无线应变测量节点的精度与功耗综合分析

在无线传感器网络中,一般采用电池供电,如何取得精度和功耗的平衡十分重要.应变片功耗与其他传感器相比大得多,直接决定无线节点总功耗.系统设计时,不但要考虑电路参数和器件噪声对精度的影响,功耗分析也很必要.从无线节点整体框架出发,系统分析了模拟和数字电路中精度和功耗的影响机理,建立了完整的理论模型.精度和功耗同时受电桥电压影响,电桥电压越高,精度越高,但功耗也越大,精度与功耗相互制约.以电桥电压和器件参数为影响因素,提出了在保证测量精度的同时,减小电路功耗的方法.在设计无线应变测量节点时,该研究可以为实现系统精度和功耗的平衡提供理论指导.     

Distributed computing for carbon footprint reduction by exploiting low-footprint energy availability

Low carbon footprint energy sources such as solar and wind power typically suffer from unpredictable or limited availability. By globally distributing a number of these renewable sources, these effects can largely be compensated for. We look at the feasibility of this approach for powering already distributed data centers in order to operate at a reduced total carbon footprint. From our study we show that carbon footprint reductions are possible, but that these are highly dependent on the approach and parameters involved. Especially the manufacturing footprint and the geographical region are critical parameters to consider. Deploying additional data centers can help in reducing the total carbon footprint, but substantial reductions can be achieved when data centers with nominal capacity well below maximum capacity redistribute processing to sites based on renewable energy availability.     

A note on models for non-probabilistic analysis of packet switching networks

We consider two models commonly used in the literature to model adversarial injection of packets into a packet switching network. We establish the relation between these two types of models, and between them and the set of sequences of packets that allow stability. We also consider the adaptive setting in which packets are injected with only their source and destination but without a prescribed path to follow.     

Modelling and optimization of power consumption in wireless access networks

The power consumption of wireless access networks will become an important issue in the coming years. In this paper, the power consumption of base stations for mobile WiMAX, fixed WiMAX, UMTS, HSPA, and LTE is modelled and related to the coverage. A new metric, the power consumption per covered area PC_area, is introduced, to compare the energy efficiency of the considered technologies for a range of bit rates. Assuming the model parameters are correct, the conclusions are then as follows. For a 5 MHz channel, UMTS is the most energy-efficient technology until a bit rate of 2.8 Mbps, LTE between 2.8 Mbps and 8.2 Mbps, fixed WiMAX between 8.2 Mbps and 13.8 Mbps and finally mobile WiMAX for bit rates higher than 13.8 Mbps. Furthermore, the influence of MIMO is investigated.For a 2 × 2 MIMO system, PC_area decreases by 36% for mobile WiMAX and by 23% for HSPA and LTE compared to the SISO system, resulting in a higher energy efficiency.The power consumption model for base stations is used in the deployment tool GRAND (Green Radio Access Network Design) for green wireless access networks. GRAND uses a genetic based algorithm and is applied on an actual case for the Brussels Capital Region, showing the possibilities of energy-efficient planning.     

A modeling approach on the TelosB WSN platform power consumption

Substantial characteristics of wireless sensor networks, such as autonomy and miniature size, are achieved at the expense of restricted energy resources. Optimal resource management is thus among the most important challenges in WSNs development and its success requires accurate and practical models based on detailed insight concerning the factors contributing to the overall power consumption of a WSN mote. To achieve such awareness, that will enable models development, appropriate measuring test-beds and methodologies are needed, facilitating reliable and accurate power consumption measurements of critical functionalities.To cover the need for energy models that precisely define the power consumption behavior of WSN hardware platforms, this paper contributes with a measuring methodology including three steps: the design and implementation of a measuring system for a wide range of power consumption thresholds, the identification, isolation and measurement of elementary functionalities of a WSN platform with respect to their contribution to the overall mote power consumption, and the extraction of valuable conclusions based on the respective measurements resulting in the composition of a practical, yet accurate power consumption model.     

