954 resultados para Power consumption
DESIGN AND IMPLEMENT DYNAMIC PROGRAMMING BASED DISCRETE POWER LEVEL SMART HOME SCHEDULING USING FPGA
Resumo:
With the development and capabilities of the Smart Home system, people today are entering an era in which household appliances are no longer just controlled by people, but also operated by a Smart System. This results in a more efficient, convenient, comfortable, and environmentally friendly living environment. A critical part of the Smart Home system is Home Automation, which means that there is a Micro-Controller Unit (MCU) to control all the household appliances and schedule their operating times. This reduces electricity bills by shifting amounts of power consumption from the on-peak hour consumption to the off-peak hour consumption, in terms of different “hour price”. In this paper, we propose an algorithm for scheduling multi-user power consumption and implement it on an FPGA board, using it as the MCU. This algorithm for discrete power level tasks scheduling is based on dynamic programming, which could find a scheduling solution close to the optimal one. We chose FPGA as our system’s controller because FPGA has low complexity, parallel processing capability, a large amount of I/O interface for further development and is programmable on both software and hardware. In conclusion, it costs little time running on FPGA board and the solution obtained is good enough for the consumers.
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In this paper, we propose an intelligent method, named the Novelty Detection Power Meter (NodePM), to detect novelties in electronic equipment monitored by a smart grid. Considering the entropy of each device monitored, which is calculated based on a Markov chain model, the proposed method identifies novelties through a machine learning algorithm. To this end, the NodePM is integrated into a platform for the remote monitoring of energy consumption, which consists of a wireless sensors network (WSN). It thus should be stressed that the experiments were conducted in real environments different from many related works, which are evaluated in simulated environments. In this sense, the results show that the NodePM reduces by 13.7% the power consumption of the equipment we monitored. In addition, the NodePM provides better efficiency to detect novelties when compared to an approach from the literature, surpassing it in different scenarios in all evaluations that were carried out.
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Many context-aware applications rely on the knowledge of the position of the user and the surrounding objects to provide advanced, personalized and real-time services. In wide-area deployments, a routing protocol is needed to collect the location information from distant nodes. In this paper, we propose a new source-initiated (on demand) routing protocol for location-aware applications in IEEE 802.15.4 wireless sensor networks. This protocol uses a low power MAC layer to maximize the lifetime of the network while maintaining the communication delay to a low value. Its performance is assessed through experimental tests that show a good trade-off between power consumption and time delay in the localization of a mobile device.
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In this paper the capabilities of ultra low power FPGAs to implement Wake-up Radios (WuR) for ultra low energy Wireless Sensor Networks (WSNs) are analyzed. The main goal is to evaluate the utilization of very low power configurable devices to take advantage of their speed, flexibility and low power consumption instead of the more common approaches based on ASICs or microcontrollers. In this context, energy efficiency is a key aspect, considering that usually the instant power consumption is considered a figure of merit, more than the total energy consumed by the application.
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In this paper an implementation of a Wake up Radio(WuR) with addressing capabilities based on an ultra low power FPGA for ultra low energy Wireless Sensor Networks (WSNs) is proposed. The main goal is to evaluate the utilization of very low power configurable devices to take advantage of their speed, flexibility and low power consumption instead of the traditional approaches based on ASICs or microcontrollers, for communication frame decoding and communication data control.
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This paper presents a low-power, high-speed 4-data-path 128-point mixed-radix (radix-2 & radix-2 2 ) FFT processor for MB-OFDM Ultra-WideBand (UWB) systems. The processor employs the single-path delay feedback (SDF) pipelined structure for the proposed algorithm, it uses substructure-sharing multiplication units and shift-add structure other than traditional complex multipliers. Furthermore, the word lengths are properly chosen, thus the hardware costs and power consumption of the proposed FFT processor are efficiently reduced. The proposed FFT processor is verified and synthesized by using 0.13 µm CMOS technology with a supply voltage of 1.32 V. The implementation results indicate that the proposed 128-point mixed-radix FFT architecture supports a throughput rate of 1Gsample/s with lower power consumption in comparison to existing 128-point FFT architectures
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In this work a novel wake-up architecture for wireless sensor nodes based on ultra low power FPGA is presented. A simple wake up messaging mechanism for data gathering applications is proposed. The main goal of this work is to evaluate the utilization of low power configurable devices to take advantage of their speed, flexibility and low power consumption compared with traditional approaches, based on ASICs or microcontrollers, for frame decoding and data control. A test bed based on infrared communications has been built to validate the messaging mechanism and the processing architecture.
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Power supply unpredictable uctuations jeopardize the functioning of several types of current electronic systems. This work presents a power supply sensor based on a voltage divider followed by buffer-comparator cells employing just MOSFET transistors and provides a digital output. The divider outputs are designed to change more slowly than the thresholds of the comparators, in this way the sensor is able to detect voltage droops. The sensor is implemented in a 65nm technology node occupying an area of 2700?m2 and displaying a power consumption of 50?W. It is designed to work with no voltage reference and with no clock and aiming to obtain a fast response.
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Leakage power consumption is a com- ponent of the total power consumption in data cen- ters that is not traditionally considered in the set- point temperature of the room. However, the effect of this power component, increased with temperature, can determine the savings associated with the careful management of the cooling system, as well as the re- liability of the system. The work presented in this paper detects the need of addressing leakage power in order to achieve substantial savings in the energy consumption of servers. In particular, our work shows that, by a careful detection and management of two working regions (low and high impact of thermal- dependent leakage), energy consumption of the data- center can be optimized by a reduction of the cooling budget.
