无线传感器网络节点的功耗分析与测试

能量消耗问题是无线传感器网络的核心问题,直接影响着网络的生命周期。本文从无线传感器网络节点的硬件构成其及运行机制、计算复杂性、数据通信量等方面去分析节点的功耗,并建立模块的功耗模型;接着研究传感节点的电流特点和微功耗测量技术,设计了一种传感节点的测量系统,以验证节点的低功耗特性。这些措施都是为了更好地分析解决无线传感网络中的能量消耗问题,保证传感器网络能量管理的有效性。     

基于功耗模型的无线传感器网络节点生存模式评估

作为一种能量受限网络,无线传感器网络节点能耗评估具有重要意义。分析组成无线传感器网络节点各个单元功耗与状态的关系,建立基于节点工作状态的功耗模型,提出节点生存模式评估方法。给出典型节点生存模式实验用例,在振动检测实验平台上进行相关参数测量与验证。实验数据表明：该方法优于Petri网模型,可为无线传感器网络节点节能优化提供较为可靠的依据。     

基于Zigbee的无线动态应变测量

ZigBee是一种低速率、低成本、低功耗的短程无线网络协议。利用最新的Zigbee无线传感器网络技术和零漂移数字可设增益应变放大器对传统的应变测量在技术上进行改进,使得应变测量更方便、灵活和准确。作者给出其测量方案的精密激励电源、仪表放大电路、DAC调零和射频硬件电路以及Zigbee无线网络协议软件设计。所设计的应变测量模块具有体积小、精度高、功耗低、配置灵活的特点。实际应用表明,该设计满足技术方案的要求并已成功地应用于桥梁和机械应变测试系统中。     

无线传感器网络节点任务调度与功耗管理算法研究

针对有能量采集系统的无线传感器网络节点异质多核SoC平台,从提高能量利用效率的角度,提出了一种任务调度与功耗管理算法.该算法处理实时有截止时间并有相互依赖关系的任务,任务执行在多个电压可调的处理单元上.通过对节点系统能量采集行为和应用情况进行分析建立了问题模型,并运用运筹学软件LINGO对模型做了求解.利用多组随机输入的任务流图对模型与算法进行了验证,该算法在功耗与时间约束范围内确实能有效提高系统的能量利用效率.     

WSN环境监测系统节点功耗与能量预警研究

良好的核心机房环境条件对于各类园区网络的正常运行至关重要,因此配备环境监测系统已经成为核心机房的一项妊备措施。针对传统监测系统布线的灵活性差等问题,本文提出了一种具有能量感知的节能无线传感器网环境监;受4系统。节点设计采用Jennic公司的JN5139SOC芯片,集成编译环境采用开源软件Code：：Blocks,其内部运行由简单任务调度器BOS来统一管理。最后结合本单位核心机房实际情况,经过实际测试,给出了恰当的节点布置方案、节点节能发射功率值,实现了能量监测预警功能。此方法不仅可以用于机房环境监测,对于其他环境监测,如现代化养殖场的环境监测同样适用。     

用于应变监测的无线传感器网络节点的设计

针对结构健康监测中应变监测系统的器件连线复杂、维修难度大的特点,设计了用于应变监测的无线传感器网络节点,其中,包括多通道应变传感信号调理电路模块、数字处理模块和无线收发模块的开发。对用于应变监测的无线传感器网络节点进行了标定,并通过无线传感器网络的载荷定位试验验证了用于应变监测的无线传感器网络节点抗干扰性强,实时性好,具有较高的稳定性和可靠性。     

低功耗温室无线测量节点的设计

为了提高温室环境参数的监测效果,采用射频SoC芯片nRF9E5、数字温湿度传感器SHT11及光强度传感器TSL2560D,设计了无线温湿度及光照度监控系统的测量节点;并根据无线通信系统的特点设计了系统的软硬件结构,其低功耗无线传输模式降低了节点的能耗.经调试和试验运行,系统具有可靠性高、使用方便、通信节点容量易扩展等优点,这对较大空间的温湿度及光照度的监控具有良好的应用价值.     

无线传感器网络节点定位问题研究

节点定位技术是无线传感器网络信息采集、传输和处理能力的基础技术之一。研究和分析了各类无线传感器节点定位技术,从定位精度、健壮性等方面分析总结当前无线传感器网络定位技术存在的问题,展望未来的研究前景与应用发展趋势。     

高精度无线应变测量系统硬件设计

无线应变测量系统无需考虑布线,装卸快速,受到人们的日益关注.但精度不够高的缺点限制了其广泛应用.提高精度的有效途径是在硬件设计时控制电路中的误差,对电路中的精度影响因素进行了系统分析,推导出电桥电压噪声、运放噪声、量化噪声与系统精度的定量关系,并提出了电路设计中各部分的精度指标.以此为依据,采用高精度恒流稳压电源,简化滤波电路等手段,设计了相应的信号处理、数据采集和无线收发电路,并选用低功耗器件以降低系统功耗.试验结果表明:该系统测量精度为0.245％,总功率最大时为178 mW,相关系数为0.998,多次测量重复性好,系统满足设计要求.     

