Increasing underwater vehicle autonomy by reducing energy consumption

In this paper, we concern ourselves with finding a control strategy that minimizes energy consumption along a trajectory connecting two given configurations. We develop an algorithm, based on our previous work with the time optimal problem, which provides implementable control strategies that are energy efficient. We find an interesting correlation between the duration of these trajectories and the optimal duration. We present the algorithm, control strategy and experimental results from our test-bed vehicle.

Reducing energy consumption of vehicle air conditioning system by an energy management system

This paper presents an energy management system to reduce the energy consumption of a vehicle when its air conditioning system is in use. The system controls the mass flow rate of the air by dynamically adjusting the blower speed and air-gates opening under various heat and loads circumstances. Simulations were conducted for a travelling vehicle operating the air conditioning system without and with the developed energy management system. The results show that the comfort temperature within the cabin room is achieved for reduced amount of energy consumption.

A game theory based strategy for reducing energy consumption in cognitive WSN

Wireless sensor networks (WSNs) are one of the most important users of wireless communication technologies in the coming years and some challenges in this area must be addressed for their complete development. Energy consumption and spectrum availability are two of the most severe constraints of WSNs due to their intrinsic nature. The introduction of cognitive capabilities into these networks has arisen to face the issue of spectrum scarcity but could be used to face energy challenges too due to their new range of communication possibilities. In this paper a new strategy based on game theory for cognitive WSNs is discussed. The presented strategy improves energy consumption by taking advantage of the new change-communication-channel capability. Based on game theory, the strategy decides when to change the transmission channel depending on the behavior of the rest of the network nodes. The strategy presented is lightweight but still has higher energy saving rates as compared to noncognitive networks and even to other strategies based on scheduled spectrum sensing. Simulations are presented for several scenarios that demonstrate energy saving rates of around 65% as compared to WSNs without cognitive techniques.

