无线传感器网络中带复杂联盟的自适应任务分配算法

针对无线传感器网络任务调度的实时性及节点计算及能量受限的特点,根据任务截止期赋予任务优先级,优先考虑高优先级任务,设计了一个无线传感器网络中带复杂联盟的自适应任务分配算法。为尽最大努力确保任务在截止期前完成,对截止期较为紧迫的任务采用历史信息生成历史联盟,并执行快速子任务分配算法;而对截止期较为宽裕的任务,在满足任务截止期约束条件下,以节点能耗和网络能量分布平衡为优化目标,采用矩阵的二进制编码形式,设计了一种离散粒子群优化算法以并行生成联盟,并执行基于负载和能量平衡的子任务分配算法。仿真实验结果表明所构造的自适应算法是有效的,在局部求解与全局探索之间能够取得较好的平衡,并能够在较短的时间内取得满意解。     

无线传感器网络任务分配动态联盟模型与算法研究

为了延长网络生命周期,减少网络能量消耗和均衡网络负载,引入了动态联盟思想,构造了无线传感器网络任务分配的动态联盟模型,继而提出了一种基于离散粒子群优化的任务分配算法.该算法根据任务总完成时间、能量损耗以及网络负载状况,建立代价函数,结合粒子群优化算法,实现优化任务分配策略.引入了变异算子,在很好地保持了种群的多样性的同时提高了算法的全局搜索能力.仿真实验结果表明了该分配算法在局部求解与全局探索之间取得了较好的平衡,能有效减少无线传感器网络的计算时间和网络能耗,并有效地均衡网络负载.     

Mobile anchor assisted particle swarm optimization (PSO) based localization algorithms for wireless sensor networks

Node localization is essential to wireless sensor networks (WSN) and its applications. In this paper, we propose a particle swarm optimization (PSO) based localization algorithm (PLA) for WSNs with one or more mobile anchors. In PLA, each mobile anchor broadcasts beacons periodically, and sensor nodes locate themselves upon the receipt of multiple such messages. PLA does not require anchors to move along an optimized or a pre‐determined path. This property makes it suitable for WSN applications in which data‐collection and network management are undertaken by mobile data sinks with known locations. To the best of our knowledge, this is the first time that PSO is used in range‐free localization in a WSN with mobile anchors. We further derive the upper bound on the localization error using Centroid method and PLA. Simulation results show that PLA can achieve high performance in various scenarios. Copyright © 2011 John Wiley & Sons, Ltd.     

无线传感器网络中Robust Position定位算法的改进

首先深入分析了两种典型的分布式的节点定位算法，并从定位精度及能量消耗两个方面给出了定量分析结果。在此基础上提出了改进的定位算法，BB_RP算法。通过仿真试验，在定位精度和能量消耗两个方面与原有算法进行定量的分析比较。结果表明，BB_RP算法虽然在定位精度略低于原有的算法，但是在能量消耗和覆盖速度两个指标上有了较大的提高，使得无线传感器网络的生命周期延长。     

Energy saving proactive neighbor discovery algorithm in mobile low-duty-cycle wireless sensor network

Mobile low-duty-cycle wireless sensor network is a new kind of wireless multi-hop network,which is self-organized by a large number of nodes that have mobile ability and are able to get into sleep for a long time.Such networks have wide application prospects in national defense,industry,agriculture and other fields that need long term monitoring in severe environments.However,the movement and the sleeping features of nodes lead to constantly change of network topology,which makes the nodes difficult to discover their neighbors quickly.Therefore,the nodes cannot achieve optimal distribution decisions.In order to solve this problem,a new proactive neighbor discovery algorithm was proposed.This algorithm made the nodes in the network take the initiative to find their neighbors when they woke up,and avoided the delay caused by long time waiting in the traditional passive neighbor discovery.In addition,by predicting the movement speed and distance of neighbors,the neighbor set at the next moment can be quickly determined,which can further reduce the delay and obtain more accurate neighbor discovery results.Theoretical analysis and experimental results show that compared with the existing algorithms,the algorithm can find all the neighbors in MLDC-WSN with less energy consumption and lower delay.     

Target tracking by lightweight blind particle filter in wireless sensor networks

For realizing robust target tracking with wireless sensor networks in the circumstance where the propagation parameters of the characteristic signal emitted by the target are unknown, a novel tracking algorithm under the particle filter framework is proposed. We propose a scheme to realize particle weight calculation without the prior knowledge about the propagation parameters of the target's characteristic signal. With the use of the monotonic relationship of the distance and the received signal strength, we define the signal characteristic sequence and particle distance sequence and utilize the modified sequence distance between the signal characteristic sequence and the particle distance sequence as the criterion to calculate the particle weight blindly with simple lightweight operations. Simulation results demonstrate the effectiveness of the proposed algorithm. Copyright © 2011 John Wiley & Sons, Ltd.     