Wavelet-based multi-resolution analysis and artificial neural networks for forecasting temperature and thermal power consumption

As part of the OptiEnR research project, the present paper deals with outdoor temperature and thermal power consumption forecasting. This project focuses on optimizing the functioning of a multi-energy district boiler (La Rochelle, west coast of France), adding to the plant a thermal storage unit and implementing a model-based predictive controller. The proposed short-term forecast method is based on the concept of time series and uses both a wavelet-based multi-resolution analysis and multi-layer artificial neural networks. One could speak of “MRA-ANN” methodology. The discrete wavelet transform allows decomposing sequences of past data in subsequences (named coefficients) according to different frequency domains, while preserving their temporal characteristics. From these coefficients, multi-layer Perceptrons are used to estimate future subsequences of 4 h and 30 min. Future values of outdoor temperature and thermal power consumption are then obtained by simply summing up the estimated coefficients. Substituting the prediction task of an original time series of high variability with the estimation of its wavelet coefficients on different levels of lower variability is the main idea of the present work. In addition, the sequences of past data are completed, for each of their components, by both the minute of the day and the day of the year to place the developed model in time. The present paper mainly focuses on the impact on forecast accuracy of various parameters, related with the discrete wavelet transform, such as both the wavelet order and the decomposition level, and the topology of the neural networks used. The number of past sequences to take into account and the chosen time step were also major concerns. The optimal configuration for the tools used leads to very good forecasting results and validates the proposed MRA-ANN methodology.     

A power efficiency routing and maintenance protocol in wireless multi-hop networks

In wireless multi-hop networks, selecting a path that has a high transmission bandwidth or a high delivery rate of packets can reduce power consumption and shorten transmission delay during data transmission. There are two factors that influence the transmission bandwidth: the signal strength of the received packets and contentions in the contention-based MAC layer. These two factors may cause more power to be consumed during data transmission. We analyze these two factors and propose a power-aware routing protocol called MTPCR. MTPCR discovers the desired routing path that has reduced power consumption during data transmission. In addition to finding a desired path to reduce power consumption, MTPCR also takes into account the situations in which the transmission bandwidth of the routing path may decrease, resulting in much power consumption during data transmission because of the mobility of nodes in a network. MTPCR is thus useful in a network: it analyzes power consumption during data transmission with the help of neighboring nodes, and it uses a path maintenance mechanism to maintain good path bandwidth. The density of nodes in a network is used to determine when to activate the path maintenance mechanism in order to reduce the overhead of this mechanism. With the proposed path maintenance mechanism, power consumption during data transmission can be efficiently reduced, as well as the number of path breakages. In our simulation, we compared our proposed routing protocol, MTPCR, with the following protocols: two classical routing protocols, AODV and DSR; two power-aware routing protocols, MMBCR and xMBCR; and one multiple path routing protocol, PAMP. The comparisons are made in terms of throughput of the routing path, power consumption in path discovery, power consumption in data transmission, and network lifetime.     

On the performance and power consumption analysis of elastic clouds

Cloud computing is a novel paradigm capable of rationalizing the use of computational resources by means of outsourcing and virtualization. Elasticity is one of the most attractive features of cloud computing. Elastic clouds are able to adapt to workload changes by provisioning and de‐provisioning resources in an autonomic manner, such that at each point in time the available resources match the current demand as closely as possible. However, elasticity adds complexity, which makes quantitative analysis of cloud performance and power consumption difficult. Such analysis is required to evaluate and quantify the cost‐benefit of a strategy portfolio and the quantitative runtime performance and power consumption experienced by cloud‐users. In this study, we present a comprehensive analytical approach to performance and power consumption analysis of elastic clouds. Several metrics are defined and evaluated: expected task completion time, power consumption rate, and task rejection rate under different load conditions, elasticity intensities, and error intensities. To validate the proposed approach, we obtain experimental data through a real‐world cloud and conduct a confidence interval analysis. The analysis results suggest the perfect coverage of theoretical results by corresponding experimental confidence intervals. Copyright © 2016 John Wiley & Sons, Ltd.     

