无线传感器网络LEACH协议的改进与仿真

LEACH路由协议是无线传感器网络中经典的层次型拓扑组织算法。对LEACH协议进行研究和分析,指出LEACH协议在簇的区域分布和簇头负载不均衡等方面问题。文章通过节点剩余能量和与基站的距离对簇头选择、构造分簇以及非簇节点选择簇头进行改进。并利用MATLAB对改进后的算法进行仿真,表明改进后的算法有效地均衡节点能量消耗,并延长网络生存时间。     

无线传感器网络LEACH协议的改进与仿真

LEACH路由协议是无线传感器网络中经典的层次型拓扑组织算法。对LEACH协议进行研究和分析,指出LEACH协议在簇的区域分布和簇头负载不均衡等方面问题。文章通过节点剩余能量和与基站的距离对簇头选择、构造分簇以及非簇节点选择簇头进行改进。并利用MATLAB对改进后的算法进行仿真,表明改进后的算法有效地均衡节点能量消耗,并延长网络生存时间。     

无线传感网络层次型拓扑控制的应用

一般情况下,为了有效地提升无线传感网络的节点能量,就需要将无线传感网络利用拓扑结构分为多个层级进行控制,选择簇头负责发挥路由的功能,在这样的操作方式下,就可以有效地保证无线传感网络的节点能量的正常保护,进而有效地保证无线传感网络的有效存在。针对这样的情况,文章将重点介绍根据引进low energy adaptive clustering hierarchy算法和混合能量高效分布式分簇算法的无线传感网络层次型拓扑控制的具体应用,通过对无线传感网络层次型拓扑控制的应用,可以有效地实现对无线传感网络资源的合理分配。     

基于空间相关性的事件驱动无线传感器网络分簇算法

分簇算法是传感器网络中减少能量消耗的一种关键技术,它能够增强网络的扩展性和延长网络的生存时间。针对传感器节点数据的空间相关性,该文提出了一种新的基于空间相关性的事件驱动传感器网络分簇算法。算法根据用户要求的误差门限及结合节点数据的空间相关性马尔可夫模型,将事件感知区域划分成虚拟极坐标等价层。每个等价层选取层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,该方法减少了传输数据量,有效节省了网络能量。     

基于空间相关性的事件驱动无线传感器网络分簇算法

分簇算法是传感器网络中减少能量消耗的一种关键技术,它能够增强网络的扩展性和延长网络的生存时间。针对传感器节点数据的空间相关性,该文提出了一种新的基于空间相关性的事件驱动传感器网络分簇算法。算法根据用户要求的误差门限及结合节点数据的空间相关性马尔可夫模型,将事件感知区域划分成虚拟极坐标等价层。每个等价层选取层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,该方法减少了传输数据量,有效节省了网络能量。     

无线传感网自适应能量驱动簇头轮换算法研究

分簇结构是大规模无线传感网(WSN)的一种有效的拓扑管理方法。在这种结构下,由于簇头(Cluster Head,CH)节点的能耗速率远高于簇成员节点(Cluster Member,CM),需要做簇头轮换以平衡网络能耗。该文分析了基于能量驱动的簇头轮换策略,并提供一种基于簇头节点实时负载来估计其启动轮换的能量阈值的自适应簇头轮换算法(Adaptive Cluster Rotation Algorithm,ACRA)。仿真结果表明,与现有算法如LEACH,EDAC等比较,ACRA算法最少化簇头轮换次数,延长了网络生存时间。     

基于能量均衡的无线传感器网络路由算法

为了提高无线传感器网络的生存时间,针对当前LEACH算法存在的能量不均衡难题,提出一种能量均衡的无线传感器网络节点路由算法。首先将监测区域看成以基站为中心的扇形区域,并将扇形区域分割成不同大小的弧形方块,每个弧形方块中的节点组成一个簇,根据节点剩余能量产生簇头,然后采用单跳和多跳相结合的簇间通信机制,最后采用仿真实验测试算法的性能。结果表明,本文算法有效提高了网络的能量利用率,能够实现节点之间的能耗均衡,使无线传感器的网络生存时间得到延长,适用于对网络生命周期要求较高的应用。     