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Simulation of satellite subsystems behaviour is extramely important in the design at early stages. The subsystems are normally simulated in the both ways : isolated and as part of more complex simulation that takes into account imputs from other subsystems (concurrent design). In the present work, a simple concurrent simulation of the power subsystem of a microsatellite, UPMSat-2, is described. The aim of the work is to obtain the performance profile of the system (battery charging level, power consumption by the payloads, power supply from solar panels....). Different situations such as battery critical low or high level, effects of high current charging due to the low temperature of solar panels after eclipse,DoD margins..., were analysed, and different safety strategies studied using the developed tool (simulator) to fulfil the mission requirements. Also, failure cases were analysed in order to study the robustness of the system. The mentioned simulator has been programed taking into account the power consumption performances (average and maximum consumptions per orbit/day) of small part of the subsystem (SELEX GALILEO SPVS modular generators built with Azur Space solar cells, SAFT VES16 6P4S Li-ion battery, SSBV magnetometers, TECNOBIT and DATSI/UPM On Board Data Handling -OBDH-...). The developed tool is then intended to be a modular simulator, with the chance of use any other components implementing some standard data.
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As advanced Cloud services are becoming mainstream, the contribution of data centers in the overall power consumption of modern cities is growing dramatically. The average consumption of a single data center is equivalent to the energy consumption of 25.000 households. Modeling the power consumption for these infrastructures is crucial to anticipate the effects of aggressive optimization policies, but accurate and fast power modeling is a complex challenge for high-end servers not yet satisfied by analytical approaches. This work proposes an automatic method, based on Multi-Objective Particle Swarm Optimization, for the identification of power models of enterprise servers in Cloud data centers. Our approach, as opposed to previous procedures, does not only consider the workload consolidation for deriving the power model, but also incorporates other non traditional factors like the static power consumption and its dependence with temperature. Our experimental results shows that we reach slightly better models than classical approaches, but simul- taneously simplifying the power model structure and thus the numbers of sensors needed, which is very promising for a short-term energy prediction. This work, validated with real Cloud applications, broadens the possibilities to derive efficient energy saving techniques for Cloud facilities.
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As embedded systems evolve, problems inherent to technology become important limitations. In less than ten years, chips will exceed the maximum allowed power consumption affecting performance, since, even though the resources available per chip are increasing, frequency of operation has stalled. Besides, as the level of integration is increased, it is difficult to keep defect density under control, so new fault tolerant techniques are required. In this demo work, a new dynamically adaptable virtual architecture (ARTICo3) to allow dynamic and context-aware use of resources is implemented in a high performance Wireless Sensor node (HiReCookie) to perform an image processing application.
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Dynamic and Partial Reconfiguration (DPR) allows a system to be able to modify certain parts of itself during run-time. This feature gives rise to the capability of evolution: changing parts of the configuration according to the online evaluation of performance or other parameters. The evolution is achieved through a bio-inspired model in which the features of the system are identified as genes. The objective of the evolution may not be a single one; in this work, power consumption is taken into consideration, together with the quality of filtering, as the measure of performance, of a noisy image. Pareto optimality is applied to the evolutionary process, in order to find a representative set of optimal solutions as for performance and power consumption. The main contributions of this paper are: implementing an evolvable system on a low-power Spartan-6 FPGA included in a Wireless Sensor Network node and, by enabling the availability of a real measure of power consumption at run-time, achieving the capability of multi-objective evolution, that yields different optimal configurations, among which the selected one will depend on the relative “weights” of performance and power consumption.
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A novel temperature sensor based on nematic liquid crystal permittivity as a sensing magnitude, is presented. This sensor consists of a specific micrometric structure that gives considerable advantages from other previous related liquid crystal (LC) sensors. The analytical study reveals that permittivity change with temperature is introduced in a hyperbolic cosine function, increasing the sensitivity term considerably. The experimental data has been obtained for ranges from −6 °C to 100 °C. Despite this, following the LC datasheet, theoretical ranges from −40 °C to 109 °C could be achieved. These results have revealed maximum sensitivities of 33 mVrms/°C for certain temperature ranges; three times more than of most silicon temperature sensors. As it was predicted by the analytical study, the micrometric size of the proposed structure produces a high output voltage. Moreover the voltage’s sensitivity to temperature response can be controlled by the applied voltage. This response allows temperature measurements to be carried out without any amplification or conditioning circuitry, with very low power consumption.
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The current trend in the evolution of sensor systems seeks ways to provide more accuracy and resolution, while at the same time decreasing the size and power consumption. The use of Field Programmable Gate Arrays (FPGAs) provides specific reprogrammable hardware technology that can be properly exploited to obtain a reconfigurable sensor system. This adaptation capability enables the implementation of complex applications using the partial reconfigurability at a very low-power consumption. For highly demanding tasks FPGAs have been favored due to the high efficiency provided by their architectural flexibility (parallelism, on-chip memory, etc.), reconfigurability and superb performance in the development of algorithms. FPGAs have improved the performance of sensor systems and have triggered a clear increase in their use in new fields of application. A new generation of smarter, reconfigurable and lower power consumption sensors is being developed in Spain based on FPGAs. In this paper, a review of these developments is presented, describing as well the FPGA technologies employed by the different research groups and providing an overview of future research within this field.