无线传感器网络中的最优感知节点分布及分布优化算法

无线传感器网络中，感知节点的合理分布以及网络拓扑的动态调整对于更加有效地进行信息收集以及提高网络的生存期限都具有重要的作用。为此，针对传感器网络的初始规划提出了一种基于遗传算法的最优分布。仿真结果表明，算法能够针对特定的目标区域获得较好的节点分布。在最佳分布的基础上，结合传感器网络的拓扑管理和节点定位，引入了一种有效的传感器网络拓扑和节点分布优化方法，为传感器网络的拓扑性能管理提供了有效的算法保证。     

一种基于有向感知模型的传感器节点覆盖算法

覆盖控制作为无线传感器网络中的一个基本问题,反映了传感器网络所能提供的“感知”服务质量.优化传感器网络覆盖对于合理分配网络的空间资源,更好地完成环境感知、信息获取任务以及提高网络生存能力都具有重要的意义.针对无线传感器网络方向个数固定的有向感知模型提出一种覆盖增强算法,采用复杂网络社团结构算法划分对网络进行节点子集划分,重新调整节点的感知方向,增强网络的覆盖率,同时有效降低了算法的时间复杂度.     

一种混沌萤火虫算法的WSN节点分布优化研究

针对无线传感器网络节点分布优化问题,提出了一种有效的混沌萤火虫优化算法。在保证节点相互连通的前提下,建立了无线传感器网络对目标区域覆盖的数学模型,并将节点分布优化问题转换为求解函数最大值问题;利用萤火虫算法优越的寻优能力来实现最优的网络节点分布,并引入立方映射混沌算子来提高算法的局部搜索能力和保持种群的多样性。通过标准函数测试与无线网络覆盖优化仿真对所提算法进行了验证,结果表明:与其他算法相比,所提算法能够较好地跳出局部最优的束缚,具有优化效果佳、稳定性好、鲁棒性强的优点,能够满足无线传感器网络节点分布优化的要求。     

无线传感器网络自适应目标跟踪节点调度算法

在无线传感器网络中,设计合理的节点调度算法是提高网络感知能力、降低系统能耗的关键。在分析节点能耗模型的基础上,针对移动目标跟踪型网络应用,提出一种高能效的无线传感器网络自适应节点调度算法ANSTT。该算法根据节点对移动目标的感知能力,以及节点的相对剩余能量水平,自动调整节点工作模式。仿真实验表明,ANSTT算法在维持低感知延时、高目标感知率的同时,可有效降低系统能耗,延长网络寿命。     

无线传感器网络中的分簇算法

分簇算法是无线传感器网络中实施分层路由所采用的重要方法,尤其是传感器节点受到能量和带宽的严重制约。如何合理、有效地利用分簇算法使得网络中节点的能量分布趋于一致,从而延长网络的生命周期,提高系统的整体性能指标,成为当前无线传感器网络研究领域内的热点问题之一。本文从能量有效性的角度出发,对最新的分簇算法进行研究与分析,指出如何根据无线传感器网络不同的分布区域、应用场景和多样的无线环境,生成性能优越的分簇算法。     

无线传感器网络中基于空间相关性的移动代理路由算法

资源受限的传感器节点密集分布在无线传感器网络监控区域,sink节点通过收集节点间观测信息对监控区域内发生的事件进行感知.本文提出SCMAR(Spatial Correlation-based Mobile Agent Routing)路由算法,在移动代理架构内,利用节点观测数据的空间相关性以能量有效的方式对感知事件进行...     

基于改进PSO的WMSNs覆盖增强算法

对无线多媒体传感器网络(WMSNs)的覆盖增强问题进行了研究.在WMSNs网络中,视频、图像节点的视角范围有限,只能监控周围的部分区域.由于节点数量众多、部署方式受限等原因,网络中往往存在大量的监测重叠与监控盲区,需要对各节点的感知方向进行优化,以提高网络的监控质量.文中基于有向感知模型,提出了一种覆盖增强算法MCE.MCE对各节点的感知方向进行调整,并使用了改进的PSO算法来计算求解.仿真实验表明,MCE算法能够有效地提高网络的覆盖率.     

三维水下传感器网络覆盖优化算法

针对三维水下传感器网络模型,对水下传感器网络的覆盖优化问题进行了描述,提出利用虚拟势场算法CAT（coverage-enhancing algorithm for three-dimensional sensor networks）调整水下传感器节点与浮标节点间缆绳的距离,逐渐消除网络中的感知重叠区域和覆盖盲区,进而实现整个水下传感器网络覆盖增强.在仿真实验中,通过CAT算法与ETG算法的比较,验证了CAT算法的有效性.     

