WSN中负载平衡的LEACH通信协议研究

LEACH协议是无线传感器网络中被广泛应用的聚类协议,但它存在负载不均衡的缺陷.通过分析LEACH协议聚类中节点的能耗情况,建立节点的能耗模型,找出了聚类之间以及节点之间负载不均衡的原因.基于原有协议,提出了一种新的LB-LEACH通信协议.使用OMNET 进行仿真实验,实验结果表明,新协议能够使聚类间的负载更加均衡,减少节点的过早死亡,延长整个网络的寿命.     

基于K-means的无线传感器网络分簇算法研究

提出一种基于K-均值聚类的无线传感器网络分簇算法。从K-均值聚类算法中要解决的合理聚类数的确定、初始聚类中心的选择以及聚类性能对目标函数的依赖这三个问题入手,运用K-均值聚类算法来实现无线传感器网络分簇。仿真与性能分析结果表明,基于K-均值聚类的无线传感器网络分簇算法既能节省节点能量、延长网络生命,又能改善网络中的能耗均衡,并保证簇首分布的均匀性。     

跨层多跳的LEACH路由协议研究

聚类算法是无线传感器网络中减少能量消耗的一种很重要的方法,它能够增强网络的扩展性和延长网络的生存时间。LEACH协议是无线传感器网络中被广泛应用的聚类协议,但它存在负载不均衡的缺陷。在原有协议的基础上提出了一种改进的通信协议：跨层多跳的LEACH路由协议（CM-LEACH）,通过跨层多跳的方式减少了节点能量的消耗。仿真实验结果表明,新协议能够使聚类间的负载更加均衡,减少节点的过早死亡,延长整个网络的寿命。     

WSN中能耗均衡的自组织多跳聚类协议研究

针对LEACH协议能耗不均和节点过早死亡的缺陷,提出了能耗均衡的自组织多跳聚类协议。该协议通过在竞争簇首过程中加入能量参量来均衡节点能耗,并完全采用节点自组织的方式构建簇首间的多跳网络,减小了协议开销、避免了外围节点的早死,比传统聚类协议更能适应大规模的传感器网络。仿真实验证明,与已有聚类协议相比,自组织多跳聚类协议能够均衡网络负载,延长网络寿命。     

基于改进能量分区控制传感网络通信优化仿真

当前无线传感网络中的节点分布可能存在极不均匀现象,造成节点能量消耗不集中,远离Sink节点的簇头能耗较大,破坏传感网络覆盖拓扑结构,导致网络的能量不均衡现象,通信受阻.为解决上述问题,提出了一种基于模糊c均值节点能量分区控制算法.利用混沌序列的均匀遍历特性和差分进化算法的高效全局搜索能力,对传感网络内的节点能量属性进行分类搜索,利用Logistics混沌映射对头节点进行优化分区操作,把混沌扰动量引入到节点能量分区当中,完成最优能量节点的选择,优化通信过程.仿真结果证明,算法对无线传感网络最优节点的聚类性能效果提高明显,通信效率提高25％以上.具有很好的实际应用性能和效果.     

一种分布式高效节能的自适应传感器网络聚类协议

现有的传感器网络拓扑协议未全面考虑节点位置、剩余能量等因素影响,算法的稳定性、能量有效性不足。提出一种分布式高效节能自适应传感器网络聚类协议(DEAC)。该协议通过增加等比能量约束项,利用节点的剩余能量信息,改变候选类首的选择概率,再基于邻居节点候选类首的信息,选择合适的类首。实验结果表明:与LEACH,HEED等拓扑协议相比,DEAC可有效减少网络总能耗、平均网络各节点的能量消耗、延长网络的生存时间,性能超过LEACH,HEED等聚类协议。     

无线传感器网络中基于减法聚类的定位算法

定位算法是无线传感器网络中的关键技术。文中在传统的Dv—Hop算法的基础上,找出其产生误差的主要原因,即对未知节点与锚节点之间的估计距离做出了修正,提出一种无线传感器网络中基于减法聚类的定位算法。该算法用减法聚类的方法,根据节点自身的密度,选出锚簇头节点,使锚簇头节点在锚节点密集处产生;同时用所有锚簇头节点平均每跳距离的均值作为未知节点的网络平均每跳距离,提高了定位精度,减少了定位过程中的能量消耗。仿真实验表明,该算法比Dv—Hop算法有更好的定位精度和鲁棒性。     

距离度量法聚类的无线传感器网络路由算法

为提升无线传感器网络簇头分布效果及簇头节点选取质量,提出基于节点间距离改进的K均值聚类路由协议算法.通过节点间最远距离及各节点距离对比方法,确定出K个规模差异小的簇群;根据不同簇群的位置、节点数目和总能量的差异,簇头选举阶段引入能量因子、质心因子和距离因子提高选取的簇头质量.实验结果表明,在网络区域内簇群分布均匀,簇头选取质量更佳,能够有效均衡全网能量,达到延长网络生命周期的目的.     