Dual‐mode multiple‐target tracking in wireless sensor networks based on sensor grouping and maximum likelihood estimation

The problem of tracking multiple mobile targets, using a wireless sensor network, is investigated in this paper. We propose a new sensor grouping algorithm, based on the maximum sensor separation distances (G‐MSSD), for estimating the location of multiple indistinguishable targets, either jointly or individually, depending on the distances between the generated groups. The joint tracking algorithm is formulated as a maximum likelihood (ML) estimator and solved through a modified version of the well‐known Gauss‐Newton (MGN) iterative method. We propose two candidate initial guesses for MGN based on G‐MSSD in joint tracking mode, while for the individual mode, the information of each group is used to estimate the location of only the corresponding target. The Cramer‐Rao lower bound (CRLB) for the variance of the proposed ML estimator is derived, and the potential conditions for reducing the CRLB are presented. Since tracking efficiency is affected by poor estimates, we present two criteria to evaluate the quality of estimates and detect the poor ones. An approach is also proposed for correcting the poor estimates, based on additional initial guesses. We demonstrate the effectiveness and accuracy of our proposed dual‐mode algorithm via simulation results and compare our results with the Multi‐Resolution search algorithm.     

基于无线传感器网络能耗系统的研究

节能已经成为无线传感器网络研究的核心部分。该文研究了无线传感器网络拓扑结构的邻近节点数对网络能耗的影响,主要采用动态电压调节技术(DVS)来降低无线传感器网络中节点的能耗。动态电压调节主要通过减少门等效电容、供电电压以及降低转换因子、时钟频率来达到降低动态能耗的目的,其中,降低供电电压节能效果最佳。与其他方法相比,动态电压调节降低能耗更加明显、效率更高。通过在CC2430节点芯片上测试验证,通过改变其分频比,得出了功耗和频率的近似线性关系。     

无线传感器网络路由中的能量预测及算法实现

基于无线传感器网络中路由协议高效合理利用能量的要求,提出一种基于剩余能量预测的地理位置路由(EPGR,energy prediction and geographical routing)算法。算法通过建立传感器网络节点运作模型,及相邻节点剩余能量预测机制,优化路由选择。仿真和分析表明,EPGR算法能够有效地优化数据传输路径,均衡传感器网络节点的能量消耗,延长网络寿命。     

基于热释电无线传感网络的人体目标识别系统

文章主要分析了热释电红外传感器搭建无线传感的网络,同时讲解了热释电红外传感器的主要特征、原理以及实现到人体目标识别功能的可行性,望能为有关人员提供到一定的参考和帮助.     

单跳节点间传输距离对无线传感器网络性能影响的评估

在无线传感器网络中对传输距离与传输能量及传输速率的关系进行了研究。传统的工作对该关系的认识并不准确,而这是考虑网络各性能指标的基础。首先介绍了实验所用到的无线传感器网络节点,实验的环境及实验的设计;然后通过实验测量得到在不同传输距离上的报文丢失率,并对其进行拟合得到传输距离与报文丢失率的关系;最后在该关系的基础上考虑了报文的重传,进一步研究了传输距离对传输能量及传输速率的影响。主要贡献是在Imote2型节点平台上定量地给出了单跳节点间传输距离对无线传感器网络性能影响的评估。     

基于PSO-BP算法的无线传感器网络定位优化

在研究现有定位算法的基础上,针对基于接收信号强度指示(RSSI)定位模型中的参数易受环境影响等问题,提出了一种新型的粒子群优化(PSO)算法与后向传播(BP)神经网络相结合的算法.BP网络算法权值的修正依赖于非线性梯度值,易形成局部极值,同时学习次数较多,需先通过粒子群算法进行优化.为了提高定位精度,首先采用速度常量法滤波处理,然后通过改进的混合优化算法对BP神经网络初始权值和阈值进行优化,并分析算法的性能.试验中隐层节点个数采用试错法,从12到19变化,以确定合适数目.实验结果表明,与一般加权算法和传统BP算法相比,改进的混合优化算法可大幅改善测距误差对定位误差的影响,同时可使25 m内最小定位误差小于0.27 m.     

Distributed estimation of sensors position in underwater wireless sensor network

In this paper, a localisation method for determining the position of fixed sensor nodes in an underwater wireless sensor network (UWSN) is introduced. In this simple and range-free scheme, the node localisation is achieved by utilising an autonomous underwater vehicle (AUV) that transverses through the network deployment area, and that periodically emits a message block via four directional acoustic beams. A message block contains the actual known AUV position as well as a directional dependent marker that allows a node to identify the respective transmit beam. The beams form a fixed angle with the AUV body. If a node passively receives message blocks, it could calculate the arithmetic mean of the coordinates existing in each messages sequence, to find coordinates at two different time instants via two different successive beams. The node position can be derived from the two computed positions of the AUV. The major advantage of the proposed localisation algorithm is that it is silent, which leads to energy efficiency for sensor nodes. The proposed method does not require any synchronisation among the nodes owing to being silent. Simulation results, using MATLAB, demonstrated that the proposed method had better performance than other similar AUV-based localisation methods in terms of the rates of well-localised sensor nodes and positional root mean square error.     

