基于WirelessHART无线传感器网络系统的设计与实现

针对传统无线传感器网络系统精度低、能耗高、通信距离短等问题。提出一种基于WirelessHART技术的新型无线传感器网络系统,该系统以WirelessHART标准为平台,在此基础上设计了主板电路、无线通信以及传感器等模块。并对WirelessHART设备节点进行有障碍传输、精度以及能耗测试。测试结果表明：设计的WirelessHART设备节点可自动克服障碍传输,精度高达98%,相比ZigBee终端节点可降低31天的能耗。该系统设计的节点具有体积小,功耗低,精度高,抗扰能力强等优点。     

无线传感器网络LEACH路由算法改进

在分析了无线传感器网络中分层路由LEACH算法的基础上,根据网络中节点初始能量的不同,提出了一种新型簇首节点选择方法,并通过MATLAB对改进后的LEACH算法进行了仿真,仿真结果显示改进后的LEACH算法充分利用了网络的功耗。     

基于MIMO的节能无线传感器网络

当今无线传感器网络主要是同构网络,即网络中传感器节点结构相同,该结构不适合基于组的传感器网络.本文通过使用多天线传感器节点作为无线传感器网络中的组长节点将MIMO和SIMO方式引入组间层和组内层组员与组长之间的通讯.文中介绍了该异构网络的基本通讯机制并对其实现进行了讨论,并提出了MIMO的传感器网络功耗和延迟模型.通过模拟实验验证了该模型优于同构网络.     

无线传感器网络的动态电压调节算法研究

对于能量有限的无线传感器网络,研究如何高效地利用有限能量具有重要意义.根据无线传感器网络多跳路由和拓扑易变的特点,提出一种基于任务驱动的含反馈的动态电压调节算法FB-DVS.该算法根据节点的任务集实时地调节节点的工作电压和频率,并通过反馈环节来修正误差,在保证任务实时性的前提下降低节点能耗.通过对仿真结果分析表明,改进的算法能有效地减少节点的能量消耗,延长无线传感器网络的生命周期.     

面向电力监控的无线传感器网络算法研究

文中考虑在电力监控系统中部署能量受限的传感器网络,这种网络中的每个传感器节点系统地收集传输的数据并将其传输到基站,着重于降低无线传感器网络的功耗。提出了一种适用于大范围无线传感器网络的能量平衡聚类路由算法(LEACH-L),并推导出最佳跳数。最后对发射节点的最佳位置进行了估计。仿真结果表明,改进后的方案可以在网络中的第一个节点结束前将网络生存期延长80%,该算法比现有的LEACH、LEACH-M等聚类算法具有更高的性能。     

一种基于RSSI的几何位置定位新算法

RSSI(接收信号强度指示)测距技术在室内应用环境中,由于多径、绕射、障碍物等因素,无线电传播路径损耗在定位过程中产生的距离误差影响了定位求精的功效,为提高定位精度,通过引入圆的几何力量线--根轴的概念,采用RSSI室内信道模型,提出了一种改进的三边定位算法:根轴定位算法.该算法无需增加额外的硬件开销,容易实现.计算机仿真结果表明,在25 m以内的环境中定位误差可小于3 cm,适合于处理能力和能量有限的无线传感器网络节点.     

一种轻量级的无线传感器网络密钥建立协议

该文提出了一种适用于无线传感器网络的轻量级密钥建立协议。该协议以预置的瞬时初始密钥为基础,通过优化密钥建立过程中的信息交互,能够获得更好的可扩展性和更低的能量开销。对该协议的完成时间和网络的连通概率的理论分析表明,该协议是可行的。从仿真结果可以看出,该协议在典型的网络规模下可以获得超过97%的连通概率。与同类协议相比,可以在保证足够的连通概率的情况下以更短的时间完成密钥建立。当网络密度为单跳30个节点时,建立时间小于5.2 s。此外,该协议的能量开销只有同类协议的25%,因此更适合应用于资源受限的无线传感器节点。     

无线传感器网络的智能低功耗侦听协议

无线传感器网络MAC层协议低功耗侦听(LPL)使用较长的前导码,在密集部署的无线传感器网络中造成较大的"串音"开销.提出一种智能低功耗侦听协议(SLPL),通过在前导码中嵌入目的地址和前导码长度索引,能有效降低非目的节点的串音开销,减少目的节点的接收开销.理论分析和部署测试表明SLPL的能效比LPL有显著提高,同时测试显示SLPL功耗小于X-MAC协议.     

基于ZigBee的低功耗无线传感节点设计与实现

以CC2430芯片为核心设计一种用于温湿度测量的无线传感节点,为了降低节点功耗,在ZigBee协议栈的基础上进行改进,为传感节点设计了空闲、触发和主动等3种工作模式,使节点能够按照实际需求控制采样的时机和速率,以减少传感节点用于无线通信的能量开销,从而满足无线传感器网络对节点低功耗的设计要求,同时根据已知参数预测传感节...     