基于减少偷听的IEEE 802.15.4网络节点能耗降低方法*

为了优化IEEE 802.15.4 MAC协议能耗性能,针对IEEE 802.15.4 MAC协议存在的空闲偷听现象浪费节点能量问题,提出一种基于减少偷听的降耗方法：节点于超帧竞争接入时期内的退避时期适时地进入休眠状态。应用该方法建立了IEEE 802.15.4 MAC时隙CSMA/CA机制的Markov模型,并对模型进行了数学推导。基于本模型,对网络节点平均能耗进行了数学分析。理论分析和仿真结果表明,该模型有效地降低了节点的平均能量消耗和空闲偷听时间,协议性能得到有效改善。     

无线传感器网络低功耗真随机源设计

针对无线传感器网络(WSNs)密码安全应用过程中的低功耗需求和无线传感器网络节点集成微型化的趋势,提出一种新的真随机源设计方法用于生成高质量密钥来保证密码算法安全性。该方法基于概率计算单元构建斐波那契振荡随机源。由于概率计算单元工作状态在MOS管的亚阈值电流区,工作电流小使得设计功耗极低。同时,防止电路停振,设计概率信号放大单元保证随机振荡正确性。本设计在中芯国际SMIC 0.13μm工艺下进行仿真验证,所产生的真随机序列性能良好。与基于数字逻辑门的振荡真随机源相比,功耗减小1000倍,面积也有明显减小,适合应用于无线传感器网络之中。     

一种低功耗的无线传感器网络MAC协议

在无线传感器网络中,为了避免不必要的能耗而达到延长网络寿命的目的,提出一种低功耗的无线传感器网络MAC协议。此协议在低功率侦听(LPL)基础上进行修改,通过前一次轮询的结果来推测这一次的流量状况,根据流量状况自适应调整侦听睡眠周期结构中相应的占空比,从而降低能耗。通过编程仿真并结合实验,对此模型进行验证,证明了此算法能降低能耗。     

Power-aware anomaly detection in smartphones: An analysis of on-platform versus externalized operation

Many security problems in smartphones and other smart devices are approached from an anomaly detection perspective in which the main goal reduces to identifying anomalous activity patterns. Since machine learning algorithms are generally used to build such detectors, one major challenge is adapting these techniques to battery-powered devices. Many recent works simply assume that on-platform detection is prohibitive and suggest using offloaded (i.e., cloud-based) engines. Such a strategy seeks to save battery life by exchanging computation and communication costs, but it still remains unclear whether this is optimal or not in all circumstances. In this paper, we evaluate different strategies for offloading certain functional tasks in machine learning based detection systems. Our experimental results confirm the intuition that outsourced computation is clearly the best option in terms of power consumption, outweighing on-platform strategies in, essentially, all practical scenarios. Our findings also point out noticeable differences among different machine learning algorithms, and we provide separate consumption models for functional blocks (data preprocessing, training, test, and communications) that can be used to obtain power consumption estimates and compare detectors.     

Numerical analysis of the power saving with a bursty traffic model in LTE-Advanced networks

We analyze the power saving operation called Discontinuous Reception (DRX) with a novel bursty packet arrival model in 3GPP Long Term Evolution (LTE)-Advanced networks. Typical analytical studies on the power saving operations in wireless networks have been carried out under the assumption that an expectation of exponentially distributed packet arrival intervals stays unchanged. However, practical packet arrival rate may change depending on time or typical Internet services may incur bursty packet arrivals. In either case, we need to evaluate the performance of the DRX operation. For this purpose, we develop a more realistic traffic arrival model considering packets may arrive in a bursty manner under the DRX operation. We, then, analyze the performance of the DRX operation in terms of power saving efficiency and average queuing delay, respectively. The analytical results are validated via comparisons with simulation results.     

