Optimizing Lifetime for Continuous Data Aggregation With Precision Guarantees in Wireless Sensor Networks

This paper exploits the tradeoff between data quality and energy consumption to extend the lifetime of wireless sensor networks. To obtain an aggregate form of sensor data with precision guarantees, the precision constraint is partitioned and allocated to individual sensor nodes in a coordinated fashion. Our key idea is to differentiate the precisions of data collected from different sensor nodes to balance their energy consumption. Three factors affecting the lifetime of sensor nodes are identified: 1) the changing pattern of sensor readings; 2) the residual energy of sensor nodes; and 3) the communication cost between the sensor nodes and the base station. We analyze the optimal precision allocation in terms of network lifetime and propose an adaptive scheme that dynamically adjusts the precision constraints at the sensor nodes. The adaptive scheme also takes into consideration the topological relations among sensor nodes and the effect of in-network aggregation. Experimental results using real data traces show that the proposed scheme significantly improves network lifetime compared to existing methods.      

Timing-Based Mobile Sensor Localization in Wireless Sensor and Actor Networks

In this paper, localization problem in wireless sensor and actor networks (WSAN) is addressed. In WSAN, the performance of event detection and tracking highly depends on the exact location information of the events that must be reported along with the event features. Having precise location information of the sensor nodes, actors are able to execute actions more effectively in the region of detected events. In this context, the accurate localization of sensor nodes is essential with respect to the actors. Particularly, the problem becomes much more complicated when the sensor nodes as well as the anchor nodes (actors) are mobile. In order to localize the mobile sensor nodes relative to the actors, a novel Timing-based Mobile Sensor Localization (TMSL) algorithm is introduced. In TMSL, sensor nodes determine their distance from actors by using propagation time and speed of RF signal. In order to determine distance from the actors, actors actively broadcast reference beacons in a pattern of intervals adaptively defined according to the mobility of sensor nodes and the required level of localization accuracy. These reference beacons carry the interval numbers in which they were transmitted. The interval numbers are then used by the sensor nodes to calculate the start time of the beacons locally which is then used to determine the propagation time. TMSL does neither require nor assume any time synchronization among the sensor nodes or with the actors. Performance evaluations clearly show that TMSL is adaptive to velocity of mobile sensor and actor nodes and can be configured according to the required localization accuracy in order to avoid overhead raised due to high velocity.     

无线传感器网络节点的辅助式定位方法

节点定位是无线传感器网络的一个重要研究内容。针对传感器网络内所有节点物理位置都未知的情况，文中提出一种利用已知的外界参考信号源来对网络内传感器节点进行定位的方法，并建立了基于TDOA、TOA及AOA的定位估计模型。尽管参数测量有误差，但所提出的方法能够提供有效的位置信息及一定的精度，而且基于AOA的定位模型并不增加传感器节点的成本和复杂度。仿真实验结果表明，该方法能对节点进行有效的定位。     

分布式无线感知网络节点部署算法研究

在无线感知网络节点部署中,目标区域的覆盖率大小对信号检测的效果具有重要的意义,通过智能优化算法来提高区域覆盖率已成为当前无线感知网络节点部署领域的研究热点之一。为了提高分布式无线感知网络对目标区域内的重点区域的覆盖率和减少冗余感知节点的投放,论文提出了一种分布式无线感知网络节点部署算法。该算法首先通过随机部署满足连通性的少量感知节点后初次工作来定位和估计出重点区域,然后将估计出的重点区域融入到粒子群算法的目标函数和粒子更新方程中实现对感知节点的重新部署,从而更好的优化了重点区域的覆盖率和减少冗余感知节点数量。仿真结果表明,与标准粒子群算法及其他优化算法相比,论文所研究的算法有更高的覆盖率和更低的迭代次数。      

基于冗余节点休眠和分阶段唤醒策略的传感器网络三维覆盖控制方法

该文针对无线传感器网络中节点能量有限且密集布点时存在大量冗余节点的情况,提出了基于冗余节点休眠和分阶段唤醒策略的无线传感器网络3维覆盖控制方法。在3维待监测区域中随机配置大量传感器节点,达到高密度分布,使冗余节点处于休眠状态,等待活跃节点能量耗尽之后,分阶段唤醒休眠节点,直至整个传感器网络中所有节点的能量都耗尽为止。仿真结果表明,该方法提高了传感器网络的网络性能,且对相同的传感器节点数,分阶段唤醒策略优于不分阶段的唤醒策略,先使冗余节点休眠之后再唤醒方法的网络性能高于直接唤醒方法的网络性能。     

Exploiting edge capability for wireless sensor networking

As considerable progress is being made in wireless sensor networking, it is envisioned that sensor nodes will be on the cubic millimeter scale, posing stringent constraints on the processing, communication, and storage capabilities of sensor nodes. While it is important to continue pursuing novel algorithms and protocols to squeeze the most out of the existing design space (sensor nodes), it is equally important to explore a new design paradigm for future sensor networks to reduce the complexity burden on sensor nodes. We propose to exploit capabilities at the network edge (i.e., an edge-based approach). We overview existing approaches to this end and present a novel edge-based routing protocol, called BeamStar, as a case study. We show that exploiting edge capability provides a new dimension of freedom for wireless sensor networking, and is effective in relieving the processing, communication, and storage requirements of sensor nodes.     