基于跨层设计的无线传感器网络节能双向梯度路由算法

针对现有无线传感器网络梯度路由算法在下行路由创建过程和能量更新机制中存在冗余控制开销的问题,该文提出一种采用跨层和功率控制机制,具有节能功能的双向梯度路由算法(Cross-layer Energy-efficient Bidirectional Routing,CEBR):无需使用专门的控制分组,采用源路由方式以较小开销建立从Sink节点通往传感器节点的下行路由;通过跨层信息共享,定期采集节点剩余能量信息并按需发布;设计使用含跳数和节点剩余能量的合成路由度量标准,减少节点能量和网络带宽消耗的同时均衡节点能耗;结合RSSI(Received Signal Strength Indication)测距实现节点发射功率控制从而在数据及查询分组发送过程中节约节点能量。理论分析表明了CEBR的有效性;仿真结果显示:与现有的典型相关算法相比,CEBR能够在建立双向梯度路由的前提下,至少降低34.5%的归一化控制开销和27.12%的数据分组平均能耗,并使网络生存期延长18.98%以上。     

Comparison of energy intake prediction algorithms for systems powered by photovoltaic harvesters

Small size photovoltaic modules can harvest enough energy to power many personal devices and wireless sensor nodes. The prediction of solar energy intake is possible thanks to the periodical availability of the sunlight and its cyclic behavior. Thus, smart and innovative power management strategies can take advantage from intake prediction algorithms to optimize the energy usage by keeping the system in low power state as long as possible. On the other hand, very accurate predictions need time and energy because of complex calculations, thus an algorithm that can provide the optimal trade-off between computational effort and accuracy is a breakthrough for systems with tight power constraints. In this paper we introduce an innovative, efficient and reliable solar prediction algorithm, the weather conditioned moving average (WCMA). The algorithm has been further enhanced to increase performance using a phase displacement regulator (PDR) which reduces the average error to less than 9.2% at a minimum energy cost. The proposed new algorithm compares favorably with several competing approaches.     

An improved key distribution mechanism for large-scale hierarchical wireless sensor networks

Wireless sensor networks are often deployed in hostile environments and operated on an unattended mode. In order to protect the sensitive data and the sensor readings, secret keys should be used to encrypt the exchanged messages between communicating nodes. Due to their expensive energy consumption and hardware requirements, asymmetric key based cryptographies are not suitable for resource-constrained wireless sensors. Several symmetric-key pre-distribution protocols have been investigated recently to establish secure links between sensor nodes, but most of them are not scalable due to their linearly increased communication and key storage overheads. Furthermore, existing protocols cannot provide sufficient security when the number of compromised nodes exceeds a critical value. To address these limitations, we propose an improved key distribution mechanism for large-scale wireless sensor networks. Based on a hierarchical network model and bivariate polynomial-key generation mechanism, our scheme guarantees that two communicating parties can establish a unique pairwise key between them. Compared with existing protocols, our scheme can provide sufficient security no matter how many sensors are compromised. Fixed key storage overhead, full network connectivity, and low communication overhead can also be achieved by the proposed scheme.     

Dual head static clustering algorithm for wireless sensor networks

Clustering of nodes is often used in wireless sensor networks to achieve data aggregation and reduce the number of nodes transmitting the data to the sink. This paper proposes a novel dual head static clustering algorithm (DHSCA) to equalise energy consumption by the sensor nodes and increase the wireless sensor network lifetime. Nodes are divided into static clusters based on their location to avoid the overhead of cluster re-formation in dynamic clustering. Two nodes in each cluster, selected on the basis of the their residual energy and their distance from the sink and other nodes in the cluster, are designated as cluster heads, one for data aggregation and the other for data transmission. This reduces energy consumption during intra-cluster and inter-cluster communication. A multi-hop technique avoiding the hot-spot problem is used to transmit the data to the sink. Experiments to observe the energy consumption patterns of the nodes and the fraction of packets successfully delivered using the DHSCA suggest improvements in energy consumption equalisation, which, in turn, enhances the lifetime of the network. The algorithm is shown to outperform all the other static clustering algorithms, while being comparable with the performance of the best dynamic algorithm.     