新型无线传感器网络节点供电方案

工业现场对振动信号等快变量进行采集时,需要对无线传感器网络节点进行在线供电.通过分析开关噪声对无线传感器网络节点通信质量的影响,并结合传感器网络的工作特点,给出无线传感器网络供电方案的设计要求.针对开关噪声的宽频谱特点,提出适用于无线传感器网络的供电方案,实验表明:该供电方案可有效消除电源噪声.     

A routing algorithm based on clusters and balance use of energy for wireless sensor networks

In a sensor network, data collected by different sensors are often correlated because they are observations of related phenomena. Efficient sensor data fusion is one of the most important issues in building real sensor networks. To balance energy cost, how to select a cluster head is a key problem that must be addressed. In this paper, we use a compression-centric data collection algorithm for use in wireless sensor networks. Also, we propose a balanced cluster head selection algorithm in each cluster. Simulation results are used to investigate the performance of the algorithm. Compared to the exhaustive search solutions, the proposed algorithm shows a significant improvement in power consumption.     

Examining the spillover effect of sustainable consumption on microloan repayment: A big data-based research

Social value-oriented consumers perform more sustainable consumption than conventional consumers do because consumers’ choices reflect their latent social values on environmental protection. However, whether sustainable consumption prompts more social value-oriented behaviors outside the consumption domain remains uncertain. The increased availability of consumer-level big data presents an opportunity to investigate consumers’ cross-domain behavior subsequent to sustainable consumption, which broadens the comprehension of sustainable consumption by going beyond the boundary of consumption behavior. Supported by a joint dataset comprising information on both consumers’ consumption behavior and their microloan repayment behavior, this study examines the effects of sustainable consumption on consumers’ subsequent debt default behavior to empirically test the cross-domain spillover effects of sustainable consumption behavior. The results suggest that the default probability of green consumers overall was 4.34 % lower than that of nongreen consumers, even though this positive effect on repayment disappears when sustainable consumption is for health reasons. The findings contribute to research on sustainable consumption by providing empirical evidence indicating that sustainable consumption has positive spillover effects in other domains. The results also provide an alternative perspective for identifying high-quality borrowers for microloan platforms.     

A routing algorithm based on clusters and balanced use of energy for wireless sensor networks

In a sensor network,data collected by different sensors are often correlated because they are observations of related phenomena.Efficient sensor data fusion is one of the most important issues in building real sensor networks.To balance energy cost,how to select a cluster head is a key problem that must be addressed.In this paper,we use a compression-centric data collection algorithm for use in wireless sensor networks.Also,we propose a balanced cluster head selection algorithm in each cluster.Simulation re...     

浅析质量式油耗仪的现场校验

检测汽车燃油消耗量常是通过燃油消耗检测仪测定燃油消耗量的容积或质量来表示。其按测量方法可分为：容积式油耗仪、质量式油耗仪、流量式油耗仪、流速式油耗仪。大多数油耗仪都能连续、累计测量,但测试的流量范围和流量误差各不相同。现以质量式油耗仪为例予以浅析其现场的校验。     

GPH: A group-based partitioning scheme for reducing total power consumption of parallel buses

Two main sources for power dissipation in parallel buses are data transitions on each wire and coupling between adjacent wires. So far, many techniques have been proposed for reducing the self and coupling powers. Most of these methods utilize one (or more) control bit(s) to manage the behavior of data transitions on the parallel bus. In this paper, we propose a new coding scheme, referred to as GPH, to reduce power dissipation of these control bits. GPH coding scheme employs partitioned Bus Invert and Odd Even Bus-Invert coding techniques. This method benefits from Particle Swarm Optimization (PSO) algorithm to efficiently partition the bus. In order to reduce self and coupling powers of the control bits, it finds partitions with similar transition behaviors and groups them together. One extra control bit is added to each group of partitions. Properly managing number of transitions on control bits of each partition and that of each group, GPH reduces total power consumption, including coupling power. It also locates control bits of each partition such that total power consumption is minimized. We evaluate the efficiency of the proposed method for coding data and address buses under various hardware platforms. Experimental results show 43% average power saving in coded data compared to the original one. We also show the prominence of our coding scheme over previously proposed techniques.