面向目标跟踪的传感器网络布局优化及保护策略

本文以目标跟踪为应用背景,改进了已有传感器感知模型和虚拟力方法,提出了一种新的传感器网络布局优化策略,该策略首先计算传感器与目标、热点区域、障碍物和其他传感器之间的虚拟力,为各传感器寻找受力平衡点,并将其作为该传感器的新位置,从而优化网络布局优化．实验证明,该策略可有效改善传感器网络覆盖率和目标探测概率．同时,本文根据各传感器获取的信息量,提出了涉及目标的传感器网络节点重要性排序算法,以及根据节点重要性进行传感器网络保护的策略。     

基于PSO的无线多媒体传感器网络覆盖增强算法

在无线多媒体传感器网络(Wireless Multimedia Sensor Networks,WMSNs)中,由于节点部署的不合理,往往存在较多的监控盲区,影响了网络的服务质量。为了提高网络的覆盖率,在有向感知模型基础的基础上,提出了一种基于粒子群算法的WMSNs覆盖增强算法PSOCE。PSOCE算法以网络覆盖率为优化目标,以粒子群算法为计算工具,同时对节点的位置与主感知方向进行调整。仿真试验表明,PSOCE算法能够有效地改进WMSNs的覆盖质量,网络的覆盖率能提高6%～12%。     

无线传感器网络延时测量数据的信息熵与不确定性

无线传感器网络的时间同步是无线传感器网络的一个重要的研究方向.本文利用时钟偏移量误差的规律性,提出基于指数时延的无线传感器网络时钟同步算法.在DMTS算法的基础上引入指数时延得到了发送者的同步模型.针对无线传感器网络延迟测量数据处理中掺杂的主观因素不能准确反映客观现实的问题,采用最大熵方法,根据测量数据求取被测量的概率...     

A distributed reinforcement learning based sensor node scheduling algorithm for coverage and connectivity maintenance in wireless sensor network

The fundamental challenge for randomly deployed resource-constrained wireless sensor network is to enhance the network lifetime without compromising its performance metrics such as coverage rate and network connectivity. One way is to schedule the activities of sensor nodes and form scheduling rounds autonomously in such a way that each spatial point is covered by at least one sensor node and there must be at least one communication path from the sensor nodes to base station. This autonomous activity scheduling of the sensor nodes can be efficiently done with Reinforcement Learning (RL), a technique of machine learning because it does not require prior environment modeling. In this paper, a Nash Q-Learning based node scheduling algorithm for coverage and connectivity maintenance (CCM-RL) is proposed where each node autonomously learns its optimal action (active/hibernate/sleep/customize the sensing range) to maximize the coverage rate and maintain network connectivity. The learning algorithm resides inside each sensor node. The main objective of this algorithm is to enable the sensor nodes to learn their optimal action so that the total number of activated nodes in each scheduling round becomes minimum and preserves the criteria of coverage rate and network connectivity. The comparison of CCM-RL protocol with other protocols proves its accuracy and reliability. The simulative comparison shows that CCM-RL performs better in terms of an average number of active sensor nodes in one scheduling round, coverage rate, and energy consumption.

     

Distributed EM algorithms for density estimation and clustering in sensor networks

The paper considers the problem of density estimation and clustering in distributed sensor networks. It is assumed that each node in the network senses an environment that can be described as a mixture of some elementary conditions. The measurements are thus statistically modeled with a mixture of Gaussians, where each Gaussian component corresponds to one of the elementary conditions. The paper presents a distributed expectation-maximization (EM) algorithm for estimating the Gaussian components, which are common to the environment and sensor network as a whole, as well as the mixing probabilities that may vary from node to node. The algorithm produces an estimate (in terms of a Gaussian mixture approximation) of the density of the sensor data without requiring the data to be transmitted to and processed at a central location. Alternatively, the algorithm can be viewed as a distributed processing strategy for clustering the sensor data into components corresponding to predominant environmental features sensed by the network. The convergence of the distributed EM algorithm is investigated, and simulations demonstrate the potential of this approach to sensor network data analysis.     