Cognitive strategies for reducing energy consumption in wireless sensor networks

El consumo energético de las Redes de Sensores Inalámbricas (WSNs por sus siglas en inglés) es un problema histórico que ha sido abordado desde diferentes niveles y visiones, ya que no solo afecta a la propia supervivencia de la red sino que el creciente uso de dispositivos inteligentes y el nuevo paradigma del Internet de las Cosas hace que las WSNs tengan cada vez una mayor influencia en la huella energética. Debido a la tendencia al alza en el uso de estas redes se añade un nuevo problema, la saturación espectral. Las WSNs operan habitualmente en bandas sin licencia como son las bandas Industrial, Científica y Médica (ISM por sus siglas en inglés). Estas bandas se comparten con otro tipo de redes como Wi-Fi o Bluetooth cuyo uso ha crecido exponencialmente en los últimos años. Para abordar este problema aparece el paradigma de la Radio Cognitiva (CR), una tecnología que permite el acceso oportunista al espectro. La introducción de capacidades cognitivas en las WSNs no solo permite optimizar su eficiencia espectral sino que también tiene un impacto positivo en parámetros como la calidad de servicio, la seguridad o el consumo energético. Sin embargo, por otra parte, este nuevo paradigma plantea algunos retos relacionados con el consumo energético. Concretamente, el sensado del espectro, la colaboración entre los nodos (que requiere comunicación adicional) y el cambio en los parámetros de transmisión aumentan el consumo respecto a las WSN clásicas. Teniendo en cuenta que la investigación en el campo del consumo energético ha sido ampliamente abordada puesto que se trata de una de sus principales limitaciones, asumimos que las nuevas estrategias deben surgir de las nuevas capacidades añadidas por las redes cognitivas. Por otro lado, a la hora de diseñar estrategias de optimización para CWSN hay que tener muy presentes las limitaciones de recursos de estas redes en cuanto a memoria, computación y consumo energético de los nodos. En esta tesis doctoral proponemos dos estrategias de reducción de consumo energético en CWSNs basadas en tres pilares fundamentales. El primero son las capacidades cognitivas añadidas a las WSNs que proporcionan la posibilidad de adaptar los parámetros de transmisión en función del espectro disponible. La segunda es la colaboración, como característica intrínseca de las CWSNs. Finalmente, el tercer pilar de este trabajo es teoría de juegos como algoritmo de soporte a la decisión, ampliamente utilizado en WSNs debido a su simplicidad. Como primer aporte de la tesis se presenta un análisis completo de las posibilidades introducidas por la radio cognitiva en materia de reducción de consumo para WSNs. Gracias a las conclusiones extraídas de este análisis, se han planteado las hipótesis de esta tesis relacionadas con la validez de usar capacidades cognitivas como herramienta para la reducción de consumo en CWSNs. Una vez presentada las hipótesis, pasamos a desarrollar las principales contribuciones de la tesis: las dos estrategias diseñadas para reducción de consumo basadas en teoría de juegos y CR. La primera de ellas hace uso de un juego no cooperativo que se juega mediante pares de jugadores. En la segunda estrategia, aunque el juego continúa siendo no cooperativo, se añade el concepto de colaboración. Para cada una de las estrategias se presenta el modelo del juego, el análisis formal de equilibrios y óptimos y la descripción de la estrategia completa donde se incluye la interacción entre nodos. Con el propósito de probar las estrategias mediante simulación e implementación en dispositivos reales hemos desarrollado un marco de pruebas compuesto por un simulador cognitivo y un banco de pruebas formado por nodos cognitivos capaces de comunicarse en tres bandas ISM desarrollados en el B105 Lab. Este marco de pruebas constituye otra de las aportaciones de la tesis que permitirá el avance en la investigación en el área de las CWSNs. Finalmente, se presentan y discuten los resultados derivados de la prueba de las estrategias desarrolladas. La primera estrategia proporciona ahorros de energía mayores al 65% comparados con una WSN sin capacidades cognitivas y alrededor del 25% si la comparamos con una estrategia cognitiva basada en el sensado periódico del espectro para el cambio de canal de acuerdo a un nivel de ruido fijado. Este algoritmo se comporta de forma similar independientemente del nivel de ruido siempre que éste sea espacialmente uniformemente. Esta estrategia, a pesar de su sencillez, nos asegura el comportamiento óptimo en cuanto a consumo energético debido a la utilización de teoría de juegos en la fase de diseño del comportamiento de los nodos. La estrategia colaborativa presenta mejoras respecto a la anterior en términos de protección frente al ruido en escenarios de ruido más complejos donde aporta una mejora del 50% comparada con la estrategia anterior. ABSTRACT Energy consumption in Wireless Sensor Networks (WSNs) is a known historical problem that has been addressed from different areas and on many levels. But this problem should not only be approached from the point of view of their own efficiency for survival. A major portion of communication traffic has migrated to mobile networks and systems. The increased use of smart devices and the introduction of the Internet of Things (IoT) give WSNs a great influence on the carbon footprint. Thus, optimizing the energy consumption of wireless networks could reduce their environmental impact considerably. In recent years, another problem has been added to the equation: spectrum saturation. Wireless Sensor Networks usually operate in unlicensed spectrum bands such as Industrial, Scientific, and Medical (ISM) bands shared with other networks (mainly Wi-Fi and Bluetooth). To address the efficient spectrum utilization problem, Cognitive Radio (CR) has emerged as the key technology that enables opportunistic access to the spectrum. Therefore, the introduction of cognitive capabilities to WSNs allows optimizing their spectral occupation. Cognitive Wireless Sensor Networks (CWSNs) do not only increase the reliability of communications, but they also have a positive impact on parameters such as the Quality of Service (QoS), network security, or energy consumption. These new opportunities introduced by CWSNs unveil a wide field in the energy consumption research area. However, this also implies some challenges. Specifically, the spectrum sensing stage, collaboration among devices (which requires extra communication), and changes in the transmission parameters increase the total energy consumption of the network. When designing CWSN optimization strategies, the fact that WSN nodes are very limited in terms of memory, computational power, or energy consumption has to be considered. Thus, light strategies that require a low computing capacity must be found. Since the field of energy conservation in WSNs has been widely explored, we assume that new strategies could emerge from the new opportunities presented by cognitive networks. In this PhD Thesis, we present two strategies for energy consumption reduction in CWSNs supported by three main pillars. The first pillar is that cognitive capabilities added to the WSN provide the ability to change the transmission parameters according to the spectrum. The second pillar is that the ability to collaborate is a basic characteristic of CWSNs. Finally, the third pillar for this work is the game theory as a decision-making algorithm, which has been widely used in WSNs due to its lightness and simplicity that make it valid to operate in CWSNs. For the development of these strategies, a complete analysis of the possibilities is first carried out by incorporating the cognitive abilities into the network. Once this analysis has been performed, we expose the hypotheses of this thesis related to the use of cognitive capabilities as a useful tool to reduce energy consumption in CWSNs. Once the analyses are exposed, we present the main contribution of this thesis: the two designed strategies for energy consumption reduction based on game theory and cognitive capabilities. The first one is based on a non-cooperative game played between two players in a simple and selfish way. In the second strategy, the concept of collaboration is introduced. Despite the fact that the game used is also a non-cooperative game, the decisions are taken through collaboration. For each strategy, we present the modeled game, the formal analysis of equilibrium and optimum, and the complete strategy describing the interaction between nodes. In order to test the strategies through simulation and implementation in real devices, we have developed a CWSN framework composed by a CWSN simulator based on Castalia and a testbed based on CWSN nodes able to communicate in three different ISM bands. We present and discuss the results derived by the energy optimization strategies. The first strategy brings energy improvement rates of over 65% compared to WSN without cognitive techniques. It also brings energy improvement rates of over 25% compared with sensing strategies for changing channels based on a decision threshold. We have also seen that the algorithm behaves similarly even with significant variations in the level of noise while working in a uniform noise scenario. The collaborative strategy presents improvements respecting the previous strategy in terms of noise protection when the noise scheme is more complex where this strategy shows improvement rates of over 50%.

