无线传感器网络模糊逻辑分簇路由协议

在无线传感器网络（Wireless Sensor Network,WSN）中,LEACH协议通过概率模型来选举簇头,由于没有考虑到传感器节点的分布情况和能量剩余等信息,可能会使得部分节点过早死亡.针对这一问题,提出基于模糊逻辑的分簇路由协议（DFLCP）.在预选簇头阶段,根据节点剩余能量等信息利用模糊逻辑计算出节点的竞争半径,使得簇头分布相对均匀;在簇头选举阶段,通过模糊逻辑确定节点成为簇头的概率.仿真结果表明：DFLCP协议可有效控制簇头节点的分布密度和簇的半径,均衡网络负载,延长节点平均生存时间.     

无线传感器网络中基于能量的成簇协议

无线传感器网络采用能量有效方式传输数据对于延长传感器网络寿命十分重要。LEACH是一种基于簇的协议,它采用本地簇头随机轮转机制将能量负载均匀分布到网络中的所有传感器节点,簇头节点将收集到数据进行融合后发送给基站。提出一种改进的方案,采用随机成簇算法让网络中传感器节点成簇,成簇的过程考虑传感器节点剩余能量和簇头与非簇头结点之间的距离。通过分析评价和仿真结果,说明新算法比LEACH更能有效利用能量且发送更多的数据。     

无线传感器网络的自组织成簇算法

异构传感器网络是一种能量有限且分布不均衡的网络,负载均衡和能量有效是此网络路由算法的一个挑战。现提出的自组织成簇算法能够有效增加传感器网络的稳定周期,算法基于传感器节点的剩余能量和通讯能耗选择适合的簇头节点。与经典的成簇算法LEACH和SET比较,本算法能够更好实现负载均衡,并极大地提高传感器网络的稳定周期。     

一种改进的基于时间竞争成簇的路由算法

为平衡无线传感器网络中的簇头负载并进一步降低多跳传输能耗,文中提出了一种改进的基于时间竞争成簇的路由算法。该算法通过限制近基站节点成簇入簇,以防止近基站节点成簇入簇的节能收益无法补偿成簇入簇能耗;利用基站广播公共信息和基于时间机制成簇,以减少节点基本信息交换能耗;通过候选簇头中继来平衡簇头负载。候选簇头的评价函数综合考虑了剩余能量和最优跳数的理想路径,以期在保持中继负载平衡的基础上尽量降低多跳能耗。仿真结果显示,该算法较LEACH和DEBUC算法延长了以30%节点死亡为网络失效的网络生存周期,表明该算法在降低节点能耗和平衡负载方面是有效的。     

基于自适应遗传算法的无线激光通信网络负载均衡成簇算法

由于无线激光通信网络吞吐量低、节点传输延时高和存在分组丢失率多等问题，提出基于自适应遗传算法的无线激光通信网络负载均衡成簇算法。利用AGCH算法对无线激光通信网络节点进行分组和成簇，从中取得簇头节点，构建资源调度模型，利用该模型对簇头节点中的资源进行分配调度，采用自适应遗传算法对建立的模型进行求解，以此提升无线激光通信网络负载均衡效果，实现无线激光通信网络负载均衡。实验结果表明，通过对该算法进行网络吞吐量测试、节点传输延时测试和分组丢失率测试，验证了该算法的有效性强、实用性高。     

无线传感器网络中一种能量有效的簇内通信方案

为了提高簇内通信的能耗均衡性,提出了一种能量有效的分簇无线传感器网络簇内空分通信方案——近簇头节点采用单跳传输,远簇头节点多跳传输,给出了空分通信方案的工程实现。仿真结果验证了空分混合通信方案在能量有效性和能耗均衡分配方面的优势。     

基于簇头间距均匀部署的LEACH协议改进算法

针对无线传感器网络中各节点能量消耗和簇头节点位置分布不均导致网络寿命下降的问题,在LEACH协议基础上提出一种改进算法。首先增加高剩余能量节点成为簇头的概率,其次设定备选簇头节点间最小距离,以降低簇内节点与簇头节点的通信能耗。通过理论分析和仿真实验,提出的算法能实现网络能耗均衡,有效延长网络的生存周期。     

基于电量均衡的无线传感器网络分簇算法

为了延长无线传感器网络的生命期,针对节点能耗分布不均匀的问题,提出一种电量均衡的分簇算法.该算法将节点剩余能量作为构建分簇结构的依据,对剩余能量较少的节点赋予一定的约束,使之成为普通节点,并使电量多的节点成为簇头节点,均衡网络电量负载,解决了网络中部分低电量节点担任骨干节点而导致能耗的问题,从而有效延长了网络的生命期.仿真实验证明了该算法的有效性.     

