837 resultados para energy consumption
Resumo:
Nowadays, there is an increasing interest in wireless sensor networks (WSN) for environmental monitoring systems because it can be used to improve the quality of life and living conditions are becoming a major concern to people. This paper describes the design and development of a real time monitoring system based on ZigBee WSN characterized by a lower energy consumption, low cost, reduced dimensions and fast adaptation to the network tree topology. The developed system encompasses an optimized sensing process about environmental parameters, low rate transmission from sensor nodes to the gateway, packet parsing and data storing in a remote database and real time visualization through a web server.
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In the last years the attentions on the energy efficiency on historical buildings grows, as different research project took place across Europe. The attention on combining, the need of the preservation of the buildings, their value and their characteristic, with the need of the reduction of energy consumption and the improvements of indoor comfort condition, stimulate the discussion of two points of view that are usually in contradiction, buildings engineer and Conservation Institution. The results are surprising because a common field is growing while remains the need of balancing the respective exigencies. From these experience results clear that many questions should be answered also from the building physicist regarding the correct assessment: on the energy consumption of this class of buildings, on the effectiveness of the measures that could be adopted, and much more. This thesis gives a contribution to answer to these questions developing a procedure to analyse the historic building. The procedure gives a guideline of the energy audit for the historical building considering the experimental activities to dial with the uncertainty of the estimation of the energy balance. It offers a procedure to simulate the energy balance of building with a validated dynamic model considering also a calibration procedure to increase the accuracy of the model. An approach of design of energy efficiency measures through an optimization that consider different aspect is also presented. All the process is applied to a real case study to give to the reader a practical understanding.
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The energy harvesting research field has grown considerably in the last decade due to increasing interests in energy autonomous sensing systems, which require smart and efficient interfaces for extracting power from energy source and power management (PM) circuits. This thesis investigates the design trade-offs for minimizing the intrinsic power of PM circuits, in order to allow operation with very weak energy sources. For validation purposes, three different integrated power converter and PM circuits for energy harvesting applications are presented. They have been designed for nano-power operations and single-source converters can operate with input power lower than 1 μW. The first IC is a buck-boost converter for piezoelectric transducers (PZ) implementing Synchronous Electrical Charge Extraction (SECE), a non-linear energy extraction technique. Moreover, Residual Charge Inversion technique is exploited for extracting energy from PZ with weak and irregular excitations (i.e. lower voltage), and the implemented PM policy, named Two-Way Energy Storage, considerably reduces the start-up time of the converter, improving the overall conversion efficiency. The second proposed IC is a general-purpose buck-boost converter for low-voltage DC energy sources, up to 2.5 V. An ultra-low-power MPPT circuit has been designed in order to track variations of source power. Furthermore, a capacitive boost circuit has been included, allowing the converter start-up from a source voltage VDC0 = 223 mV. A nano-power programmable linear regulator is also included in order to provide a stable voltage to the load. The third IC implements an heterogeneous multisource buck-boost converter. It provides up to 9 independent input channels, of which 5 are specific for PZ (with SECE) and 4 for DC energy sources with MPPT. The inductor is shared among channels and an arbiter, designed with asynchronous logic to reduce the energy consumption, avoids simultaneous access to the buck-boost core, with a dynamic schedule based on source priority.
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This thesis focuses on the energy efficiency in wireless networks under the transmission and information diffusion points of view. In particular, on one hand, the communication efficiency is investigated, attempting to reduce the consumption during transmissions, while on the other hand the energy efficiency of the procedures required to distribute the information among wireless nodes in complex networks is taken into account. For what concerns energy efficient communications, an innovative transmission scheme reusing source of opportunity signals is introduced. This kind of signals has never been previously studied in literature for communication purposes. The scope is to provide a way for transmitting information with energy consumption close to zero. On the theoretical side, starting from a general communication channel model subject to a limited input amplitude, the theme of low power transmission signals is tackled under the perspective of stating sufficient conditions for the capacity achieving input distribution to be discrete. Finally, the focus is shifted towards the design of energy efficient algorithms for the diffusion of information. In particular, the endeavours are aimed at solving an estimation problem distributed over a wireless sensor network. The proposed solutions are deeply analyzed both to ensure their energy efficiency and to guarantee their robustness against losses during the diffusion of information (against information diffusion truncation more in general).
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This paper examines the accuracy of software-based on-line energy estimation techniques. It evaluates today’s most widespread energy estimation model in order to investigate whether the current methodology of pure software-based energy estimation running on a sensor node itself can indeed reliably and accurately determine its energy consumption - independent of the particular node instance, the traffic load the node is exposed to, or the MAC protocol the node is running. The paper enhances today’s widely used energy estimation model by integrating radio transceiver switches into the model, and proposes a methodology to find the optimal estimation model parameters. It proves by statistical validation with experimental data that the proposed model enhancement and parameter calibration methodology significantly increases the estimation accuracy.
