一种近似秩排序的无线传感器网络分簇路由算法

为了延长无线传感器网络(WSN)的生存期,能量有效的路由算法至关重要。以分配网络中的业务负载为目标的传感器节点聚类是解决无线传感器网络能量均衡的有效方法。文中为无线传感器网络提出一种基于近似秩排序(ARO)的分层和基于距离的组合聚类方法,并使用多跳数据传输。仿真结果表明,ARO-WSN在能耗和网络生存期方面优于经典的LEACH算法、LEACH-C算法和K-means聚类算法,能有效地延长网络的生存期。     

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。     

能量高效的无线传感器网络时空查询处理算法

 在无线传感器网络环境中,用户经常提交的查询是时空查询,如“获得区域A在某个给定时间段内的感知数据”.由于传感器节点能量十分有限,因此,能量高效的时空查询处理是目前亟需解决的问题.首先指出了现有的时空查询处理算法能量消耗大的原因在于查询协调节点选择不合理.然后给出了理论上最优的查询协调节点的位置及其证明,并基于该理论提出了一类能量高效的传感器网络时空查询算法ECSTA.最后通过实验分析了节点密度和查询区域大小对算法能量消耗的影响.理论和实验结果表明ECSTA算法优于现有的STWin框架下的算法.     

基于位置感知的无线传感器网络聚类算法

针对以能量有效的方式收集传感器网络空间相关性数据的问题,本文提出了一种新的基于位置感知的无线传感器网络聚类算法。算法根据用户查询误差门限和基于位置信息的节点感知数据相异度矩阵,进行无监督数据挖掘,将监测区域划分成信息等价域。每个等价域选取城内当前剩余能量最大的节点作为簇头,网络通过移动代理收集簇头感知信息,从而减少了传输数据量,有效节省了网络能量。     

传感器网络中节点能量有效均衡的Top-k查询技术

无线传感器网络中top-k查询处理的节点能量高效以及实现各节点的能量消耗均衡,可以有效延长网络的生命周期。该文提出一种基于采样技术和节点空间相关性,来实现节点的能量均衡和高效的查询处理算法,称为能量均衡采样(,)近似top-k算法EBSTopk(,)。首先对传感器网络进行分区处理,利用区域内两两节点间的空间相关性对其建立线性回归预测模型和高斯预测模型;然后根据用户给定的相对误差界和置信水平1-建立节点高相关性预测准则;最后根据上述预测模型和准则,提出基于反复随机采样的能量均衡算法EBSTopk(,)-LR和EBSTopk(,)-MG。实验表明,所提出的EBSTopk(,)算法减少了无线传感器网络中的全局能量消耗,且在多次top-k查询后各节点的能量消耗达到均衡。     

基于D-S证据理论的组合数据融合算法

针对在无线传感器网络中传感器节点本身能量有限的特性,提出一种基于D-S证据理论的组合数据融合算法.先对传感器网络的当前值依据各组数据的标准差进行聚类,然后对每一类数据组,用D-S证据推理算法进行融合,将其结果看成一个虚拟传感器节点数据,最后通过计算马哈诺比斯距离得出虚拟节点数据向量的异常值,把它作为加权权重进行加权融合.仿真试验表明:该算法识别目标的可信度高于D-S推理法,且在计算复杂度上也有明显优势.     

矿井无线通信网络中LEACH协议的改进

针对矿井下无线传感器网络通信的特点,对LEACH协议分簇进行优化,并充分考虑能量和距离的因素,对簇头节点的选取进行优化,提出基于K-means++聚类的路由算法LEACH-KPPE,有效地改善了LEACH算法中簇头节点分布不均、能耗不均以及网络的稳定性等问题。仿真实验结果表明,该算法有效地改善了整个网络的能耗,提高了能量的利用率,有效延长了网络的生命周期。     

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.     

基于能量因素的无线传感器网络关键节点判定算法

无线传感器网络中关键节点的判定对网络抗毁性研究具有重要作用。考虑到节点能量受限,该文综合节点剩余生命期和节点移除导致的网络能耗值增加,提出一种将能量因素作为衡量节点重要程度的关键节点判定算法(CNDBE),解决了能量受限的无线传感器网络关键节点判定问题。实验结果表明,在对基于CNDBE,最短路径树算法(SPT)和能量感知的关键节点生成树算法(ENCAST)判定得到的关键节点进行保护时,CNDBE具有更强的网络抗毁性和更长的网络生命期。     

WSN中基于能量感知的最小跳数路由算法

无线传感器网络的拓扑往往由于节点死亡而发生变化。网络拓扑的重新构建加速了剩余传感器节点的死亡,缩短了网络的生存时间。针对无线传感器网络对网络生存时间的苛刻要求,提出了一种基于能量感知的最小跳数路由算法。建立路由时,该算法综合考虑了节点剩余能量和该节点潜在的转发能力。仿真结果显示,该算法在生存时间、存活节点数和吞吐量方面的性能要远优于LEACH算法和HEED算法。     

基于节点信任值的安全层次路由协议

由于无线传感器网络容易受到攻击,所以保证无线传感器在网络数据传输过程中的路由安全是必要的,文中提出一种基于节点信任值、节点度和距离的簇头选举算法,进行路由主干节点的可信选举,建立安全可信的层次路由。仿真结果表明,该算法可有效评估节点的信任值,解决了节点失效或被俘获所导致的层次路由安全问题。     

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.     