无线传感器网络节点的设计

无线传感器网络是一种以无中心节点的全分布系统。通过随机投放的方式,众多传感器节点被密集部署于监控区域。这些传感器节点集成有传感器、数据处理单元和通信模块,它们通过无线信道相连,自组织地构成网络系统。传感器节点借助于其内置的形式多样的传感器,测量所在周边环境中的相关信号,传感器节点间具有良好的协作能力,通过局部的数据交换来完成全局任务。     

建筑物抗震性无线检测系统的设计

介绍了一种基于无线传感器网络技术的建筑物抗震性检测系统.首先,提出了以无线通信震动传感器形成一种可扩展的无线传感器网络的系统结构.然后,介绍在该系统中采用的无线震动传感器节点以及检测基站设备的设计.在本系统中,节点和基站设备所使用的近距离通信标准为802.15.4/ZigBee标准.     

一种新的无线传感器网络传输机制——RNTA算法的研究与仿真

针对无线传感器网络体积小与能量受限的特点,该文提出了一种新的传输机制RNTA算法,即将无线传感器网络中的部分冗余节点组成中继树,并利用该树作为网络内信息传输的代理,完成了信息从簇头到基站的传输,达到了节省正常节点和簇头能量的目的。仿真结果表明:该机制可以有效提高网络的生命周期。     

一种无线传感器网络异构分簇模型的簇头调度方案

将无线传感器网络划分成簇会有效利用系统资源,近来提出的基于异构分簇模型的无线传感器网络,是指网络中存在多种不同能力的节点,能力强的节点自动成为簇头,这种网络避免了复杂的簇头选举过程并有效降低了普通节点的硬件复杂性和成本。但是,固定簇头的方法会削弱系统的负载均衡以及健壮性。为了解决这个问题,提出了一种基于自适应退避策略的簇头调度方案,该方案通过适当增加冗余度实现传感节点的k覆盖,增强了网络的健壮性。同时,依赖于地理信息和剩余电池能量信息,簇头节点通过自主周期性睡眠来保证系统负载的均衡分配,延长网络生存期。     

Comparative Study of the Different Variants of the DV-Hop Based Node Localization Algorithms for Wireless Sensor Networks

Wireless Personal Communications - Node localization is one of the essential services where sensor nodes in the wireless sensor network collaborate to provide location information of sensor nodes...     

Delay-Constrained Optimal Data Aggregation in Hierarchical Wireless Sensor Networks

A lot of realistic applications with wireless sensor networks adopt hierarchical architecture in which sensor nodes are grouped into clusters, with each cluster relying on a gateway node for local data aggregation and long-distance radio transmission. Compared to normal sensor nodes, the gateway nodes, also called application nodes (ANs), are equipped with relatively powerful transceivers and have more energy. Nevertheless, since an AN is the main gateway for sensor nodes within its clusters, its energy may be depleted more quickly than normal sensor nodes. As such, it is important to find methods to save energy for ANs. This paper presents a Delay-Constrained Optimal Data Aggregation (DeCODA) framework that considers the unique feature of traffic patterns and information processing at ANs for energy saving. Mathematical models and analytical results are provided, and simulation studies are performed to verify the effectiveness of the DeCODA framework.     

A Green Clustering Protocol for Mobile Sensor Network Using Particle Swarm Optimization

Energy consumption of sensor nodes is one of the crucial issues in prolonging the lifetime of wireless sensor networks. One of the methods that can improve the utilization of sensor nodes batteries is the clustering method. In this paper, we propose a green clustering protocol for mobile sensor networks using particle swarm optimization (PSO) algorithm. We define a new fitness function that can optimize the energy consumption of the whole network and minimize the relative distance between cluster heads and their respective member nodes. We also take into account the mobility factor when defining the cluster membership, so that the sensor nodes can join the cluster that has the similar mobility pattern. The performance of the proposed protocol is compared with well-known clustering protocols developed for wireless sensor networks such as LEACH (low-energy adaptive clustering hierarchy) and protocols designed for sensor networks with mobile nodes called CM-IR (clustering mobility-invalid round). In addition, we also modify the improved version of LEACH called MLEACH-C, so that it is applicable to the mobile sensor nodes environment. Simulation results demonstrate that the proposed protocol using PSO algorithm can improve the energy consumption of the network, achieve better network lifetime, and increase the data delivered at the base station.     