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Investigation uses simulation to explore the inherent tradeoffs ofcontrolling high-speed and highly robust walking robots while minimizing energy consumption. Using a novel controller which optimizes robustness, energy economy, and speed of a simulated robot on rough terrain, the user can adjust their priorities between these three outcome measures and systematically generate a performance curveassessing the tradeoffs associated with these metrics.
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The increasing usage of wireless networks creates new challenges for wireless access providers. On the one hand, providers want to satisfy the user demands but on the other hand, they try to reduce the operational costs by decreasing the energy consumption. In this paper, we evaluate the trade-off between energy efficiency and quality of experience for a wireless mesh testbed. The results show that by intelligent service control, resources can be better utilized and energy can be saved by reducing the number of active network components. However, care has to be taken because the channel bandwidth varies in wireless networks. In the second part of the paper, we analyze the trade-off between energy efficiency and quality of experience at the end user. The results reveal that a provider's service control measures do not only reduce the operational costs of the network but also bring a second benefit: they help maximize the battery lifetime of the end-user device.
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The past decade has seen the energy consumption in servers and Internet Data Centers (IDCs) skyrocket. A recent survey estimated that the worldwide spending on servers and cooling have risen to above $30 billion and is likely to exceed spending on the new server hardware . The rapid rise in energy consumption has posted a serious threat to both energy resources and the environment, which makes green computing not only worthwhile but also necessary. This dissertation intends to tackle the challenges of both reducing the energy consumption of server systems and by reducing the cost for Online Service Providers (OSPs). Two distinct subsystems account for most of IDC’s power: the server system, which accounts for 56% of the total power consumption of an IDC, and the cooling and humidifcation systems, which accounts for about 30% of the total power consumption. The server system dominates the energy consumption of an IDC, and its power draw can vary drastically with data center utilization. In this dissertation, we propose three models to achieve energy effciency in web server clusters: an energy proportional model, an optimal server allocation and frequency adjustment strategy, and a constrained Markov model. The proposed models have combined Dynamic Voltage/Frequency Scaling (DV/FS) and Vary-On, Vary-off (VOVF) mechanisms that work together for more energy savings. Meanwhile, corresponding strategies are proposed to deal with the transition overheads. We further extend server energy management to the IDC’s costs management, helping the OSPs to conserve, manage their own electricity cost, and lower the carbon emissions. We have developed an optimal energy-aware load dispatching strategy that periodically maps more requests to the locations with lower electricity prices. A carbon emission limit is placed, and the volatility of the carbon offset market is also considered. Two energy effcient strategies are applied to the server system and the cooling system respectively. With the rapid development of cloud services, we also carry out research to reduce the server energy in cloud computing environments. In this work, we propose a new live virtual machine (VM) placement scheme that can effectively map VMs to Physical Machines (PMs) with substantial energy savings in a heterogeneous server cluster. A VM/PM mapping probability matrix is constructed, in which each VM request is assigned with a probability running on PMs. The VM/PM mapping probability matrix takes into account resource limitations, VM operation overheads, server reliability as well as energy effciency. The evolution of Internet Data Centers and the increasing demands of web services raise great challenges to improve the energy effciency of IDCs. We also express several potential areas for future research in each chapter.
