基于距离分区的多级异构无线传感器网络成簇算法

为了防止无线传感器网络(WSN)节点因为通信距离过长而过早死亡,有效延长网络生命周期,提出了一种基于距离分区的高能效的多级异构无线传感器网络成簇算法(MHCADP)。此算法将监测区域分为三部分,并根据不同监测区域和基站的距离部署能量不同的三类节点,按照节点剩余能量与网络平均能量的比例来选举簇头节点,让较高初始能量和剩余能量的节点拥有更多的机会成为簇头。另外,在数据传输时,考虑节点和基站的距离以及自身剩余能量,选择单跳或多跳的传输方式。仿真实验结果表明,与现有的重要成簇算法——低能耗自适应分簇分层(LEACH)算法和稳定选举协议(SEP)算法相比,MHCADP算法能够有效减少网络能量消耗和平衡网络负载,使网络稳定周期和生命周期延长50%以上。     

无线传感器网络LEACH协议的改进方案

由于LEACH协议中簇头节点的选举未考虑能量,簇头节点在空间上分布不均等不足。根据簇头节点周围其它簇头节点存在情况,结合节点的能量提出一种改进型的路由协议。改进后的协议簇头节点在空间分布上得到有效地改善,同时降低节点早死的概率。     

自适应分簇拓扑算法EC—LEACH的研究

LEACH(Low-Energy Adaptive Clustering Hierarchy)是一种自适应分簇拓扑算法.针对LEACH算法存在的问题,本文提出了一种改进算法--EC-LEACH(Energy Comparison LEACH).该算法采用与LEACH算法相同的前提假设,对LEACH算法的某些参数进行了改进,主要包括:①从节点能量方面考虑,修改了LEACH算法的簇头选举阈值;②综合考虑节点的能量状况与节点度,采用簇头主动"让贤"的方法选择簇头.仿真结果表明,改进后的算法能够有效平衡节点的能量消耗分布,有效延长网络生存时间.     

基于LEACH协议的改进路由算法

针对LEACH协议在簇头选择过程中消耗能量多和节点间能量消耗不均匀的问题,本文提出了一种基于时间的均匀分簇混合路由协议( ECHT)在簇头竞选阶段中,节点广播成为簇头的时间与其剩余能量成反比,越早广播的节点将成为簇头.在数据传输阶段中,采用多跳与单跳相结合的方式将数据传送到基站,并计算数据传送开销来修改节点能量以此确定网络生命周期.仿真结果显示,ECHT协议能有效地均衡网络节点的能量消耗和延长网络生命周期.     

基于能量优化模型的无线传感器网络分簇算法

考虑到无线传感器分簇网络中簇的规模、簇头数量和节点剩余能量是能量有效型分簇路由算法关注的重要指标,提出了一种基于能量优化模型(EOM)的分布式分簇算法——EOMC,该算法通过建立网络能耗优化模型,以最优簇头数构建分簇通信规模,并结合功率控制将候选簇头限制在一定宽度的选举环带,使得簇头分布均衡,同时兼顾到节点剩余能量进行分簇,以达到均衡节点能耗,延长网络生存期的目的。与低能耗自适应分簇分层(LEACH)协议的对比仿真的结果表明,该算法能够达到预期指标,算法的开销相对较小。     

基于Mamdani模糊推理的无线传感器网络可信簇头选举算法

为了解决无线传感器网络中恶意节点成为簇头而引起的层次路由安全问题,提出了一种基于Mamdani模糊推理的可信簇头选举算法(TCEM)。TCEM算法根据节点的行为表现,采用贝叶斯原理评估节点信任值,在此基础上,结合密集度及向心度,使用Mamdani模糊推理方法计算节点优越度,选择最优者作为簇头,从而实现簇头的可信选举。仿真实验结果表明,该算法能有效阻止恶意节点成为簇头,且在簇头合理分布、网络整体能效等方面均有良好表现。     

面向分簇无线传感器网络的两层动态地址分配协议

针对分簇无线传感器网络提出了一种新的两层动态地址分配(TTDA)协议.TTDA采用两级地址分配方式,即基站为簇头分配地址,簇头为簇成员分配地址.基站为簇头分配地址时,采用Huffman编码,使得离基站更远的簇头获取更短的地址,从而节省地址传输能耗.地址分配基于租约,只在一段时间内有效,因此节点失效后可以回收其地址.T1...     