一种新的无线传感器节点的连续参数功耗模型

为了估计传感器节点的能量开销,需要对节点功耗进行合理、准确的建模。然而,现有的节点功耗模型都没有很好地满足准确性这一要求。该文提出了一种新的基于连续参数功耗状态机的节点功耗模型,可用于任意类型传感器节点的功耗建模。该模型能够根据电源电压和工作频率等参数的变化对节点功耗进行更为准确的预测。通过对传感器节点中常用的ATmega128(L)微处理器进行实际建模并与独立的实测结果进行比较,可以发现该模型对活动状态功耗的预测误差小于1%,对空闲状态功耗的预测误差小于9.7%。该模型可用于替换传感器网络仿真工具的现有模型,为传感器节点的能量开销提供更为准确的预测结果。     

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.     

一种用于水声传感网的MAC层协议

针对分簇的水声传感网,提出了一种基于时分多址（TDMA）的MAC层协议——Cluster-TDMA。该协议主要由规划阶段和传输阶段组成。规划阶段,首先由网关节点规划能造成簇间干扰的子节点的传输,其次由各簇头节点分别规划本簇内其他子节点的传输;传输阶段,子节点根据规划表周期性地向簇头节点发送数据,这些数据最终汇聚到网关节点。该协议简单有效地解决了引起簇间干扰子结点的传输规划问题。C++仿真实验表明,该协议具有良好的吞吐率和能量效率性能。     

无线火灾监控系统在坑、地道式防护工程中的应用研究

针对目前我国坑、地道式防护工程火灾监测系统存在的问题,设计一种无线火灾监控系统,该系统由传感器节点、路由节点、网关节点以及PC机组成。介绍了该探测系统传感器节点和网关节点的硬件设计以及传感器节点、路由节点、网关节点的功能、流程等软件设计。该系统集监测、显示、报警、通信等多功能于一体,可以对目标区域进行远程监控,监测节点体积小,无需布线,移动、安装方便。     

Identifying Neighbor and Connectivity of Wireless Sensor Networks with Poisson Point Process

Identifying neighbor and connectivity are the fundamental requirements in wireless sensor networks. The sensor nodes are scattered randomly over the area of interest and their first step is to identify their immediate neighbors, i.e., the nodes with which they have direct wireless communication. On the other hand, connectivity ensures that sensor nodes can communicate with each other in order to aggregate sensing data hop by hop to the base stations (sink nodes). In this paper, we study identifying neighbor and connectivity in the context of wireless sensor networks, using Poisson point process theory.     

A Hybrid Key Predistribution Scheme for Sensor Networks Employing Spatial Retreats to Cope with Jamming Attacks

In order to provide security services in wireless sensor networks, a well-known task is to provide cryptographic keys to sensor nodes prior to deployment. It is difficult to assign secret keys for all pairs of sensor node when the number of nodes is large due to the large numbers of keys required and limited memory resources of sensor nodes. One possible solution is to randomly assign a few keys to sensor nodes and have nodes be able to connect to each other with some probability. This scheme has limitations in terms of the tradeoffs between connectivity and memory requirements. Recently, sensor deployment knowledge has been used to improve the level of connectivity while using lesser amounts of memory space. However, deployment based key predistribution schemes may cause a large number of nodes to be cryptographically isolated if nodes move after key pre-distribution. Mobility may be necessitated for reasons depending on applications or scenarios. In this paper, we consider mobility due to spatial retreat of nodes under jamming attacks as an example. Jamming attacks are easy and efficient means for disruption of the connectivity of sensors and thus the operation of a sensor network. One solution for mobile sensor nodes to overcome the impact of jamming is to perform spatial retreats by moving nodes away from jammed regions. Moved nodes may not be able to reconnect to the network because they do not have any shared secret with new neighbors at new locations if strict deployment knowledge based key predistribution is employed. In this paper, we propose a hybrid key predistribution scheme that supports spatial retreat strategies to cope with jamming attacks. Our scheme combines the properties of random and deployment knowledge based key predistribution schemes. In the presence of jamming attacks, our scheme provides high key connectivity (similar to deployment knowledge based schemes) while reducing the number of isolated nodes. We evaluate the performance of our scheme through simulations and analysis.     

无线传感器网络中联合功率 控制和速率调整

 无线传感器网络本质上是能量受限的,而且,传感器节点扮演着数据收集和数据转发的双重角色.本文提出了怎样分配传感器节点的功率用于转发其它节点的数据.在节点的转发功率分配比确定后,研究了采用价格作为一种方法,刺激节点与它到数据采集节点路径上的所有节点合作.通过把无线传感器网络中数据收集和传输抽象为一个网络效用最大化问题,通过采用对偶分解技术,提出了一种迭代价格与联合功率控制和速率调整的分布式算法.实验表明,该算法能提高系统的性能,同时降低功率的消耗.