Resumo:
Two of the indicators of the UN Millennium Development Goals ensuring environmental sustainability are energy use and per capita carbon dioxide emissions. The increasing urbanization and increasing world population may require increased energy use in order to transport enough safe drinking water to communities. In addition, the increase in water use would result in increased energy consumption, thereby resulting in increased green-house gas emissions that promote global climate change. The study of multiple Municipal Drinking Water Distribution Systems (MDWDSs) that relates various MDWDS aspects--system components and properties--to energy use is strongly desirable. The understanding of the relationship between system aspects and energy use aids in energy-efficient design. In this study, components of a MDWDS, and/or the characteristics associated with the component are termed as MDWDS aspects (hereafter--system aspects). There are many aspects of MDWDSs that affect the energy usage. Three system aspects (1) system-wide water demand, (2) storage tank parameters, and (3) pumping stations were analyzed in this study. The study involved seven MDWDSs to understand the relationship between the above-mentioned system aspects in relation with energy use. A MDWDSs model, EPANET 2.0, was utilized to analyze the seven systems. Six of the systems were real and one was a hypothetical system. The study presented here is unique in its statistical approach using seven municipal water distribution systems. The first system aspect studied was system-wide water demand. The analysis involved analyzing seven systems for the variation of water demand and its impact on energy use. To quantify the effects of water use reduction on energy use in a municipal water distribution system, the seven systems were modeled and the energy usage quantified for various amounts of water conservation. It was found that the effect of water conservation on energy use was linear for all seven systems and that all the average values of all the systems' energy use plotted on the same line with a high R 2 value. From this relationship, it can be ascertained that a 20% reduction in water demand results in approximately a 13% savings in energy use for all seven systems analyzed. This figure might hold true for many similar systems that are dominated by pumping and not gravity driven. The second system aspect analyzed was storage tank(s) parameters. Various tank parameters: (1) tank maximum water levels, (2) tank elevation, and (3) tank diameter were considered in this part of the study. MDWDSs use a significant amount of electrical energy for the pumping of water from low elevations (usually a source) to higher ones (usually storage tanks). The use of electrical energy has an effect on pollution emissions and, therefore, potential global climate change as well. Various values of these tank parameters were modeled on seven MDWDSs of various sizes using a network solver and the energy usage recorded. It was found that when averaged over all seven analyzed systems (1) the reduction of maximum tank water level by 50% results in a 2% energy reduction, (2) energy use for a change in tank elevation is system specific, and (2) a reduction of tank diameter of 50% results in approximately a 7% energy savings. The third system aspect analyzed in this study was pumping station parameters. A pumping station consists of one or more pumps. The seven systems were analyzed to understand the effect of the variation of pump horsepower and the number of booster stations on energy use. It was found that adding booster stations could save energy depending upon the system characteristics. For systems with flat topography, a single main pumping station was found to use less energy. In systems with a higher-elevation neighborhood, however, one or more booster pumps with a reduced main pumping station capacity used less energy. The energy savings for the seven systems was dependent on the number of boosters and ranged from 5% to 66% for the analyzed five systems with higher elevation neighborhoods (S3, S4, S5, S6, and S7). No energy savings was realized for the remaining two flat topography systems, S1, and S2. The present study analyzed and established the relationship between various system aspects and energy use in seven MDWDSs. This aids in estimating the amount of energy savings in MDWDSs. This energy savings would ultimately help reduce Greenhouse gases (GHGs) emissions including per capita CO 2 emissions thereby potentially lowering the global climate change effect. This will in turn contribute to meeting the MDG of ensuring environmental sustainability.
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In recent years, advanced metering infrastructure (AMI) has been the main research focus due to the traditional power grid has been restricted to meet development requirements. There has been an ongoing effort to increase the number of AMI devices that provide real-time data readings to improve system observability. Deployed AMI across distribution secondary networks provides load and consumption information for individual households which can improve grid management. Significant upgrade costs associated with retrofitting existing meters with network-capable sensing can be made more economical by using image processing methods to extract usage information from images of the existing meters. This thesis presents a new solution that uses online data exchange of power consumption information to a cloud server without modifying the existing electromechanical analog meters. In this framework, application of a systematic approach to extract energy data from images replaces the manual reading process. One case study illustrates the digital imaging approach is compared to the averages determined by visual readings over a one-month period.
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Basis for the economic efficiency of international supply chains rests on the efficiency of multimodal transport chains. Materials and products are transported along the edges of transport networks with the forwarder endeavouring to maximize the transport efficiency by using the effects of scale along the edges. The network nodes provide the means to have the goods transferred between the means of transport. Whilst purely economic criteria were initially the driving force for a change in the means of transport, ecological requirements are now becoming ever more relevant. The transportation chains should not only be economically presentable but also it makes sense for them to have a “green footprint”. In this context the following considerations will deal with the transfer processes within the network nodes, especially those within inland and feeder terminals. Replies are to be given to the questions as to how far the choice of the crane primary drive has an impact on energy consumption and environmental compatibility of handling the goods and which additional benefit does the recuperation of engrained energies bring during the handling process.
Resumo:
Over the past several years the topics of energy consumption and energy harvesting have gained significant importance as a means for improved operation of wireless sensor and mesh networks. Energy-awareness of operation is especially relevant for application scenarios from the domain of environmental monitoring in hard to access areas. In this work we reflect upon our experiences with a real-world deployment of a wireless mesh network. In particular, a comprehensive study on energy measurements collected over several weeks during the summer and the winter period in a network deployment in the Swiss Alps is presented. Energy performance is monitored and analysed for three system components, namely, mesh node, battery and solar panel module. Our findings cover a number of aspects of energy consumption, including the amount of load consumed by a mesh node, the amount of load harvested by a solar panel module, and the dependencies between these two. With our work we aim to shed some light on energy-aware network operation and to help both users and developers in the planning and deployment of a new wireless (mesh) network for environmental research.