无线传感器网络簇间节能路由算法

针对基于分簇网络的无线传感器网络簇间路由协议,让簇首和Sink节点直接通信或通过簇首节点转发数据造成能耗不均,节点过早死亡的缺陷。文中提出一种基于网关节点模型的无线传感器网络簇间路由算法,通过簇头与网关节点、网关节点自身建立虚电路,制定存储转发路由,将数据转发给Sink节点。并引入延时等待机制,增强了簇间信息的融合度,此算法适用于大规模无线传感器网络,有良好的可扩展性。仿真表明在能量节省等性能上与传统簇间路由算法相较有较大提高。     

分簇无线传感器网络中的频谱感知方案

无线传感器网络中的节点众多,节点之间仅依靠频谱资源管理机制分配的频段进行数据传输会造成频谱资源紧张。针对这一问题,将认知无线电技术引入分簇的无线传感器网络,并且考虑分簇无线传感器网络节点的能量受限问题提出了一种节能的频谱感知方案。此方案首先让簇内的节点采取双门限能量检测的协作频谱感知方法,在满足目标检测概率和虚警概率的条件下,确定进行频谱感知的最少节点数,降低系统能耗。其次,通过选择合适的簇内节点进行频谱感知,使簇内节点的能耗均衡,簇的生命周期得到延长。     

Low-Energy Adaptive Unequal Clustering Protocol Using Fuzzy c-Means in Wireless Sensor Networks

Clustering technique in wireless sensor networks incorporate proper utilization of the limited energy resources of the deployed sensor nodes with the highest residual energy that can be used to gather data and send the information. However, the problem of unbalanced energy consumption exists in a particular cluster node in the network. Some more powerful nodes act as cluster head to control sensor network operation when the network is organized into heterogeneous clusters. It is important to assume that energy consumption of these cluster head nodes is balanced. Often the network is organized into clusters of equal size where cluster head nodes bear unequal loads. Instead in this paper, we proposed a new protocol low-energy adaptive unequal clustering protocol using Fuzzy c-means in wireless sensor networks (LAUCF), an unequal clustering size model for the organization of network based on Fuzzy c-means (FCM) clustering algorithm, which can lead to more uniform energy dissipation among the cluster head nodes, thus increasing network lifetime. A heuristic comparison between our proposed protocol LAUCF and other different energy-aware protocol including low energy adaptive clustering hierarchy (LEACH) has been carried out. Simulation result shows that our proposed heterogeneous clustering approach using FCM protocol is more effective in prolonging the network lifetime compared with LEACH and other protocol for long run.     

An unequal cluster-based routing scheme for multi-level heterogeneous wireless sensor networks

In wireless sensor networks (WSNs), clustering can significantly reduce energy dissipation of nodes, and also increase communication load of cluster heads. When multi-hop communication model is adopted in clustering, “energy hole” problem may occur due to unbalanced energy consumption among cluster heads. Recently, many multi-hop clustering protocols have been proposed to solve this problem. And the main way is using unequal clustering to control the size of clusters. However, many of these protocols are about homogeneous networks and few are about heterogeneous networks. In this paper, we present an unequal cluster-based routing scheme for WSNs with multi-level energy heterogeneity called UCR-H. The sensor field is partitioned into a number of equal-size rectangular units. We first calculate the number of clusters in each unit by balancing energy consumption among the cluster heads in different units. And then we find the optimal number of units by minimizing the total energy consumption of inter-cluster forwarding. Finally, the size of clusters in each unit is elaborately designed based on node’s energy level and the number of clusters in this unit. And a threshold is also designed to avoid excessive punishment to the nodes with higher energy level. Simulation results show that our scheme effectively mitigates the “energy hole” problem and achieves an obvious improvement on the network lifetime.     

基于动态分簇路由优化和分布式粒子滤波的传感器网络目标跟踪方法

针对无线传感器网络中节点通信能力及能量有限的情况,该文提出基于动态分簇路由优化和分布式粒子滤波的传感器网络目标跟踪方法。该方法以动态分簇的方式将监测区域内随机部署的传感器节点划分为若干个簇,并对簇内成员节点与簇首节点之间、簇首节点与基站之间的通信路由进行优化,确保网络能耗的均衡分布,在此基础上,被激活的簇内成员节点并行地执行分布式粒子滤波算法实现目标跟踪。仿真结果表明,该方法能有效地降低传感器网络中节点的总能耗,能在实现跟踪的同时保证目标跟踪的精度。     

Systematic energy-balanced cooperative transmission scheme in wireless sensor networks

Energy efficiency is a critical issue in wireless sensor networks(WSNs).In order to minimize energy consumption and balance energy dissipation throughout the whole network,a systematic energy-balanced cooperative transmission scheme in WSNs is proposed in this paper.This scheme studies energy efficiency in systematic view.For three main steps,namely nodes clustering,data aggregation and cooperative transmission,corresponding measures are put forward to save energy.These measures are well designed and tightly coupled to achieve optimal performance.A half-controlled dynamic clustering method is proposed to avoid concentrated distribution of cluster heads caused by selecting cluster heads randomly and to get high spatial correlation between cluster nodes.Based on clusters built,data aggregation,with the adoption of dynamic data compression,is performed by cluster heads to get better use of data correlation.Cooperative multiple input multiple output(CMIMO) with an energy-balanced cooperative cluster heads selection method is proposed to transmit data to sink node.System model of this scheme is also given in this paper.And simulation results show that,compared with other traditional schemes,the proposed scheme can efficiently distribute the energy dissipation evenly throughout the network and achieve higher energy efficiency,which leads to longer network lifetime span.By adopting orthogonal space time block code(STBC),the optimal number of the cooperative transmission nodes varying with the percentage of cluster heads is also concluded,which can help to improve energy efficiency by choosing the optimal number of cooperative nodes and making the most use of CMIMO.     