改进遗传算法优化无线传感器网络路由算法

为了有效延长无线传感器网络的生存时间,针对传感器节点能耗不均衡难题,提出一种改进遗传算法优化的无线传感器网络路由算法。首先对LEACH算法不足进行分析,然后构建簇头节点选择的目标函数,并将其作为遗传算法的搜索目标,最后通过遗传算法找到下一时刻簇头的候选节点,并针对遗传算法不足进行相应改进。采用仿真实验对算法的性能进行分析,结果表明,相对于其它无线传感器路由算法,本文算法可以保证无线传感器的节点能量均衡,延长了网络的生存时间。     

一种基于节能的无线传感器网络GAF算法

GAF(Geographical Adaptive Fidelity)拓扑控制算法提出的节点休眠机制和基于网格划分的拓扑控制方案,使其在无线传感网络的拓扑生成及节能方面起到非常好的效果。然而,传统的GAF算法由于其随机的簇头选择策略和固定的网络划分机制,导致其全网节点的能量消耗不均匀,节点死亡过快。文章将GAF中固定的网格结构进行动态化的水平和垂直方向的周期化移动,最大化延长了网络生存时间。     

一种半集中式低能耗自适应无线传感器网络成簇算法

基于对LEACH等算法的研究,提出一种半集中式,综合利用节点位置信息与剩余能量的无线传感器网络分簇及簇头选举算法。利用节点位置信息,在簇头选举阶段和传感数据传输阶段使用不同的拓扑划分,在尽可能选取剩余能量较高的节点作为簇头的前提下,能够既保证簇均匀分布,又尽量做到簇头在簇内处于相对中心位置,并且避免了成簇阶段的碰撞。仿真结果表明,该算法有效延长了网络生存周期,收集了更多的传感数据,并且适合大范围覆盖的传感器网络。     

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。     

一种无线传感器网络分簇路由算法研究

在分析LEACH协议的基础上提出一种基于能量和距离的多跳路由算法（CAED）。由基站依据节点剩余能量和簇头与基站的距离分别选出二层簇头,簇内节点利用单跳和多跳模式与簇头进行通信。仿真实验表明,新算法有效地平衡了节点的能量消耗,并显著地延长了网络的生命周期。     

Multi-factor and Distributed Clustering Routing Protocol in Wireless Sensor Networks

One of important issues in wireless sensor networks is how to effectively use the limited node energy to prolong the lifetime of the networks. Clustering is a promising approach in wireless sensor networks, which can increase the network lifetime and scalability. However, in existing clustering algorithms, too heavy burden of cluster heads may lead to rapid death of the sensor nodes. The location of function nodes and the number of the neighbor nodes are also not carefully considered during clustering. In this paper, a multi-factor and distributed clustering routing protocol MFDCRP based on communication nodes is proposed by combining cluster-based routing protocol and multi-hop transmission. Communication nodes are introduced to relay the multi-hop transmission and elect cluster heads in order to ease the overload of cluster heads. The protocol optimizes the election of cluster nodes by combining various factors such as the residual energy of nodes, the distance between cluster heads and the base station, and the number of the neighbor nodes. The local optimal path construction algorithm for multi-hop transmission is also improved. Simulation results show that MFDCRP can effectively save the energy of sensor nodes, balance the network energy distribution, and greatly prolong the network lifetime, compared with the existing protocols.     

无线传感网络中基于蚁群的路由算法

In the wireless sensor networks, high efficient data routing for the limited energy resource networks is an important issue. By introducing Ant-colony algorithm, this paper proposes the wireless sensor network routing algorithm based on LEACH. During the construction of sensor network clusters, to avoid the node premature death because of the energy consumption, only the nodes whose residual energy is higher than the average energy can be chosen as the cluster heads. The method of repeated division is used to divide the clusters in sensor networks so that the numbers of the nodes in each cluster are balanced. The basic thought of ant-colony algorithm is adopted to realize the data routing between the cluster heads and sink nodes, and the maintenance of routing. The analysis and simulation showed that the proposed routing protocol not only can reduce the energy consumption, balance the energy consumption between nodes, but also prolong the network lifetime.     