交通路灯监控系统的无线传感网链状路由算法

在交通路灯监控系统中为节省网络节点能耗和降低数据传输时延,提出一种无线传感网链状路由算法（CRASMS）。该算法根据节点和监控区域的信息将监控区域分成若干个簇区域,在每一个簇区域中依次循环选择某个节点为簇头节点,通过簇头节点和传感节点的通信建立簇内星型网络,最终簇头节点接收传感节点数据,采用数据融合算法降低数据冗余,通过簇头节点间的多跳路由将数据传输到Sink节点并将用户端的指令传输到被控节点。仿真结果表明：CRASMS算法保持了PEGASIS算法在节点能耗方面和LEACH算法在传输时延方面的优点,克服了PEGASIS 算法在传输时延方面和LEACH算法在节点能耗方面的不足,将网络平均节点能耗和平均数据传输时延保持在较低水平。在一定的条件下,CRASMS算法比LEACH和PEGASIS算法更优。     

NHRPA: a novel hierarchical routing protocol algorithm for wireless sensor networks

Considering severe resources constraints and security threat hierarchical routing protocol algorithm. The proposed routing of wireless sensor networks （WSN）, the article proposed a novel protocol algorithm can adopt suitable routing technology for the nodes according to the distance of nodes to the base station, density of nodes distribution, and residual energy of nodes. Comparing the proposed routing protocol algorithm with simple direction diffusion routing technology, cluster-based routing mechanisms, and simple hierarchical routing protocol algorithm through comprehensive analysis and simulation in terms of the energy usage, packet latency, and security in the presence of node protocol algorithm is more efficient for wireless sensor networks. compromise attacks, the results show that the proposed routing     

Optimal load balanced clustering in homogeneous wireless sensor networks

Balancing the load among sensor nodes is a major challenge for the long run operation of wireless sensor networks. When a sensor node becomes overloaded, the likelihood of higher latency, energy loss, and congestion becomes high. In this paper, we propose an optimal load balanced clustering for hierarchical cluster‐based wireless sensor networks. We formulate the network design problem as mixed‐integer linear programming. Our contribution is 3‐fold: First, we propose an energy aware cluster head selection model for optimal cluster head selection. Then we propose a delay and energy‐aware routing model for optimal inter‐cluster communication. Finally, we propose an equal traffic for energy efficient clustering for optimal load balanced clustering. We consider the worst case scenario, where all nodes have the same capability and where there are no ways to use mobile sinks or add some powerful nodes as gateways. Thus, our models perform load balancing and maximize network lifetime with no need for special node capabilities such as mobility or heterogeneity or pre‐deployment, which would greatly simplify the problem. We show that the proposed models not only increase network lifetime but also minimize latency between sensor nodes. Numerical results show that energy consumption can be effectively balanced among sensor nodes, and stability period can be greatly extended using our models.     

无线传感网中基于DPAM-MD算法的恶意节点识别研究

随着无线传感器网络的不断发展,恶意节点对其安全造成了极大的威胁。传统的基于信誉阈值的模型无法准确的识别亚攻击性等恶意节点,而且会出现低识别率和高误判率等问题。为了解决这些问题,引入了基于DPAM-MD算法的新型恶意节点识别方法,在传统信誉阈值判断模型的基础上,通过结合曼哈顿度量和DPAM算法识别出亚攻击性节点。算法中提出一种新型的基于密度的聚类算法,并结合簇间和簇内距离均衡化的目标函数,将所有的节点进行分类。该算法可以提高聚类质量,有效缩短聚类时间,提高了恶意节点识别的效率。经仿真实验结果验证,改进后的算法对识别特征不明显的恶意节点效果十分显著。     

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.     

Fuzzy-based unequal clustering protocol for underwater wireless sensor networks

Underwater wireless sensor network (UWSN) is a network made up of underwater sensor nodes, anchor nodes, surface sink nodes or surface stations, and the offshore sink node. Energy consumption, limited bandwidth, propagation delay, high bit error rate, stability, scalability, and network lifetime are the key challenges related to underwater wireless sensor networks. Clustering is used to mitigate these issues. In this work, fuzzy-based unequal clustering protocol (FBUCP) is proposed that does cluster head selection using fuzzy logic as it can deal with the uncertainties of the harsh atmosphere in the water. Cluster heads are selected using linguistic input variables like distance to the surface sink node, residual energy, and node density and linguistic output variables like cluster head advertisement radius and rank of underwater sensor nodes. Unequal clustering is used to have an unequal size of the cluster which deals with the problem of excess energy usage of the underwater sensor nodes near the surface sink node, called the hot spot problem. Data gathered by the cluster heads are transmitted to the surface sink node using neighboring cluster heads in the direction of the surface sink node. Dijkstra's shortest path algorithm is used for multi-hop and inter-cluster routing. The FBUCP is compared with the LEACH-UWSN, CDBR, and FBCA protocols for underwater wireless sensor networks. A comparative analysis shows that in first node dies, the FBUCP is up to 80% better, has 64.86% more network lifetime, has 91% more number of packets transmitted to the surface sink node, and is up to 58.81% more energy efficient than LEACH-UWSN, CDBR, and FBCA.     

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...