamos una plataforma para caracterizar la energía que será empleada para medir experimentalmente el consumo energético de dispositivos reales. En nuestro enfoque, realizamos dos tipos de análisis: a pequeña escala de tiempo y a gran escala de tiempo. Por lo tanto, para validar nuestro entorno de medidas, caracterizamos a través de análisis numérico los algoritmos para la Adaptación de la Tasa (RA) en IEEE 802.11, para entonces comparar nuestros resultados teóricos con los experimentales. A continuación extendemos nuestro análisis a la plataforma SDR acelerada por hardware previamente mencionada. Nuestros resultados experimentales muestran que nuestra sistema puede en efecto reducir la huella energética reconfigurando el despligue del sistema. Entonces, la escala de tiempos es elevada y presentamos los esquemas para Recursos bajo Demanda (RoD) en despliegues de red ultra-densos. Esta estrategia está basada en apagar/encender dinámicamente los elementos que forman la red con el fin de reducir el total del consumo energético. Por lo tanto, presentamos un modelo analítico en dos sabores, un modelo exacto que predice el comportamiento del sistema con precisión pero con un alto coste computacional y uno simplificado que es más ligero en complejidad mientras que mantiene la precisión. Nuestros resultados muestran que estos esquemas pueden efectivamente mejorar la eficiencia energética de los despliegues y mantener la Calidad de Servicio (QoS). Con el fin de probar la plausibilidad de los esquemas RoD, presentamos un plataforma softwarizada que sigue el paradigma SDN, OFTEN (OpenFlow framework for Traffic Engineering in mobile Network with energy awareness). Nuestro diseño está basado en OpenFlow con funcionalidades para hacerlo consciente de la energía. Finalmente, un prototipo real con esta plataforma es presentando, probando así la plausibilidad de los RoD en despligues reales.The upcoming 5th Generation of mobile systems (5G) is about to revolutionize the industry, bringing a new architecture oriented to new vertical markets and services. Due to this, the 5G-PPP has specified a list of Key Performance Indicator (KPI) that 5G systems need to support e.g. increasing the 1000 times higher data volume, 10 to 100 times more connected devices or 10 times lower power consumption. In order to achieve these requirements, it is expected to expand the current deployments using more Points of Attachment (PoA) by increasing their density and by using multiple wireless technologies. This massive deployment strategy triggers a side effect in the energy efficiency though, generating a conflict with the “10 times lower power consumption” KPI. In this context, the research community has proposed novel paradigms to achieve the imposed requirements for 5G systems, being materialized in technologies such as Software Defined Networking (SDN) and Network Function Virtualization (NFV). These new paradigms are the first step to softwarize the mobile network deployments, enabling new degrees of flexibility and reconfigurability of the Radio Access Network (RAN). In this thesis, we first present a detailed analysis and characterization of softwarized mobile networking. We consider software as a basis for the next generation of cellular networks and hence, we analyze and characterize the impact on the energy efficiency of these systems. The first goal of this work is to characterize the available software platforms for Software Defined Radio (SDR), focusing on the two main open source solutions: OAI and srsLTE. As result, we provide a methodology to analyze and characterize the performance of these solutions in terms of CPU usage, network performance, compatibility and extensibility of the software. Once we have understood the expected performance for such platformsc, we study an SDR prototype built with hardware acceleration, that employs a FPGA based platform. This prototype is designed to include energy-awareness capabilites, allowing the system to be reconfigured to minimize the energy footprint when possible. In order to validate our system design, we later present an energy characterization platform that we will employ to experimentally measure the energy consumption of real devices. In our approach, we perform two kind of analysis: at short time scale and large time scale. Thus, to validate our approach in short time scale and the energy framework, we have characterized though numerical analysis the Rate Adaptation (RA) algorithms in IEEE 802.11, and then compare our theoretical results to the obtained ones through experimentation. Next we extend our analysis to the hardware accelerated SDR prototype previously mentioned. Our experimental results show that our system can indeed reduce the energy footprint reconfiguring the system deployment. Then, the time scale of our analysis is elevated and we present Resource-on-Demand (RoD) schemes for ultradense network deployments. This strategy is based on dynamically switch on/off the elements that form the network to reduce the overall energy consumption. Hence, we present a analytic model in two flavors, an exact model that accurately predicts the system behaviour but high computational cost and a simplified one that is lighter in complexity while keeping the accuracy. Our results show that these schemes can effectively enhance the energy efficiency of the deployments and mantaining the Quality of Service (QoS). In order to prove the feasibility of RoD, we present a softwarized platform that follows the SDN paradigm, the OFTEN (Open Flow framework for Traffic Engineering in mobile Networks with energy awareness) framework. Our design is based on OpenFlow with energy-awareness functionalities. Finally, a real prototype of this framework is presented, proving the feasibility of the RoD in real deployments.FP7-CROWD (2013-2015) CROWD (Connectivity management for eneRgy Optimised Wireless Dense networks).-- H2020-Flex5GWare (2015-2017) Flex5GWare (Flexible and efficient hardware/software platforms for 5G network elements and devices).Programa de Doctorado en Ingeniería Telemática por la Universidad Carlos III de MadridPresidente: Gramaglia , Marco.- Secretario: José Nuñez.- Vocal: Fabrizio Giulian