Energy-efficient collaborative target tracking algorithm using cost-reference particle filtering in wireless acoustic sensor networks

Target tracking is one of the most important applications of wireless sensor networks. Optimized computation and energy dissipation are critical requirements to save the limited resource of sensor nodes. A new robust and energy-efficient collaborative target tracking framework is proposed in this article. After a target is detected, only one active cluster is responsible for the tracking task at each time step. The tracking algorithm is distributed by passing the sensing and computation operations from one cluster to another. An event-driven cluster reforming scheme is also proposed for balancing energy consumption among nodes. Observations from three cluster members are chosen and a new class of particle filter termed cost-reference particle filter (CRPF) is introduced to estimate the target motion at the cluster head. This CRPF method is quite robust for wireless sensor network tracking applications because it drops the strong assumptions of knowing the probability distributions of the system process and observation noises. In simulation experiments, the performance of the proposed collaborative target tracking algorithm is evaluated by the metrics of tracking precision and network energy consumption.     

分簇无线传感器网络节能的信号源数目估计

In view of the characteristic of the energy constraint of the wireless sensor networks, a method is proposed for the estimation of the number of signal sources in wireless sensor networks, which is based on clustering and decision-level data fusion. And a new cluster head selection algorithm based upon nodes’ residual energy is proposed. In the method proposed in this paper, the first is to divide the sensor networks into clusters with each cluster independently working on the estimation of the number of signal sources so as to generate the final results. Secondly, the results from each cluster at the fusion center are fused to obtain the estimates of the number of signal sources. The simulation results demonstrate that the methods of estimating the number of signal sources and cluster head selection algorithm proposed in this paper can efficiently reduce energy consumption for network transmission, and increase network life on the premise that the reliability of the estimation is ensured.      

An energy efficient clustering routing algorithm for wireless sensor networks

~~An energy efficient clustering routing algorithm for wireless sensor networks1. Mainwaring A, Polastre J, Szewczyk R, et al. Wireless sensor networks for habitat monitoring. Proceedings of the ACM International Workshop on Wireless Sensor Networks and A…     

基于聚类的无线传感网络的合作MIMO传输方案

Wireless sensor network is becoming more and more popular in recent years, but energy-constrained characteristic of sensor nodes is one of the critical issues that we must consider in system design. In this paper, a cluster-based virtual V-BLAST transmission scheme is proposed to achieve energy savings for energy-constrained wireless sensor networks. In the proposed scheme, instead of using cluster member as cooperative nodes, multiple cluster heads cooperate to form virtual antenna array so that V-BLAST based virtual MIMO transmission can be implemented. Based on the communication energy consumption model, a way to optimize the parameters for the scheme is given. In addition, detailed simulation is performed to evaluate the performance of the proposed scheme for both densely and sparsely deployed sensor networks. Theoretical analysis and simulation results verify the energy efficiency of the proposed scheme.     

Energy Efficient Reservation-Based Cluster Head Selection in WSNs

Due to the type of applications, wireless sensor nodes must always be inexpensive and small. Hence, the presence of constraints such as the limitation of energy resource is inevitable. So far, several studies have been carried out in order to present solutions for the reduction of energy consumption. In the meantime, clustering is given prime significance as an efficient method, which means partitioning network into distinct areas and is a way for managing nodes communication. In clustering algorithms, although the continuous execution of clustering phase and dynamic cluster head selection lead to energy consumption parity, they cause considerable energy dissipation due to the need for message transmitting to set new clusters and cluster heads. In this paper, the effect of using reservation to reduce message transmitting and energy dissipation has been studied. Reservation is the mechanism by the aid of which the number of communicated messages for the regular execution of clustering phase and cluster head selection can be reduced. The results of analysis and simulation show that the proposed method has significant impact on energy dissipation reduction.     

A Tree-Based Data Collecting Network Structure for Wireless Sensor Networks

In a sensor network with a large number of densely populated sensor nodes, a single target of interest may be detected by multiple sensor nodes simultaneously. Data collected from the sensor nodes are usually highly correlated, and hence energy saving using in-network data fusion becomes possible. A traditional data fusion scheme starts with dividing the network into clusters, followed by electing a sensor node as cluster head in each cluster. A cluster head is responsible for collecting data from all its cluster members, performing data fusion on these data and transmitting the fused data to the base station. Assuming that a sensor node is only capable of handling a single node-to-node transmission at a time and each transmission takes T time-slots, a cluster head with n cluster members will take at least nT time-slots to collect data from all its cluster members. In this paper, a tree-based network structure and its formation algorithms are proposed. Simulation results show that the proposed network structure can greatly reduce the delay in data collection.