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In this paper we address energy efficiency issues of Information Centric Networking (ICN) architectures. In the proposed framework, we investigate the impact of ICN architectures on energy consumption of networking hardware devices and compare them with the energy consumption of other content dissemination methods. In particular, we investigate the consequences of caching in ICN from the energy efficiency perspective, taking into account the energy consumption of different hardware components in the ICN architectures. Based on the results of the analysis, we address the practical issues regarding the possible deployment and evolution of ICN from an energy-efficiency perspective. Finally, we summarize our findings and discuss the outlook/future perspectives on the energy efficiency of Information-Centric Networks.
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This paper proposes the Optimized Power save Algorithm for continuous Media Applications (OPAMA) to improve end-user device energy efficiency. OPAMA enhances the standard legacy Power Save Mode (PSM) of IEEE 802.11 by taking into consideration application specific requirements combined with data aggregation techniques. By establishing a balanced cost/benefit tradeoff between performance and energy consumption, OPAMA is able to improve energy efficiency, while keeping the end-user experience at a desired level. OPAMA was assessed in the OMNeT++ simulator using real traces of variable bitrate video streaming applications. The results showed the capability to enhance energy efficiency, achieving savings up to 44% when compared with the IEEE 802.11 legacy PSM.
Resumo:
Various applications for the purposes of event detection, localization, and monitoring can benefit from the use of wireless sensor networks (WSNs). Wireless sensor networks are generally easy to deploy, with flexible topology and can support diversity of tasks thanks to the large variety of sensors that can be attached to the wireless sensor nodes. To guarantee the efficient operation of such a heterogeneous wireless sensor networks during its lifetime an appropriate management is necessary. Typically, there are three management tasks, namely monitoring, (re) configuration, and code updating. On the one hand, status information, such as battery state and node connectivity, of both the wireless sensor network and the sensor nodes has to be monitored. And on the other hand, sensor nodes have to be (re)configured, e.g., setting the sensing interval. Most importantly, new applications have to be deployed as well as bug fixes have to be applied during the network lifetime. All management tasks have to be performed in a reliable, time- and energy-efficient manner. The ability to disseminate data from one sender to multiple receivers in a reliable, time- and energy-efficient manner is critical for the execution of the management tasks, especially for code updating. Using multicast communication in wireless sensor networks is an efficient way to handle such traffic pattern. Due to the nature of code updates a multicast protocol has to support bulky traffic and endto-end reliability. Further, the limited resources of wireless sensor nodes demand an energy-efficient operation of the multicast protocol. Current data dissemination schemes do not fulfil all of the above requirements. In order to close the gap, we designed the Sensor Node Overlay Multicast (SNOMC) protocol such that to support a reliable, time-efficient and energy-efficient dissemination of data from one sender node to multiple receivers. In contrast to other multicast transport protocols, which do not support reliability mechanisms, SNOMC supports end-to-end reliability using a NACK-based reliability mechanism. The mechanism is simple and easy to implement and can significantly reduce the number of transmissions. It is complemented by a data acknowledgement after successful reception of all data fragments by the receiver nodes. In SNOMC three different caching strategies are integrated for an efficient handling of necessary retransmissions, namely, caching on each intermediate node, caching on branching nodes, or caching only on the sender node. Moreover, an option was included to pro-actively request missing fragments. SNOMC was evaluated both in the OMNeT++ simulator and in our in-house real-world testbed and compared to a number of common data dissemination protocols, such as Flooding, MPR, TinyCubus, PSFQ, and both UDP and TCP. The results showed that SNOMC outperforms the selected protocols in terms of transmission time, number of transmitted packets, and energy-consumption. Moreover, we showed that SNOMC performs well with different underlying MAC protocols, which support different levels of reliability and energy-efficiency. Thus, SNOMC can offer a robust, high-performing solution for the efficient distribution of code updates and management information in a wireless sensor network. To address the three management tasks, in this thesis we developed the Management Architecture for Wireless Sensor Networks (MARWIS). MARWIS is specifically designed for the management of heterogeneous wireless sensor networks. A distinguished feature of its design is the use of wireless mesh nodes as backbone, which enables diverse communication platforms and offloading functionality from the sensor nodes to the mesh nodes. This hierarchical architecture allows for efficient operation of the management tasks, due to the organisation of the sensor nodes into small sub-networks each managed by a mesh node. Furthermore, we developed a intuitive -based graphical user interface, which allows non-expert users to easily perform management tasks in the network. In contrast to other management frameworks, such as Mate, MANNA, TinyCubus, or code dissemination protocols, such as Impala, Trickle, and Deluge, MARWIS offers an integrated solution monitoring, configuration and code updating of sensor nodes. Integration of SNOMC into MARWIS further increases performance efficiency of the management tasks. To our knowledge, our approach is the first one, which offers a combination of a management architecture with an efficient overlay multicast transport protocol. This combination of SNOMC and MARWIS supports reliably, time- and energy-efficient operation of a heterogeneous wireless sensor network.