一种基于贝叶斯博弈的传感器网络分簇算法

提出了一种基于贝叶斯博弈的无线传感器网络分簇算法.算法将无线传感器网络节点的簇头选择抽象为一个多人的博弈过程,节点之间通过不完全信息的静态博弈实现簇头的合理分布.算法在支付函数的设计时充分考虑了节点能耗和路径损耗等因素,因此通过博弈该算法能实现簇头的合理分布.仿真结果表明,算法在保证数据传输实时性的前提下可使网络能耗更加稳定、能量分布更加均匀,有效地延长网络生命周期.     

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.     

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。     

An energy aware algorithm for OLSR clustering

One of the important aspects of a mobile ad hoc network (MANET) is the limitation of the amount of available energy and the network lifetime. The tremendous amount of using mobile nodes in wireless communication medium makes energy efficiency a fundamental requirement for MANETs. In this paper, we propose a novel energy aware clustering algorithm for the optimized link state routing (OLSR) routing protocol. This algorithm takes into account the node density and mobility and gives major improvements regarding the number of elected cluster heads. Our objective is to elect a reasonable number of cluster heads that will serve for hierarchical routing based on OLSR. The proposed algorithm aims to increase the network lifetime by considering the ad hoc residual energy while taking routing decisions. It also optimizes the delay of carried flows by adopting a selective forwarding approach based on a hierarchical routing model.     

Energy-balanced unequal clustering protocol for wireless sensor networks

Clustering provides an effective way to prolong the lifetime of wireless sensor networks.One of the major issues of a clustering protocol is selecting an optimal group of sensor nodes as the cluster heads to divide the network.Another is the mode of inter-cluster communication.In this paper,an energy-balanced unequal clustering(EBUC)protocol is proposed and evaluated.By using the particle swarm optimization(PSO)algorithm,EBUC partitions all nodes into clusters of unequal size,in which the clusters closer to the base station have smaller size.The cluster heads of these clusters can preserve some more energy for the inter-cluster relay traffic and the 'hot-spots' problem can be avoided.For inter-cluster communication,EBUC adopts an energy-aware multihop routing to reduce the energy consumption of the cluster heads.Simulation results demonstrate that the protocol can efficiently decrease the dead speed of the nodes and prolong the network lifetime.     

Joint Routing and Resource Allocation for Cluster Based Isolated Nodes in Cognitive Radio Wireless Sensor Networks

Clustering is an effective way to increase network lifetime but it leads to formation of isolated nodes in the wireless sensor network. These isolated sensor nodes forward data directly to sink and consume more energy which significantly reduces the network lifetime. In this article, we present how to maximize the network lifetime through joint routing and resource allocation with isolated nodes technique (JR-IN) between cluster head and isolated nodes in a cognitive based wireless sensor networks. In JR-IN technique the network area is divided into different layers and cluster size is formulated in each layer such that the size of the cluster remains unequal when it moves towards sink. Hence the cluster size is lager in the outermost layer compared to the cluster size in the inner most layer. To avoid inter cluster collision, we proposed different fixed channel to all the cluster heads in the network. For the intra cluster communication, the cluster member (sensor nodes) will lease the spectrum from the cluster head and forward data to their respective cluster head using TDMA technique. The periodical data gathering of cluster heads and forwarding the data to one hop cluster head may tend to lose energy faster and dies out quickly. We also propose in the JR-IN technique, the isolated nodes in the layer will take charge as a cluster head node and utilizes the resource allocated to the respective cluster head and forward the data to next hop cluster head. Simulation result shows that JR-IN outperforms the existing techniques, maximizes network lifetime and throughput and reduces the end to end delay.