无线传感器网络相机节点JPEG2000低功耗实现

无线传感器网络（WSNs）中,相机节点采集的图像数据量非常大,传输前需要对图像进行压缩。为了满足WSNs应用的低能耗、高图像质量需求,结合自行研制的基于DSP的相机节点,对JPEG2000图像压缩算法的低功耗实现问题进行了研究。对算法的小波变换、量化、编码等部分进行了改进,优化了其硬件实现方案。实验表明：通过一定的改进和优化,其实现过程中需要的存储量和实现时间大大降低,进而极大地降低节点能耗。     

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.     

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 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.     

一种超低功耗无线震动传感器设计

为实现长期无人值守的震动测量与目标识别,设计了一种超低功耗无线震动传感器.该传感器采用磁电式敏感元件来获取震动信号,通过信号调理、数据采集、数据分析、数据存储和无线通信的软硬件设计,完成目标识别和数据传输.通过免供电传感和双处理器设计实现超低功耗工作,利用无线传感器网络监测模式构建无线、分布式震动监测网络.试验结果表明:该传感器能够完成震动信号测量并识别履带车和行人这两种典型目标,电流仅有30μA,预计可连续工作200天以上.     

Utility-based downlink power allocation in multicell wireless packet networks

This paper introduces a utility-based radio resource management technique in multicell wireless packet networks. In terms of allocation of base station (BS) downlink transmit power and assignment of resource to users in each cell, we formulate a problem of maximizing system utility which is defined as the sum of cell utilities. The problem, however, is not solvable due to its non-convex property. Thus, we propose a heuristic algorithm based on an intuition obtained from analyzing a simple two-cell problem. Though the heuristic approach also incurs signaling overhead for power coordination between neighboring base stations, it is much less than that of the original approach. Simulation results show the performance of our proposed algorithm compared with two competitive schemes: optimal and maximum power allocation schemes. As expected, the optimal allocation scheme shows the best performance but can not be employed in a real network due to intractable complexity. Our heuristic algorithm performs reasonably well with very low complexity.     

Application-aware integration of data collection and power management in wireless sensor networks

Sensors are typically deployed to gather data about the physical world and its artifacts for a variety of purposes that range from environment monitoring, control, to data analysis. Since sensors are resource constrained, often sensor data is collected into sensor databases that reside at (more powerful) servers. A natural tradeoff exists between resources (bandwidth, energy) consumed and the quality of data collected at the server. Blindly transmitting sensor updates at a fixed periodicity to the server results in a suboptimal solution due to the differences in stability of sensor values and due to the varying application needs that impose different quality requirements across sensors. In order to adapt to these variations while at the same time optimizing the energy consumption of sensors, this paper proposes three different models and corresponding data collection protocols. We analyze all three models with a Markov state machine formulation, and either derive closed forms for the operation point of the data collection application or suggest algorithms for estimating this operating point to achieve a minimal energy consumption. We observe that the operating point depends on environmental characteristics and application quality requirements, which the proposed algorithms aim to accommodate. Our experimental results show significant energy savings compared to the naive approach to data collection.     

Practical data compression in wireless sensor networks: A survey

Power consumption is a critical problem affecting the lifetime of wireless sensor networks. A number of techniques have been proposed to solve this issue, such as energy-efficient medium access control or routing protocols. Among those proposed techniques, the data compression scheme is one that can be used to reduce transmitted data over wireless channels. This technique leads to a reduction in the required inter-node communication, which is the main power consumer in wireless sensor networks. In this article, a comprehensive review of existing data compression approaches in wireless sensor networks is provided. First, suitable sets of criteria are defined to classify existing techniques as well as to determine what practical data compression in wireless sensor networks should be. Next, the details of each classified compression category are described. Finally, their performance, open issues, limitations and suitable applications are analyzed and compared based on the criteria of practical data compression in wireless sensor networks.     

移动检测节点能耗优化及预测研究

无线传感器网络具有智能感知外界信息的能力.由于外界环境变化的影响,传感器检测移动事件消耗的能量具有不确定性.在移动频率较低的情况下频繁地检测移动事件会浪费不必要的能耗.在不错过移动事件发生并使节点尽可能长时间地运行在低功耗工作模式的情况下,设置合理的移动检测周期是节点能量利用的关键.介绍了一种无线传感器网络节点能耗的模型,利用该模型的能耗计算方法推算出了在不同移动频率情况下合适的检测参数,对移动检测节点能耗进行优化.通过不同移动频率的实验,论证了该模型能耗计算方法的有效性,并进一步对能耗进行了预测.     

A robust power and rate control method for state-delayed wireless networks

A robust power and rate control algorithm is proposed for distributed wireless networks where the network dynamics is modelled as an uncertain discrete-time state-delayed system.