基于遗传算法和蚁群算法的LEACH改进协议

针对无线传感器网络低功耗自适应集簇分层(Low Energy Adaptive Clustering Hierarchy, LEACH)路由协议因能耗不均衡导致节点过早死亡的问题,提出了一种基于遗传算法和蚁群算法改进的LEACH路由协议。在分簇阶段,通过遗传算法选举合理的簇头节点并根据节点的分布划分簇群;在数据传输阶段,通过蚁群算法使簇头节点尽可能选择能量充足且距离较短的路径进行数据传输。仿真结果表明,与传统的分簇路由协议LEACH和LEACH-C相比,改进算法可以使网络的能量消耗更加均衡,并延长网络的生命周期。     

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LEACH算法的改进与仿真分析

对无线传感器网络分簇路由协议中LEACH算法进行了研究,针对算法中簇头节点随机选取、节点能量分布不均等不足之处,提出一种基于节点剩余能量、邻居密度与基站相对距离等因素改进的LEACH算法。改进后的算法通过网络最低能耗计算得出最优簇头数目,在簇头选取阶段,优化簇头的阈值计算公式,使节点剩余能量高、节点邻居数目多、相对基站距离近的节点更容易成为簇头。利用MATLAB软件,对LEACH算法、HEED算法及改进的LEACH算法的性能进行了仿真分析和比较。实验结果表明,改进的LEACH算法的网络整体能耗要低于LEACH算法和HEED算法,并显著地延长了网络的生存时间。     

非变换簇的WSN分簇路由算法

针对LEACH算法簇头选取及能量消耗方面的不足,提出一种基于能量、距离和节点度的分簇路由算法CMEDD,通过均匀分簇减少重建过程,对簇头选举公式进行改进,合理选择簇头,从而均衡节点能耗。采用基于代价因子的单跳和多跳相结合的方式建立最优路径进行数据传输。仿真结果表明,与LEACH算法和RMCRW算法相比,CMEDD算法能够有效均衡节点能耗,可相对延长网络生存周期。     

一种基于LEACH的无线传感器网络路由算法及仿真

在低功耗自适应分簇（LEACH,Low Energy Adaptive Clustering Hierarch）算法中,由于每一轮循环都要重新构造簇,距离较远的簇头节点可能会因长距离发送数据而过早耗尽自身能量,能量较低的节点当选为簇头节点时将会加速该节点的死亡,影响整个网络的生命周期。针对LEACH算法分簇机制中存在的不足,提出了一种改进的路由算法。仿真结果表明,改进算法通过考虑节点的剩余能量与固定分簇的方法,有效的改善了网络能量均衡,提高了网络生存时间。     

一种基于历史信息的簇头选取机制

无线传感器网络（WSN,Wireless Sensor Network）中,如何减少节点的能耗一直是簇头选择机制的研究目标。现提出了一种基于历史能耗信息选择机制的簇头选择算法（CHCM,Cluster Head Choosing Mechanism）,该算法通过节点历史能耗信息和节点分布密度参数预测簇头能耗速度,并将该预测方法融入簇头选取过程当中,使网络生命期延长。最后利用CHCM对LEACH路由协议进行改进,得到CHCM＋LEACH路由协议。仿真结果表明CHCM＋LEACH在网络生命期和网络总剩余能量上分别比LEACH算法分别提高了27%和14%。     

考虑整体消耗代价的无线传感器网络分簇算法

在LEACH协议的基础上,研究一种无线传感器网络分簇算法,采用高级节点作为固定簇头替代LEACH中的随机簇头选择策略,推导出最优簇头节点数目即所需高级节点数的计算公式及各类节点所需能量的表达式,并从网络整体消耗代价的角度出发,通过仿真对网络性能进行分析评价。结果表明,采用一定量的高级节点作为固定簇头,当其节点硬件代价和电池能量代价之比a1/b超过一定值时,新算法的整体网络代价明显低于LEACH。     

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。     

认知无线电网络自适应能量驱动双门限簇头轮换算法研究

 为了延长基于分簇结构的认知无线电网络的网络寿命,需要采用簇头轮换的方法来平衡认知无线电网络的能耗.通过分析网络中簇头节点与普通节点之间的能耗差异,建立能量消耗模型,并提出了一种基于簇头节点实时负载来估计其启动簇头轮换的双门限自适应簇头轮换算法(Double Thresholds Adaptive Cluster Rotation Algorithm,DTACRA).仿真结果表明,与现有算法LEACH和EDAC算法等比较,DTACRA算法可以有效提高节点能量利用效率,延长了网络生存时间.     

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.     