一种传感器网络的非均匀节能分簇模型

针对无线传感器网络中节点能耗不平衡导致系统生存时间缩短的问题,提出了一种无线传感器网络的非均匀节能分簇(UEEC)模型.UEEC通过自组织的方式和对簇头的动态选择,在靠近sink点(基站)的地方形成较小的簇,在远离sink点的地方形成较大的簇,从而使簇头能够对信息收集能耗与信息转发能耗进行平衡.同时,簇头的动态选举又能够把能耗平均分散在各个节点上.仿真结果表明,UEEC在减少与平衡无线传感器网络的节点能耗上有较好的性能,从而能够延长无线传感器网络的生存时间.     

无线传感器网络LEACH协议改进

本文在对现有分簇技术如LEACH协议进行深入全面分析的基础上,提出新的基于剩余能量和距离的争先式多跳簇生成算法。算法有两个特点,1）提出“参考能量”的概念,由节点自身剩余能量和参考能量的比值确定节点成为簇首的优先度,凭优先度争先成为簇首,同时考虑节点与基站的问距,判断“参考距离”,使簇首分布均衡。2）基站需要用一个给定的发送功率向网络内广播一个信号。每个传感器节点在接收到此信号后,根据接收信号的强度计算它到基站的近似距离。获得这个距离不仅有助于传感器节点向基站传输数据时选择合适的发送功率以节约能量消耗,而且还为本算法构造非均匀大小的簇。     

无线传感器网络的流量自适应分簇算法协议

在分析LEACH路由协议算法的缺点的基础上,提出了一种用于无线传感器网络的基于流量自适应的TDMA分簇算法协议.该协议根据当前节点数据流量的变化,自适应地调整该节点在其簇内通信的时隙长度,减少节点空闲时消耗的能量和节点从睡眠到活跃状态来回切换的能量.仿真实验结果表明,与LEACH协议簇内时隙分配算法相比,运用这种新的时隙分配算法,可以节省节点的能量,提高网络的生存时间,改善网络性能.     

基于能耗均衡的水下传感器网络分簇路由算法

针对水下传感器网络能耗不均衡问题,提出一种能耗均衡的多跳非均匀分簇路由算法。算法在水下传感器网络非均匀分簇的基础上,通过改进节点簇头竞选的阈值计算方式,解决了网络后期簇头竞选阈值低导致的网络能耗激增;通过引入多跳路由选择公式,综合考虑节点剩余能量和链路能耗,延长网络生命周期。仿真表明,提出的算法生成簇头数目稳定,能耗较低,并且能有效延长水下传感器网络的生命周期。     

A Nonuniform Clustering Routing Algorithm Based on an Improved K-Means Algorithm

In a large-scale wireless sensor network (WSN), densely distributed sensor nodes process a large amount of data. The aggregation of data in a network can consume a great amount of energy. To balance and reduce the energy consumption of nodes in a WSN and extend the network life, this paper proposes a nonuniform clustering routing algorithm based on the improved K-means algorithm. The algorithm uses a clustering method to form and optimize clusters, and it selects appropriate cluster heads to balance network energy consumption and extend the life cycle of the WSN. To ensure that the cluster head (CH) selection in the network is fair and that the location of the selected CH is not concentrated within a certain range, we chose the appropriate CH competition radius. Simulation results show that, compared with LEACH, LEACH-C, and the DEEC clustering algorithm, this algorithm can effectively balance the energy consumption of the CH and extend the network life.     

An Asynchronous Clustering and Mobile Data Gathering Schema Based on Timer Mechanism in Wireless Sensor Networks

Recently, Wireless sensor networks (WSNs) have become very popular research topics which are applied to many applications. They provide pervasive computing services and techniques in various potential applications for the Internet of Things (IoT). An Asynchronous Clustering and Mobile Data Gathering based on Timer Mechanism (ACMDGTM) algorithm is proposed which would mitigate the problem of “hot spots” among sensors to enhance the lifetime of networks. The clustering process takes sensors’ location and residual energy into consideration to elect suitable cluster heads. Furthermore, one mobile sink node is employed to access cluster heads in accordance with the data overflow time and moving time from cluster heads to itself. Related experimental results display that the presented method can avoid long distance communicate between sensor nodes. Furthermore, this algorithm reduces energy consumption effectively and improves package delivery rate.     