Staff report on measures for reducing energy consumption for homeowners and renters.

Prepared in cooperation with the Edison Electric Institute and marketing staff of various utilities throughout the country.

Economics and forecast of energy consumption in NGN networks: the case of Spain

Reducing energy consumption is one of the main goals of sustainability planning in most countries. For instance in Europe, the EC established the objectives in the Communication “20 20 by 2020 Europe's climate change opportunity”.

On the economics of energy consumption in 4G networks: the case of Spain

Reducing energy consumption is one of the main challenges in most countries. For example, European Member States agreed to reduce greenhouse gas (GHG) emissions by 20% in 2020 compared to 1990 levels (EC 2008). Considering each sector separately, ICTs account nowadays for 2% of total carbon emissions. This percentage will increase as the demand of communication services and applications steps up. At the same time, the expected evolution of ICT-based developments - smart buildings, smart grids and smart transportation systems among others - could result in the creation of energy-saving opportunities leading to global emission reductions (Labouze et al. 2008), although the amount of these savings is under debate (Falch 2010). The main development required in telecommunication networks ?one of the three major blocks of energy consumption in ICTs together with data centers and consumer equipment (Sutherland 2009) ? is the evolution of existing infrastructures into ultra-broadband networks, the so-called Next Generation Networks (NGN). Fourth generation (4G) mobile communications are the technology of choice to complete -or supplement- the ubiquitous deployment of NGN. The risk and opportunities involved in NGN roll-out are currently in the forefront of the economic and policy debate. However, the issue of which is the role of energy consumption in 4G networks seems absent, despite the fact that the economic impact of energy consumption arises as a key element in the cost analysis of this type of networks. Precisely, the aim of this research is to provide deeper insight on the energy consumption involved in the usage of a 4G network, its relationship with network main design features, and the general economic impact this would have in the capital and operational expenditures related with network deployment and usage.

Energy Consumption Forecast in 4G Networks: The Case of Spain

Reducing energy consumption is one of the main goals of sustainability planning in most countries. For instance in Europe, the EC established the objectives in the Communication “20 20 by 2020 Europe's climate change opportunity”. • Next Generation Networks (NGN)  One of the most relevant upcoming ICT development • The role of energy consumption seems mostly absent from the main analysis and the debate on NGN deployment.

Cooking in the ungra area: Fuel efficiency, energy losses, and opportunities for reducing firewood consumption

Cooking efficiency and related fuel economy issues have been studied in a particular rural area of India. Following a description of the cooking practices and conditions in this locale, cooking efficiency is examined. A cooking efficiency of only 6% was found. The use of aluminium rather than clay pots results in an increased efficiency. In addition, cooking efficiency correlates very well with specific fuel consumption. The latter parameter is much simpler to analyse than cooking efficiency. The energy losses during cooking are examined in the second part of this case study. The major energy losses are heating of excess air, heat carried away by the combustion products, heat transmitted to the stove body and floor, and the chemical energy in charcoal residue. The energy loss due to the evaporation of cooking water is also significant because it represents about one-third of the heat reaching the pots.

