无线传感器网络基于多元簇首的分簇数据收集算法

为了提高数据收集可靠性和延长网络生命周期,该文提出基于多元簇首的分簇数据收集算法。算法将网络划分为大小相等的栅格,由每个栅格中的节点各自构成一个簇,根据节点失效概率从每个栅格中选出多个簇首,并由同一栅格中的多个簇首协作完成栅格中节点的数据收集任务。此外,算法还采取了一些降低能量开销的措施。仿真实验结果表明,与现有相关算法相比,该算法具有较高的数据收集可靠性,并能够显著延长网络生命周期。     

基于能量和密度的WSNs动态分区成簇路由算法

针对传统的层次型网络存在的分簇不合理和能耗不均衡等问题,提出了一种基于能量和密度的动态非均匀分区成簇路由算法。该算法先根据节点与基站之间的距离将网络合理地进行动态的区域划分,在区域内成簇,使靠近基站的簇规模小于距离基站较远的簇,减少靠近基站的簇首负担和能量消耗;通过综合考虑节点剩余能量和节点密度等因素来优化簇的非均匀划分和簇首的选择,簇首间采取基于数据聚合的多跳传输机制。仿真结果表明,与经典路由算法LEACH相比,该算法能有效均衡节点能耗,延长网络生命周期。     

基于分簇的无线传感器网络路由算法

在大规模无线传感器网络中以最节能的方式将数据发送到sink是该领域研究的热点之一。针对LEACH算法的不足之处,提出了一种能耗均衡的路由算法。此算法在考虑节点剩余能量的基础上采用两分法选举簇首,然后簇首通过能耗代价函数计算出一条能耗最小的路径,以多跳转发的方式将数据传送到sink.,为了进一步减少节点的能耗,算法在簇内采用了数据聚合机制。仿真结果表明,算法有效地均衡了网络能耗,延长了网络生存期。     

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。     

基于动态簇半径的非均匀分簇算法

在无线传感器网络分簇路由算法中,针对节点能耗不均衡所引发的"热区"问题,提出了基于动态簇半径的非均匀分簇算法(UCDCR)。该算法在簇组建阶段,对网络进行区域划分,不同区域的候选簇首通过簇竞争半径来构建大小不同的簇,使簇首随网络的运行动态的改变簇竞争半径,为数据转发预留更多能量。仿真结果表明:与EEUC算法和CUCRA算法相比,UCDCR算法更加有效地均衡了节点能耗,延长了网络生命的周期。     

基于天牛须搜索的无线传感网分簇路由协议

针对无线传感器网络中的能耗不均衡问题,提出一种基于天牛须搜索算法的负载均衡分簇路由协议算法(LEACH-BAS)。该算法引入候选簇首选举机制,使用天牛须搜索算法对簇首分布进行搜索优化,形成合理分簇。此外,在簇间路由通信时,考虑剩余能量因子和传输能耗因子来选择中继节点。仿真结果表明,LEACH-BAS算法的网络生命周期相比LEACH、EAMMH、LEACH-GA和LEACH-PSO算法分别延长了39%、22%、15%和8%。LEACH-BAS算法应用在WSN监测场景,能有效解决WSN中能量不足的问题,优化簇首节点分布,降低节点能耗,有效地延长网络生命周期。     

基于数据融合的无线传感器网络路由算法

在分簇协议LEACH和链状协议PEGASIS的基础上,提出一种新的基于数据融合的分簇路由算法.簇首节点采用多跳方式传输数据,并根据周围节点的密集程度构造不同大小的簇;簇内节点计算上行和下行节点构造数据融合树,采用时分复用调度算法进行多跳路由.NS2仿真结果表明该路由算法均衡了各个节点的能量消耗,延长了网络存活时间,并降低了网络延迟.     

WSN中能量有效分簇多跳路由算法

针对现有无线传感器网络(WSN)分簇路由算法存在的能耗不均衡问题,提出一种能量有效分簇多跳路由算法,该算法包括两个方面:一是选举簇首时引入簇内平均剩余能量因子,根据上一轮结束后簇内各节点剩余能量和簇内节点的平均剩余能量的比值更新簇首在所有节点中所占的百分比;二是要求簇首根据MTE多跳路由协议与基站通信,从而均衡WSN整...     