无线传感器网络分层路由协议的研究

无线传感器网络作为一种新兴的信息获取技术,是当前的研究热点。由于无线传感器网络节点能量有限,因此对其路由协议的研究成为重中之重。对近年来无线传感器网络路由协议进行归纳和分析,并基于分层路由协议提出一种均衡能量消耗的改进方案。首先,使用K-means聚类算法形成分簇,分簇形成后综合考虑节点能量和到簇中心的距离两个因素选出簇头。其次,使用多跳路由的方式进行通信,根据簇头到汇聚节点的距离形成最佳路径。     

基于模糊强化学习和果蝇优化的WSN数据聚合算法

在无线传感器网络中,传感器的能量时有限的,如果传感器的能量耗尽,那么无线传感网络的鲁棒性和寿命就会大大降低.因此,提出了基于模糊强化学习和果蝇优化的数据聚合机制,以最大限度地延长网络寿命,并进行高效数据聚合.首先,网格聚类用于簇的形成和簇头的选择,接着评估各个网格簇所有可能的数据聚合节点,然后采用模糊强化学习选取最佳数据聚合节点,最后利用果蝇优化算法动态定位整个无线传感网络的数据汇聚节点.仿真结果表明,提出的数据聚合方案在能耗和网络鲁棒性方面优于对比方案.     

T-LEACH: The method of threshold-based cluster head replacement for wireless sensor networks

In wireless sensor networks, power is the most essential resource because each sensor node has limited batteries. Many kinds of existing clustering protocols have been developed to balance and maximize lifetime of the sensor nodes in wireless sensor networks. These protocols select cluster heads periodically, and they considered only ‘How can we select cluster heads energy-efficiently?’ or ‘What is the best selection of cluster heads?’ without considering energy-efficient period of the cluster heads replacement. Unnecessary head selection may dissipate limited battery power of the entire sensor networks. In this paper, we present T-LEACH, which is a threshold-based cluster head replacement scheme for clustering protocols of wireless sensor networks. T-LEACH minimizes the number of cluster head selection by using threshold of residual energy. Reducing the amount of head selection and replacement cost, the lifetime of the entire networks can be extended compared with the existing clustering protocols. Our simulation results show that T-LEACH outperformed LEACH in terms of balancing energy consumption and network lifetime.     

PEACH: Power-efficient and adaptive clustering hierarchy protocol for wireless sensor networks

The main goal of this research is concerning clustering protocols to minimize the energy consumption of each node, and maximize the network lifetime of wireless sensor networks. However, most existing clustering protocols consume large amounts of energy, incurred by cluster formation overhead and fixed-level clustering, particularly when sensor nodes are densely deployed in wireless sensor networks. In this paper, we propose PEACH protocol, which is a power-efficient and adaptive clustering hierarchy protocol for wireless sensor networks. By using overhearing characteristics of wireless communication, PEACH forms clusters without additional overhead and supports adaptive multi-level clustering. In addition, PEACH can be used for both location-unaware and location-aware wireless sensor networks. The simulation results demonstrate that PEACH significantly minimizes energy consumption of each node and extends the network lifetime, compared with existing clustering protocols. The performance of PEACH is less affected by the distribution of sensor nodes than other clustering protocols.     

HDEEC：面向异构网络的一种基于簇路由协议

有效地使用传感节点的能量进而延长网络寿命成为设计无线传感网路由协议的一项挑战性的工作.为了延长网络,现存的多数簇方案是面向同构网络.为此,面向异构网络,提出基于簇的分布式能量有效路由HDEEC(heterogeneous WSN distributed energy-efficient clustering)协议.HDEEC协议首先提出异构网络模型,考虑了普通节点、特优节点和超特优节点三级能量节点;然后,提出能量消耗模型;最后依据这两个模型,提出了簇头选择方案.HDEEC协议以平衡、有效方式动态改变节点被选为簇头的概率.仿真结果表明,提出的HDEEC协议能够有效延长网络寿命,比DEEC、DDEEC的网络寿命分别提高了72％、68％.     