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。     

A novel residual energy‐based distributed clustering and routing approach for performance study of wireless sensor network

Non‐uniform energy consumption during operation of a cluster‐based routing protocol for large‐scale wireless sensor networks (WSN) is major area of concern. Unbalanced energy consumption in the wireless network results in early node death and reduces the network lifetime. This is because nodes near the sink are overloaded in terms of data traffic compared with the far away nodes resulting in node deaths. In this work, a novel residual energy–based distributed clustering and routing (REDCR) protocol has been proposed, which allows multi‐hop communication based on cuckoo‐search (CS) algorithm and low‐energy adaptive‐clustering–hierarchy (LEACH) protocol. LEACH protocol allows choice of possible cluster heads by rotation at every round of data transmission by a newly developed objective function based on residual energy of the nodes. The information about the location and energy of the nodes is forwarded to the sink node where CS algorithm is implemented to choose optimal number of cluster heads and their positions in the network. This approach helps in uniform distribution of the cluster heads throughout the network and enhances the network stability. Several case studies have been performed by varying the position of the base stations and by changing the number of nodes in the area of application. The proposed REDCR protocol shows significant improvement by an average of 15% for network throughput, 25% for network scalability, 30% for network stability, 33% for residual energy conservation, and 60% for network lifetime proving this approach to be more acceptable one in near future.     

An intelligent and knowledge‐based overlapping clustering protocol for wireless sensor networks

Overlapping is one of the topics in wireless sensor networks that is considered by researchers in the last decades. An appropriate overlapping management system can prolong network lifetime and decrease network recovery time. This paper proposes an intelligent and knowledge‐based overlapping clustering protocol for wireless sensor networks, called IKOCP. This protocol uses some of the intelligent and knowledge‐based systems to construct a robust overlapping strategy for sensor networks. The overall network is partitioned to several regions by a proposed multicriteria decision‐making controller to monitor both small‐scale and large‐scale areas. Each region is managed by a sink, where the whole network is managed by a base station. The sensor nodes are categorized by various clusters using the low‐energy adaptive clustering hierarchy (LEACH)‐improved protocol in a way that the value of p is defined by a proposed support vector machine–based mechanism. A proposed fuzzy system determines that noncluster heads associate with several clusters in order to manage overlapping conditions over the network. Cluster heads are changed into clusters in a period by a suggested utility function. Since network lifetime should be prolonged and network traffic should be alleviated, a data aggregation mechanism is proposed to transmit only crucial data packets from cluster heads to sinks. Cluster heads apply a weighted criteria matrix to perform an inner‐cluster routing for transmitting data packets to sinks. Simulation results demonstrate that the proposed protocol surpasses the existing methods in terms of the number of alive nodes, network lifetime, average time to recover, dead time of first node, and dead time of last node.     

一种基于K-means的WSN移动汇聚路由算法

无线传感网络(Wireless Sensor Network,WSN)作为一种资源受限的网络,网络中节点的能耗直接影响了网络的性能。因此,均衡网络中的能耗,延长网络的生命周期,成为设计WSN路由算法的重要目标。于是,在LEACH-C协议的基础上提出了一种移动汇聚路由算法。分簇阶段由Sink节点计算最优簇首个数,通过K-means聚类将网络中的节点划分至不同的集群,选择通信成本最低的节点作为各集群的簇首。稳定传输阶段通过移动Sink进行数据采集,针对不同的延迟分别规划Sink节点的移动轨迹。MATLAB仿真结果表明,与LEACH和LEAHC-C算法相比簇首的分布更合理,结合Sink节点的移动策略能有效均衡网络能耗,延长网络的寿命。     

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。     

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。     

基于改进SSA优化WSN分簇协议

无线传感器网络(Wireless Sensor Networks,WSN)的路由协议是无线传感器网络领域中的一个研究热点.针对LEACH协议的不足,提出一种基于自适应t分布改进麻雀搜索算法(Improved Sparrow Search Algorithm,ISSA)的改进LEACH协议(LEACH?ISSA),以解决...     

A Green Clustering Protocol for Mobile Sensor Network Using Particle Swarm Optimization

Energy consumption of sensor nodes is one of the crucial issues in prolonging the lifetime of wireless sensor networks. One of the methods that can improve the utilization of sensor nodes batteries is the clustering method. In this paper, we propose a green clustering protocol for mobile sensor networks using particle swarm optimization (PSO) algorithm. We define a new fitness function that can optimize the energy consumption of the whole network and minimize the relative distance between cluster heads and their respective member nodes. We also take into account the mobility factor when defining the cluster membership, so that the sensor nodes can join the cluster that has the similar mobility pattern. The performance of the proposed protocol is compared with well-known clustering protocols developed for wireless sensor networks such as LEACH (low-energy adaptive clustering hierarchy) and protocols designed for sensor networks with mobile nodes called CM-IR (clustering mobility-invalid round). In addition, we also modify the improved version of LEACH called MLEACH-C, so that it is applicable to the mobile sensor nodes environment. Simulation results demonstrate that the proposed protocol using PSO algorithm can improve the energy consumption of the network, achieve better network lifetime, and increase the data delivered at the base station.     

有效降低无线网络节点能量的LEACH新算法

LEACH是一种低功耗自适应按簇分层路由算法.为了降低节点能耗,在LEACH协议的基础上提出了在选举簇头时,改变阈值T(n)的大小以降低节点成为簇头的概率,从而节省网络因分簇而消耗的能量.同时又提出了一种基于节点剩余能量的二层簇头的算法,该算法能使节点减少将冗余信息传输到基站,从而达到降低节点消耗能量的目的.通过实验仿真,表明这些方法能使网络节点能量的消耗减少,达到了延长网络生命周期的目的.