Enhanced Energy Efficient with a Trust Aware in MANET for Real-Time Applications

Mobile ad hoc networks (MANETs) are subjected to attack detection for transmitting and creating new messages or existing message modifications. The attacker on another node evaluates the forging activity in the message directly or indirectly. Every node sends short packets in a MANET environment with its identifier, location on the map, and time through beacons. The attackers on the network broadcast the warning message using faked coordinates, providing the appearance of a network collision. Similarly, MANET degrades the channel utilization performance. Performance highly affects network performance through security algorithms. This paper developed a trust management technique called Enhanced Beacon Trust Management with Hybrid Optimization (EBTM-Hyopt) for efficient cluster head selection and malicious node detection. It tries to build trust among connected nodes and may improve security by requiring every participating node to develop and distribute genuine, accurate, and trustworthy material across the network. Specifically, optimized cluster head election is done periodically to reduce and balance the energy consumption to improve the lifetime network. The cluster head election optimization is based on hybridizing Particle Swarm Optimization (PSO) and Gravitational Search Optimization Algorithm (GSOA) concepts to enable and ensure reliable routing. Simulation results show that the proposed EBTM-HYOPT outperforms the state-of-the-art trust model in terms of 297.99 kbps of throughput, 46.34% of PDR, 13% of energy consumption, 165.6 kbps of packet loss, 67.49% of end-to-end delay, and 16.34% of packet length.     

ECO-BAT: A New Routing Protocol for Energy Consumption Optimization Based on BAT Algorithm in WSN

Wireless sensor network (WSN) has been widely used due to its vast range of applications. The energy problem is one of the important problems influencing the complete application. Sensor nodes use very small batteries as a power source and replacing them is not an easy task. With this restriction, the sensor nodes must conserve their energy and extend the network lifetime as long as possible. Also, these limits motivate much of the research to suggest solutions in all layers of the protocol stack to save energy. So, energy management efficiency becomes a key requirement in WSN design. The efficiency of these networks is highly dependent on routing protocols directly affecting the network lifetime. Clustering is one of the most popular techniques preferred in routing operations. In this work we propose a novel energy-efficient protocol for WSN based on a bat algorithm called ECO-BAT (Energy Consumption Optimization with BAT algorithm for WSN) to prolong the network lifetime. We use an objective function that generates an optimal number of sensor clusters with cluster heads (CH) to minimize energy consumption. The performance of the proposed approach is compared with Low-Energy Adaptive Clustering Hierarchy (LEACH) and Energy Efficient cluster formation in wireless sensor networks based on the Multi-Objective Bat algorithm (EEMOB) protocols. The results obtained are interesting in terms of energy-saving and prolongation of the network lifetime.     

An Energy-Efficient Protocol Using an Objective Function & Random Search with Jumps for WSN

Wireless Sensor Networks (WSNs) have hardware and software limitations and are deployed in hostile environments. The problem of energy consumption in WSNs has become a very important axis of research. To obtain good performance in terms of the network lifetime, several routing protocols have been proposed in the literature. Hierarchical routing is considered to be the most favorable approach in terms of energy efficiency. It is based on the concept parent-child hierarchy where the child nodes forward their messages to their parent, and then the parent node forwards them, directly or via other parent nodes, to the base station (sink). In this paper, we present a new Energy-Efficient clustering protocol for WSNs using an Objective Function and Random Search with Jumps (EEOFRSJ) in order to reduce sensor energy consumption. First, the objective function is used to find an optimal cluster formation taking into account the ratio of the mean Euclidean distance of the nodes to their associated cluster heads (CH) and their residual energy. Then, we find the best path to transmit data from the CHs nodes to the base station (BS) using a random search with jumps. We simulated our proposed approach compared with the Energy-Efficient in WSNs using Fuzzy C-Means clustering (EEFCM) protocol using Matlab Simulink. Simulation results have shown that our proposed protocol excels regarding energy consumption, resulting in network lifetime extension.     

低时延能耗均衡的水声传感器网络簇间路由算法

针对水声传感器网络的簇间路由选择问题,提出了一种基于前向网关的低时延能耗均衡路由算法,该算法采用最优方向角原则和能耗均衡原则选择中继簇头和中继网关,以减小长延迟和高能耗对水声通信的影响。仿真结果表明该算法在网络平均能耗、端到端时延和网络生命周期等方面具有较好的性能。