基于IEEE1451的靶场分布式无线传感器网络构建方案

摘要：为了解决兵器试验靶场“异常弹”和散布大的弹箭的弹着点定位问题，提出了基于IEEE1451标准和ZigBee、WiFi通信协议构建一种异构分簇网络的方案。论文首先介绍了IEEE 1451 协议族，阐述了系统总体结构，对比了三中无线通讯协议，优选出ZigBee、WiFi通信协议构建无线传感器网络。针对靶场分布式测试结构，给出了簇头资源分配方案和簇头节点、网关节点硬件设计方案及结构设计方案。最后，分析了IEEE1451协议的实现形式，并详细讨论了服务器端的软件设计、功能模块划分。实验结果表明：该方案实现了靶场上多节点多通信方式的无线传感器网络构建，网络具有良好的稳定性、扩展性及远程控制能力，为其他无线传感器网络构建提供了很好的应用案例     

一种基于簇头选择模型的无线传感器网络分簇算法

针对分层结构的无线传感器网络,本文提出了一种分簇算法.节点通过簇头选择模型来决定自己是否被选为簇头.簇头选择模型由节点度(ND)和剩余能量(RE)共同决定.从而提高了网络体系结构的稳定性,减少计算和通信开销.所述分簇算法不仅优化了簇头选择,还均衡整个网络节点的能量消耗,进而延长网络的生命周期.最后通过理论分析和仿真进一步验证该分簇算法的性能.     

无线传感器网络中基于分簇的自适应MAC协议

本文分析了目前无线传感器网络中MAC协议的不足，提出一种基于分簇的自适应MAC协议(AMAC)，该协议的时间帧长度可以根据网络拓扑和负载变化自动调整。通过仿真验证，在实时性、移动性较强的无线传感器网络中AMAC协议性能优于其它MAC协议。     

Energy-efficient clustering in lossy wireless sensor networks

Recent experimental studies have revealed that a large percentage of wireless links are lossy and unreliable for data delivery in wireless sensor networks (WSNs). Such findings raise new challenges for the design of clustering algorithms in WSNs in terms of data reliability and energy efficiency. In this paper, we propose distributed clustering algorithms for lossy WSNs with a mobile collector, where the mobile collector moves close to each cluster head to receive data directly and then uploads collected data to the base station. We first consider constructing one-hop clusters in lossy WSNs where all cluster members are within the direct communication range of their cluster heads. We formulate the problem into an integer program, aiming at maximizing the network lifetime, which is defined as the number of rounds of data collection until the first node dies. We then prove that the problem is NP-hard. After that, we propose a metric-based distributed clustering algorithm to solve the problem. We adopt a metric called selection weight for each sensor node that indicates both link qualities around the node and its capability of being a cluster head. We further extend the algorithm to multi-hop clustering to achieve better scalability. We have found out that the performance of the one-hop clustering algorithm in small WSNs is very close to the optimal results obtained by mathematical tools. We have conducted extensive simulations for large WSNs and the results demonstrate that the proposed clustering algorithms can significantly improve the data reception ratio, reduce the total energy consumption in the network and prolong network lifetime compared to a typical distributed clustering algorithm, HEED, that does not consider lossy links.     

一种带有能量自补给节点的异构传感器网络分簇路由算法

针对现有无线传感器网络分簇路由算法的网络生命周期短、能量消耗不均衡等问题,结合节点的能量采集技术,提出了一种带有能量自补给节点的异构传感器网络分簇路由算法。考虑到实际环境中节点能量补给不稳定,根据节点的剩余能量和当前能量自补给状态,设计了能量均衡的簇头选举机制和簇间多跳机制。仿真结果表明,在延长网络生命周期和均衡全网能量消耗方面,该算法优于采用相同能量补给规律的传统分簇路由算法(LEACH算法和SEP算法)和其他基于能量自补给的分簇路由算法(PHC算法和EBCS算法)。     

HACH: Heuristic Algorithm for Clustering Hierarchy protocol in wireless sensor networks

Wireless sensor networks (WSNs) require energy management protocols to efficiently use the energy supply constraints of battery-powered sensors to prolong its network lifetime. This paper proposes a novel Heuristic Algorithm for Clustering Hierarchy (HACH), which sequentially performs selection of inactive nodes and cluster head nodes at every round. Inactive node selection employs a stochastic sleep scheduling mechanism to determine the selection of nodes that can be put into sleep mode without adversely affecting network coverage. Also, the clustering algorithm uses a novel heuristic crossover operator to combine two different solutions to achieve an improved solution that enhances the distribution of cluster head nodes and coordinates energy consumption in WSNs. The proposed algorithm is evaluated via simulation experiments and compared with some existing algorithms. Our protocol shows improved performance in terms of extended lifetime and maintains favourable performances even under different energy heterogeneity settings.     

基于最优分簇的能量异构无线传感器网络路由协议

为了进一步均衡网络能耗,延长网络生命周期,提出了一种基于最优分簇的能量异构无线传感器网络路由协议(OCRP).OCRP协议考虑了最优簇首数K,将待测区域划分为K个固定分区,优化了成簇过程;在簇首选择阶段,充分考虑了节点的剩余能量、整个网络的能量以及节点与基站之间的距离,改进了簇头选举机制.仿真结果表明,该协议在延长网络寿命和能量消耗方面的性能优于EH-LEACH和DEEC路由协议.