传感器网络中基于簇树的路由算法

针对无线传感器网络中高能效收集数据的需要,提出一种基于簇树的路由算法ETRA(energy-efficient tree-clustered Routing algorithm).首先,ETRA利用改进的最小ID算法实现对网络的平衡分簇;然后,通过簇首信息交换,构建从簇首至sink节点的数据汇聚树;最后,在数据收集阶段,数据从成员节点传送至簇首节点,并通过数据汇聚树传送至sink节点.仿真结果表明,与典型的分簇协议相比,ETRA获得了更均衡的分簇结构和更长的网络生存期.     

无线传感器网络多汇聚节点分簇算法

为解决大规模无线传感器网络的节点通信效率问题,提出无线传感器网络的一种多汇聚节点分簇算法,针对拥有多个汇聚节点的监控区域,对网络进行层次化管理。算法通过对多种参数的综合考虑后产生簇头,并将传感器节点分配到相应的簇,由此可以有效降低节点的非均匀能耗,减少因能耗较大节点的能量过度衰竭而造成网络可用率下降。仿真结果显示,该算法可以延缓首个死亡节点的发生时间,并能有效延长无线传感器网络的整体可用率。     

基于全局信息的LEACH协议改进算法

传统LEACH协议在选举簇头节点时,采用动态簇头选举算法,每轮选举产生簇头节点个数为最佳簇头数的概率并不是最大,使得每轮选举的簇头数偏差较大,不能使节点能量达到最优化。针对这一问题,提出了改进的LEACH-P协议,该协议在簇头选举阶段通过簇头节点间的相互协作,以少量的能量消耗来获取全局信息,消除了LEACH协议簇头选举算法的盲目性,从而改善簇头选举算法。实验结果表明,LEACH—P协议相比传统LEACH协议有效地节省了节点能量,延长了网络生命周期。     

Energy-Efficient Routing Algorithm Based on Unequal Clustering and Connected Graph in Wireless Sensor Networks

Clustering and multi-hop routing algorithms substantially prolong the lifetime of wireless sensor networks (WSNs). However, they also result in the energy hole and network partition problems. In order to balance the load between multiple cluster heads, save the energy consumption of the inter-cluster routing, in this paper, we propose an energy-efficient routing algorithm based on Unequal Clustering Theory and Connected Graph Theory for WSN. The new algorithm optimizes and innovates in two aspects: cluster head election and clusters routing. In cluster head election, we take into consideration the vote-based measure and the transmission power of sensor nodes when to sectionalize these nodes into different unequal clusters. Then we introduce the connected graph theory for inter-cluster data communication in clusters routing. Eventually, a connected graph is constituted by the based station and all cluster heads. Simulation results show that, this new algorithm balances the energy consumption among sensor nodes, relieves the influence of energy-hole problem, improve the link quality, achieves a substantial improvement on reliability and efficiency of data transmission, and significantly prolongs the network lifetime.     

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.     

Dual head static clustering algorithm for wireless sensor networks

Clustering of nodes is often used in wireless sensor networks to achieve data aggregation and reduce the number of nodes transmitting the data to the sink. This paper proposes a novel dual head static clustering algorithm (DHSCA) to equalise energy consumption by the sensor nodes and increase the wireless sensor network lifetime. Nodes are divided into static clusters based on their location to avoid the overhead of cluster re-formation in dynamic clustering. Two nodes in each cluster, selected on the basis of the their residual energy and their distance from the sink and other nodes in the cluster, are designated as cluster heads, one for data aggregation and the other for data transmission. This reduces energy consumption during intra-cluster and inter-cluster communication. A multi-hop technique avoiding the hot-spot problem is used to transmit the data to the sink. Experiments to observe the energy consumption patterns of the nodes and the fraction of packets successfully delivered using the DHSCA suggest improvements in energy consumption equalisation, which, in turn, enhances the lifetime of the network. The algorithm is shown to outperform all the other static clustering algorithms, while being comparable with the performance of the best dynamic algorithm.     