基于无线传感器网络的K均值算法研究

传统无线传感网一般由大量密集的传感器节点构成,存在节点计算能力、能源和带宽都非常有限的缺点,为了有效节能、延长网络寿命,介绍了基于聚类的K均值算法.该算法通过生成的簇头节点散播到网络的各个区域中,减少了每个区域内通信的能耗和可能会出现的一般节点过早死亡的情况,从而避免了网络对该区城提早失去监控.实验证明,该算法对各节点...     

Static wireless sensor networks deployment using an improved binary PSO

A major issue in designing wireless sensor networks is the deployment problem. Indeed, many performances of the sensor network, such as coverage, are determined by the number and locations of deployed sensors. This paper reviews existing deterministic deployment strategies and devises a modified binary particle swarm optimization, which adopts a new position updating procedure for a faster convergence and exploits the abandonment concept to avoid some drawbacks such as premature convergence. The devised approach combines, in a meaningful way, the characteristics of the binary particle swarm optimization with the wireless sensor networks deployment requirements in order to devise a lightweight and efficient sensor placement algorithm. The effectiveness and efficiency of the proposed approach are evaluated through extensive simulations. The obtained results show that the proposed algorithm outperforms the state‐of‐the‐art approaches, especially in the case of preferential coverage. Copyright © 2015 John Wiley & Sons, Ltd.     

基于粒子群优化和M-H采样粒子滤波的传感器网络目标跟踪方法

针对实际应用条件下传感器节点的观测数据与目标动态参数间呈现为非线性关系的特性,提出了一种基于粒子群优化和M-H抽样粒子滤波的传感器网络目标跟踪方法。该方法采用分布式结构,在动态网络拓扑结构下,由粒子群优化和M-H抽样技术实现滤波中的重抽样过程,抑制粒子退化现象,并通过粒子间共享历史信息,降低单个粒子历史状态间的相关性使各粒子能快速收敛至最优分布,从而实现高精度的目标跟踪效果。仿真结果表明,相比现有的基于信息粒子滤波和并行粒子滤波技术的传感器网络目标跟踪方法,所提出的方法能降低网络总能耗,同时保证目标跟踪的精度。     

基于能量均衡的无线传感器网络路由算法

为了提高无线传感器网络的生存时间,针对当前LEACH算法存在的能量不均衡难题,提出一种能量均衡的无线传感器网络节点路由算法。首先将监测区域看成以基站为中心的扇形区域,并将扇形区域分割成不同大小的弧形方块,每个弧形方块中的节点组成一个簇,根据节点剩余能量产生簇头,然后采用单跳和多跳相结合的簇间通信机制,最后采用仿真实验测试算法的性能。结果表明,本文算法有效提高了网络的能量利用率,能够实现节点之间的能耗均衡,使无线传感器的网络生存时间得到延长,适用于对网络生命周期要求较高的应用。     

基于节能策略的无线传感器网络MAC协议

由于无线传感器网络的特殊性,针对其节能问题的媒体访问控制(MAC)协议研究越来越受到人们的关注.首先分析了无线传感器网络中能源损耗的原因,接着对近年来典型的基于节能策略的无线传感器网络MAC协议进行了分析总结,并综合其它性能指标比较了协议性能,最后提出了一些未来的研究方向.     

LEACH算法的改进分簇模型在无线传感器网络中的研究

无线传感器网络是将传感器通过无线通信的方式,对网络信息进行处理及传递.网络综合了传感器技术、嵌入式计算技术、分布式信息处理技术和通信技术,可以实时监测、感知和采集网络分布区域内的各种对象的信息,并对这些信息进行处理,传送给所需用户.LEACH算法是一种典型的层次路由算法,该算法提出了低功耗持续运行的模型.但LEACH算...     

AD HOC技术在无线传感器网络中的应用

在介绍两种典型的移动自组织网络中路由算法的基础上，讨论将移动自组织网络路由算法直接运用于无线传感器网络的可行性。从路由性能以及能量的角度进行分析，结果显示，传感器网络以数据为中心的特点约束了移动自组织网络路由算法的直接应用。进一步提出了基于聚类算法的路由，将聚类算法作为移动自组织网络应用的桥梁。仿真结果也显示了基于聚类算法的路由的优越性。