Reducing Cache Hierarchy Energy Consumption by Predicting Forwarding and Disabling Associative Sets

The first level data cache un modern processors has become a major consumer of energy due to its increasing size and high frequency access rate. In order to reduce this high energy con sumption, we propose in this paper a straightforward filtering technique based on a highly accurate forwarding predictor. Specifically, a simple structure predicts whether a load instruction will obtain its corresponding data via forwarding from the load-store structure -thus avoiding the data cache access - or if it will be provided by the data cache. This mechanism manages to reduce the data cache energy consumption by an average of 21.5% with a negligible performance penalty of less than 0.1%. Furthermore, in this paper we focus on the cache static energy consumption too by disabling a portin of sets of the L2 associative cache. Overall, when merging both proposals, the combined L1 and L2 total energy consumption is reduced by an average of 29.2% with a performance penalty of just 0.25%. Keywords: Energy consumption; filtering; forwarding predictor; cache hierarchy

Energy consumption feedback in perspective: integrating Australian data to meta-analyses on in home displays

Providing homeowners with real-time feedback on their electricity consumption through a dedicated display device has been shown to reduce consumption by approximately 6-10%. However, recent advances in smart grid technology have enabled larger sample sizes and more representative sample selection and recruitment methods for display trials. By analyzing these factors using data from current studies, this paper argues that a realistic, large-scale conservation effect from feedback is in the range of 3-5%. Subsequent analysis shows that providing real-time feedback may not be a cost effective strategy for reducing carbon emissions in Australia, but that it may enable additional benefits such as customer retention and peak-load shift.

The energy consumption - real GDP nexus revisited : empirical evidence from 93 countries

In this paper, we analyse the long-run relationship between energy consumption and real GDP for 93 countries. We find mixed results on the impact of energy consumption on real GDP, with greater evidence at the country level supporting energy consumption having a negative causal effect on real GDP. For the G6 panel of countries, we find significant evidence that energy consumption negatively Granger causes real GDP. This means that for countries where energy consumption has a negative long-run causal effect on real GDP, energy conversation policies should not retard economic growth. We identify these countries and regional panels. We argue that these countries/regions should play a greater role in reducing carbon dioxide emissions.

Advances in understanding energy consumption behavior and the governance of its change - Outline of an integrated framework

Transforming today’s energy systems in industrialized countries requires a substantial reduction of the total energy consumption at the individual level. Selected instruments have been found to be effective in changing people’s behavior in single domains. However, the so far weak success story on reducing overall energy consumption indicates that our understanding of the determining factors of individual energy consumption as well as of its change is far from being conclusive. Among others, the scientific state of the art is dominated by analyzing single domains of consumption and by neglecting embodied energy. It also displays strong disciplinary splits and the literature often fails to distinguish between explaining behavior and explaining change of behavior. Moreover, there are knowledge gaps regarding the legitimacy and effectiveness of the governance of individual consumption behavior and its change. Against this backdrop, the aim of this paper is to establish an integrated interdisciplinary framework that offers a systematic basis for linking the different aspects in research on energy related consumption behavior, thus paving the way for establishing a better evidence base to inform societal actions. The framework connects the three relevant analytical aspects of the topic in question: (1) It systematically and conceptually frames the objects, i.e. the energy consumption behavior and its change (explananda); (2) it structures the factors that potentially explain the energy consumption behavior and its change (explanantia); (3) it provides a differentiated understanding of change inducing interventions in terms of governance. Based on the existing states of the art approaches from different disciplines within the social sciences the proposed framework is supposed to guide interdisciplinary empirical research.

Link between energy consumption per hour of activity and productivity of labour

The data set shows energy consumption per hour of work (in MJ/hour), and labour productivity (in USD/hour) in the PS economic sector (Energy & Mining + Industry + Construction) for the period 1970-2009 and for the following countries: Germany, Spain, USA, Canada, Italy, UK, France, Japan. The intention is to look at the relationship between energy consumption as a driver of improvements in the productivity of labour. This is of particular relevance for the discussion of reducing working time in the context of the 'degrowth' debate, as it is done in the article to which this data is a suplement.