Performance analysis of an improved dynamic power management model in wireless sensor node

The energy consumption in the wireless sensor networks is a very critical issue which attracts immediate attention for the sake of the growing demand of the billion dollar market in future. The Dynamic Power Management (DPM) technique is a way of controlling and saving the energy usage in a sensor node. Previously, researchers have proposed lifetime improving stochastic models for wireless sensor networks and limited work has been done focusing on the wireless sensor node. This paper proposes an analyser based Semi-Markov model for DPM in the event-driven sensor node. The power consumption comparison with previously proposed models without this analyser shows the analyser significant contributes to lifetime improvement. The improved model is more power efficient, presents how the DPM model observes the input event arrival and power states of the sensor node components, and then dynamically manages the power consumption of the overall system. Further, to observe the effect of event arrival, missed events, waiting time, processor utilization on the power consumption and lifetime, the proposed DPM system with the single server queuing model is developed.     

基于连通支配集的无线传感网Top-k查询最优支撑树研究

构建底层逻辑树能有效降低集中式top-k查询带来的巨大通信开销,针对现有逻辑树都以固定汇聚节点为根节点,导致其附近节点能耗太大、过早死亡的问题,本文在无固定汇聚节点的网络背景下,基于连通支配集,提出一种能耗均衡的top-k查询最优支撑树构建方法,综合节点能量、度数以及与邻节点通信开销,选取能量代价小的作为支配节点负责查询中间数据处理,在每次查询中,节点基于地理位置ID轮流作为根节点,有效均衡节点的能耗.仿真实验表明,与其他逻辑拓扑树相比,基于最优支撑树的top-k查询具有相近的查询时间,但其平均每轮查询能耗更小,多次查询后各节点能耗达到均衡,有效延长了网络生命周期.     

一种无线传感器网络的能耗平衡覆盖模型

针对无线传感器网络节点能量有限、最小覆盖方法能耗不均衡的问题,该文提出了一种能耗平衡的连通覆盖模型,并对模型进行了分析与仿真。模型利用Voronoi划分和Delaunay三角剖分对传感器网络进行分割,判别重复覆盖目标区域的冗余传感器节点,采用节点到sink点的跳数对节点分层,进而提出选择休眠节点的方法。仿真结果表明,由模型建立的非最小连通覆盖集所导出的无线传感器网络,能够平衡节点能耗、使用优化路由、减弱路由关键点的影响。     

Instruction‐Level Power Estimator for Sensor Networks

In sensor networks, analyzing power consumption before actual deployment is crucial for maximizing service lifetime. This paper proposes an instruction‐level power estimator (IPEN) for sensor networks. IPEN is an accurate and fine grain power estimation tool, using an instruction‐level simulator. It is independent of the operating system, so many different kinds of sensor node software can be simulated for estimation. We have developed the power model of a Micaz‐compatible mote. The power consumption of the ATmega128L microcontroller is modeled with the base energy cost and the instruction overheads. The CC2420 communication component and other peripherals are modeled according to their operation states. The energy consumption estimation module profiles peripheral accesses and function calls while an application is running. IPEN has shown excellent power estimation accuracy, with less than 5% estimation error compared to real sensor network implementation. With IPEN's high precision instruction‐level energy prediction, users can accurately estimate a sensor network's energy consumption and achieve fine‐grained optimization of their software.     

A Distributed Query Protocol in Wireless Sensor Networks

In wireless sensor networks, query execution over a specific geographical region is an essential function for collecting sensed data. However, sensor nodes deployed in sensor networks have limited battery power. Hence, the minimum number of connected sensor nodes that covers the queried region in a sensor network must be determined. This paper proposes an efficient distributed protocol to find a subset of connected sensor nodes to cover the queried region. Each node determines whether to be a sensing node to sense the queried region according to its priority. The proposed protocol can efficiently construct a subset of connected sensing nodes and respond the query request to the sink node. In addition, the proposed protocol is extended to solve the k-coverage request. Simulation results show that our protocol is more efficient and has a lower communication overhead than the existing protocol.     

Energy awareness workflow model for wireless sensor nodes

Before the development of a large‐scale wireless sensor network (WSN) infrastructure, it is necessary to create a model to evaluate the lifespan of the infrastructure, the system performance and the cost so that the best design solution can be obtained. Energy consumption is an important factor that influences the lifespan of WSNs. One of the ways to extend the lifespan of WSNs is to design wireless sensor nodes with low power consumption. This involves component selection and the optimisation of hardware architecture, monitoring software system and protocols to satisfy the requirements of the particular applications. This paper proposes a comprehensive model to describe the workflow of a wireless sensor node. Parameter setup and energy consumption calculation are demonstrated through the model simulation. It provides a mathematical approach to dynamically evaluate the energy consumption of a sensor node. This will benefit the development of wireless sensor nodes based on microprocessors with limited computational capability. Therefore, the model can be applied in dynamic power management systems for wireless sensor nodes or in wireless communication protocols with energy awareness, in particular, for WSNs with self‐organisation. More importantly, the generalisation of the model may be employed as a standard paradigm for the development of wireless sensor node with energy awareness. Copyright © 2012 John Wiley & Sons, Ltd.