Effective data transmission through energy-efficient clustering and Fuzzy-Based IDS routing approach in WSNs

Wireless sensor networks(WSN)gather information and sense information samples in a certain region and communicate these readings to a base station(BS).Energy efficiency is considered a major design issue in the WSNs,and can be addressed using clustering and routing techniques.Information is sent from the source to the BS via routing procedures.However,these routing protocols must ensure that packets are delivered securely,guaranteeing that neither adversaries nor unauthentic individuals have access to the sent information.Secure data transfer is intended to protect the data from illegal access,damage,or disruption.Thus,in the proposed model,secure data transmission is developed in an energy-effective manner.A low-energy adaptive clustering hierarchy(LEACH)is developed to efficiently transfer the data.For the intrusion detection systems(IDS),Fuzzy logic and artificial neural networks(ANNs)are proposed.Initially,the nodes were randomly placed in the network and initialized to gather information.To ensure fair energy dissipation between the nodes,LEACH randomly chooses cluster heads(CHs)and allocates this role to the various nodes based on a round-robin management mechanism.The intrusion-detection procedure was then utilized to determine whether intruders were present in the network.Within the WSN,a Fuzzy interference rule was utilized to distinguish the malicious nodes from legal nodes.Subsequently,an ANN was employed to distinguish the harmful nodes from suspicious nodes.The effectiveness of the proposed approach was validated using metrics that attained 97%accuracy,97%specificity,and 97%sensitivity of 95%.Thus,it was proved that the LEACH and Fuzzy-based IDS approaches are the best choices for securing data transmission in an energy-efficient manner.

Research on Improved Low-Energy Adaptive Clustering Hierarchy Protocol in Wireless Sensor Networks

In wireless sensor networks(WSNs), due to the limited battery power of the sensor nodes, the communication energy consumption is the main factor to affect the lifetime of the networks. A reasonable design of the communication protocol can effectively reduce the energy consumption of the network system. Based on low-energy adaptive clustering hierarchy(LEACH), an improved LEACH protocol in WSNs is proposed. In order to optimize the cluster head(CH) election in the cluster setup phase, the improved LEACH takes into account a number of factors, including energy consumption of communication between nodes, remaining energy of the nodes,and the distance between nodes and base station(BS). In the steady phase, one-hop routing and multiple-hop routing are combined to transmit data between CHs to improve energy efficiency. The forward CH is selected as relay node according to the values of path cost. The simulation results show that the proposed algorithm performs better in balancing network energy consumption, and it can effectively improve the data transmission efficiency and prolong the network lifetime, as compared with LEACH, LEACH-C(LEACH-centralized) and NDAPSO-C(an adaptive clustering protocol based on improved particle swarm optimization) algorithms.

Two-Level Linear Clustering Protocol Based on Wireless Sensor Networks

Aiming at the defects of the nodes in the low energy adaptive clustering hierarchy （LEACH） protocol, such as high energy consumption and uneven energy consumption, a two-level linear clustering protocol is built. The protocol improves the way of the nodes distribution at random. The terminal nodes which have not been a two-level cluster head in the cluster can compete with the principle of equivalent possibility, and on the basis of the rest energy of nodes the two-level cluster head is selected at last. The single hop within the cluster and single hop or multiple hops between clusters are used. Simulation experiment results show that the performance of the two-level linear clustering protocol applied to the Hexi corridor agricultural field is superior to that of the LEACH protocol in the survival time of network nodes, the ratio of success, and the remaining energy of network nodes.

An Efficient Key Management Protocol for Wireless Sensor Networks

Key management is a fundamental security service in wireless sensor networks. The communication security problems for these networks are exacerbated by the limited power and energy of the sensor devices. In this paper, we describe the design and implementation of an efficient key management scheme based on low energy adaptive clustering hierarchy（LEACH） for wireless sensor networks. The design of the protocol is motivated by the observation that many sensor nodes in the network play different roles. The paper presents different keys are set to the sensors for meeting different transmitting messages and variable security requirements. Simulation results show that our key management protocol based-on LEACH can achieve better performance. The energy consumption overhead introduced is remarkably low compared with the original Kerberos schemes.

A Distributed Clustering Algorithm for Wireless Sensor Networks

In the paper, we consider a network of energy constrained sensors deployed over a region. Each sensor node in such a network is systematically gathering and transmitting sensed data to a base station （via clusterhead） for further processing. The key problem focuses on how to reduce the power consumption of wireless microsensor networks. The core includes the energy efficiency of clusterheads and that of cluster members. We first extend low-energy adaptive clustering hierarchy （LEACH）＇s stochastic clusterhead selection algorithm by a factor with distance-based deterministic component （LEACH-D） to reduce energy consumption for energy efficiency of clusterhead. And the cost function is proposed so that it balances the energy consumption of nodes for energy efficiency of cluster member. Simulation results show that our modified scheme can extend the network life around up to 40% before first node dies. Through both theoretical analysis and numerical results, it is shown that the proposed algorithm achieves better performance than the existing representative methods.