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.     

A grid based clustering and routing algorithm for solving hot spot problem in wireless sensor networks

Energy conservation of the sensor nodes is the most important issue that has been studied extensively in the design of wireless sensor networks (WSNs). In many applications, the nodes closer to the sink are overburdened with huge traffic load as the data from the entire region are forwarded through them to reach the sink. As a result, their energy gets exhausted quickly and the network is partitioned. This is commonly known as hot spot problem. Moreover, sensor nodes are prone to failure due to several factors such as environmental hazards, battery exhaustion, hardware damage and so on. However, failure of cluster heads (CHs) in a two tire WSN is more perilous. Therefore, apart from energy efficiency, any clustering or routing algorithm has to cope with fault tolerance of CHs. In this paper, we address the hot spot problem and propose grid based clustering and routing algorithms, combinedly called GFTCRA (grid based fault tolerant clustering and routing algorithms) which takes care the failure of the CHs. The algorithms follow distributed approach. We also present a distributed run time management for all member sensor nodes of any cluster in case of failure of their CHs. The routing algorithm is also shown to tolerate the sudden failure of the CHs. The algorithms are tested through simulation with various scenarios of WSN and the simulation results show that the proposed method performs better than two other grid based algorithms in terms of network lifetime, energy consumption and number of dead sensor nodes.     

Constructing a MANET Based on Clusters

This paper proposes a scheme for constructing a mobile ad hoc network (MANET) based on clusters. The proposed MANET architecture is made up of two hierarchies. One hierarchy is the backbone network which is made up of cluster heads and associate nodes, and the other hierarchy is the cluster which is made up of one cluster head and multiple cluster members. In the proposed cluster generation algorithm, the number of potential cluster members is used as a metric, and it is always the new node with the maximum number of potential cluster members that is elected as a cluster head. In this way, the number of cluster heads is minimized. In this scheme, only one associate node is used to achieve the communication between two cluster heads, so the number of nodes included in the backbone network is minimized. This scheme also proposes the cluster merging algorithm in order to maintain the minimum number of cluster heads. In the proposed cluster repair algorithm, if a cluster head fails/moves out of the cluster, then a new cluster head is elected to maintain the cluster stability. From the perspective of the cluster stability, this paper analyzes the performance parameters of the proposed scheme, and the data results show that the proposed scheme improves the MANET stability.     

一种基于邻域信息的多信道自适应建网算法

为实现多信道无线自组网的高效建网,针对节点难以感知全网拓扑、其他所有节点的可用频谱以及无法获得同步信息的实际场景,提出了一种基于邻域信息的多信道自适应建网算法。该算法首先设计基于邻域信息的建网策略,使节点能够以自身信息为基础,充分利用可用信道情况、邻居簇首情况等有限的邻域信息进行自适应决策,以建立分簇结构的网络;然后提出基于最大熵原理的信道质量评价算法和基于多头绒泡菌模型的邻居簇首评价算法,分别对节点的可用信道和邻居簇首进行排序,指导节点在建网过程中选择合理的信道和簇首。仿真结果表明,所提建网算法能够使节点在实际场景通信受限的条件下以较小的通信开销完成建网,建立的网络在公共信道数量和簇规模方面也取得了较好的均衡。     

基于繁忙因子的VVSN自适应双簇头分簇算法研究

在WSN中,节点之间不平衡通信消耗大量能量,因此网络生存时间较短。为改善网络整体生存时间,提出一种基于网络繁忙因子的簇头自适应切换算法。首先,算法一次性选举双簇头,再根据网络实际情况自适应切换簇头。然后,在簇头选举完成后,节点通过当前簇头与基站通信,若当前簇头的能量低于门限值,则网络中的当前簇头将被切换到次级簇头,此时节点通过次级簇头与基站通信,从而降低节点能耗,减少节点的死亡率。双簇头切换机制缩短了整体通信距离,缓解簇头节点过早死亡,使网络生存时间增长。仿真结果表明,该算法通过缩短整体通信距离可显著降低整体网络的能量消耗,增加网络的生存时间。