Optimal placement and routing strategies for resilient two‐tiered sensor networks

In hierarchical sensor networks using relay nodes, sensor nodes are arranged in clusters and higher powered relay nodes can be used as cluster heads. The lifetime of such a network is determined primarily by the lifetime of the relay nodes. In this paper, we propose two new integer linear programs (ILPs) formulations for optimal data gathering, which maximize the lifetime of the upper tier relay node network. Unlike most previous approaches considered in the literature, our formulations can generate optimal solutions under the non‐flow‐splitting model. Experimental results demonstrate that our approach can significantly extend network lifetime, compared to traditional routing schemes, for the non‐flow‐splitting model. The lifetime can be further enhanced by periodic updates of the routing strategy based on the residual energy at each relay node. The proposed rescheduling scheme can be used to handle single or multiple relay node failures. We have also presented a very simple and straightforward algorithm for the placement of relay nodes. The placement algorithm guarantees that all the sensor nodes can communicate with at least one relay node and that the relay node network is at least 2‐connected. This means that failure of a single relay node will not disconnect the network, and data may be routed around the failed node. The worst case performance of the placement algorithm is bounded by a constant with respect to any optimum placement algorithm. Copyright © 2008 John Wiley & Sons, Ltd.     

具有路径能耗优化特性的WSN无标度容错拓扑控制算法

针对数据传输型的大规模无线传感网络中路径能量损耗问题,建立在多跳模式下的网络路径能耗优化模型,得出可以使网络通信能耗最小的节点度取值规律。依据节点度的最优取值,通过控制网络平均节点度的适应度模型来构建网络拓扑,提出一种具有路径能耗优化特性的无标度容错拓扑控制算法EETA(energy efficiency topology algorithm)。动态性能分析表明,由该算法生成的网络拓扑,其节点的度分布服从幂律,具有无标度拓扑的强容错能力。仿真实验结果显示,该算法同时也降低了网络路径能量消耗,具有路径节能性。     

Adaptation of a routing algorithm in wireless video sensor network for disaster scenarios using JPEG 2000

In this work we will develop an extension of one of existing routing algorithm in wireless sensor network. This new adaptation will permit the sensor node to save more energy and transmit images in wireless mode. This situation will be strategic and helpful especially in disaster scenario, where groups of rescuers must be on site to accomplish emergency tasks; therefore it’s very important and necessary to establish a wireless communication in real time between individuals or groups. The nature of wireless video sensor network makes it suitable to be used in the context of emergencies because introducing a video give more information in precise time and this is very advantageous when the existing infrastructure is down or severely overloaded. In emergencies the network topology may change rapidly and randomly. The increasing mobility of terminals makes them progressively dependent on their autonomy from the power source. This is illustrated by introducing many mobility models and using many scenarios of mobility in emergency situation, where image transmission via sensor node is used. Low complexity algorithm in image processing in order to reduce time transfer of selected data by this way allows saving energy. Efficiency in emergency scenario is the main objective of this work, achieved by the combination of three strategies: low-power mode algorithm, a power-aware routing strategy and compression technique in image processing used in sensor node. A selected set of simulations studies and real test bed on sensor node platform (Telos-B) indicate a reduction in energy consumption and a significant increase in node lifetime whereas network performance is not affected significantly. This is the big interest of our work in emergency situation, by increasing life time of node, individual can communicate longer and give more chance to rescuers to find them.     

A new algorithm for cluster head selection in LEACH protocol for wireless sensor networks

In wireless sensor network, a large number of sensor nodes are distributed to cover a certain area. Sensor node is little in size with restricted processing power, memory, and limited battery life. Because of restricted battery power, wireless sensor network needs to broaden the system lifetime by reducing the energy consumption. A clustering‐based protocols adapt the use of energy by giving a balance to all nodes to become a cluster head. In this paper, we concentrate on a recent hierarchical routing protocols, which are depending on LEACH protocol to enhance its performance and increase the lifetime of wireless sensor network. So our enhanced protocol called Node Ranked–LEACH is proposed. Our proposed protocol improves the total network lifetime based on node rank algorithm. Node rank algorithm depends on both path cost and number of links between nodes to select the cluster head of each cluster. This enhancement reflects the real weight of specific node to success and can be represented as a cluster head. The proposed algorithm overcomes the random process selection, which leads to unexpected fail for some cluster heads in other LEACH versions, and it gives a good performance in the network lifetime and energy consumption comparing with previous version of LEACH protocols.     

基于改进DV-Hop的无线传感器网络节点定位算法

针对DV-Hop距算法定位误差大的难题,提出一种改进离估计误差,并利用DV-Hop的传感器节点定位算法。首先修正知节点与信标节DV-Hop算法对节点进行定位;然后对进V-Hop算法定位误差行校正,最后在Matlab 2012平台上对算法性能进行仿真分析。仿真结果表明,本文算法可以较好地克服DV-Hop算法存在的不足,提高了传感器节点的定位精度。