基于LEACH协议的能量优化方法

针对低功耗自适应聚类协议产生的整体能耗不均及网络生命周期短的问题,提出一种改进的能量优化方法。结合能量模型、节点发送及融合数据的综合能耗计算簇头比例;利用节点剩余能量与节点基站间的距离,优化成簇阶段中簇头选取阈值公式。在普通节点入簇阶段,引入簇规模密度,避免簇规模差距过大,采用就近原则与簇密度规模更新簇头。在数据传输阶段,引入“热区”边界对簇头分类,不同类簇头采用不同的数据传输方式。仿真结果表明,所提方法能均衡网络能耗且延长网络生命周期。

Accelerated Particle Swarm Optimization Algorithm for Efficient Cluster Head Selection in WSN

Numerous wireless networks have emerged that can be used for short communication ranges where the infrastructure-based networks may fail because of their installation and cost.One of them is a sensor network with embedded sensors working as the primary nodes,termed Wireless Sensor Networks(WSNs),in which numerous sensors are connected to at least one Base Station(BS).These sensors gather information from the environment and transmit it to a BS or gathering location.WSNs have several challenges,including throughput,energy usage,and network lifetime concerns.Different strategies have been applied to get over these restrictions.Clustering may,therefore,be thought of as the best way to solve such issues.Consequently,it is crucial to analyze effective Cluster Head(CH)selection to maximize efficiency throughput,extend the network lifetime,and minimize energy consumption.This paper proposed an Accelerated Particle Swarm Optimization(APSO)algorithm based on the Low Energy Adaptive Clustering Hierarchy(LEACH),Neighboring Based Energy Efficient Routing(NBEER),Cooperative Energy Efficient Routing(CEER),and Cooperative Relay Neighboring Based Energy Efficient Routing(CR-NBEER)techniques.With the help of APSO in the implementation of the WSN,the main methodology of this article has taken place.The simulation findings in this study demonstrated that the suggested approach uses less energy,with respective energy consumption ranges of 0.1441 to 0.013 for 5 CH,1.003 to 0.0521 for 10 CH,and 0.1734 to 0.0911 for 15 CH.The sending packets ratio was also raised for all three CH selection scenarios,increasing from 659 to 1730.The number of dead nodes likewise dropped for the given combination,falling between 71 and 66.The network lifetime was deemed to have risen based on the results found.A hybrid with a few valuable parameters can further improve the suggested APSO-based protocol.Similar to underwater,WSN can make use of the proposed protocol.The overall results have been evaluated and compared with the existing approaches of sensor networks.

基于非均匀分簇的无线传感器网络分层路由协议

针对大规模无线传感器网络(WSN)中由于簇首节点分布不合理而导致节点消耗能量过快的问题,设计了一种基于非均匀分簇的无线传感器网络分层路由协议(HRPNC)。HRPNC结合低功耗自适应集簇分层型协议(LEACH)中的分簇思想,并在分层的基础上对能量均衡的无线传感器网络非均匀分簇路由协议(DEBUC)中竞争半径的算法进行改进,即通过分层机制及竞争机制选取簇首,使簇首节点分布更加合理,有效均衡节点的能量消耗。在Matlab上进行的仿真实验中,HRPNC在生存周期上较LEACH协议与DEBUC协议分别提高了约500轮、300轮;HRPNC的节点平均剩余能量高于LEACH协议与DEBUC协议,节点能量的消耗在生存周期间基本保持较低且平稳的能量消耗;HRPNC较LEACH协议与DEBUC协议在数据包传输总量上分别提高了约300%、130%;在不同仿真环境下,HRPNC的丢包率均比LEACH协议和DEBUC协议低。实验结果表明,HRPNC不仅能有效延长网络的生存周期,提高数据的传输数量与网络的稳定性,并且能有效降低数据传输的丢包率。

一种新的基于分簇的无线传感器网络多跳节能路由协议

针对在LEACH(low energy adaptive clustering hierarchy)协议中,所有节点均通过一跳通信将数据传输到簇头节点使簇头能耗太大而过快衰竭死亡的问题,提出了一种新的分簇的无线传感器网络多跳节能路由协议.簇头之间采用多跳方式将数据传送到基站,避免了单跳通信簇头节点能量消耗过大的问题.利用NS-2(networksimulator-version 2)的仿真结果表明该算法优于LEACH,能有效地降低节点的能耗,延长网络生命周期.

基于LEACH协议的簇头选举改进算法

以减小LEACH协议簇形成过程中的能量消耗为目的,提出一种改进的簇头选举算法LEACH-ECHC。当所有簇头的剩余能量最小值小于某个阈值时,进行全网选举;当簇头能量小于该簇剩余能量的平均值时,进行簇内选举,并对簇头产生的阈值进行优化。仿真结果显示,LEACH-ECHC算法有更高的能量有效性,可以延长网络寿命,使节点能耗更均衡。

LEACH-EE——基于LEACH协议的高效聚类路由算法

为延缓传感器网络寿命,减少能量的消耗,提出一种基于LEACH协议的高效聚类路由算法(LEACH-EE)。它通过簇头来收集数据,然后簇头之间形成一个多跳的通向基站的最优路径,最后数据融合给一个簇头传给基站。这样解决了LEACH协议的簇头节点负载过重的问题,以及改善了网络能量的消耗和网络的生存时间。实验证明此方法行之有效。

基于LEACH和PEGASIS的簇头成链可靠路由协议研究

减少能耗、延长网络寿命是无线传感网络的关键技术。基于LEACH和PEGASIS算法,提出一种改进的有效路由算法。改进的算法规定LEACH中簇头数目为5个,利用PEGASIS算法使簇头成链,并选择剩余能量最多的簇头传送信息给基站。在选择簇头时,考虑节点的剩余能量,给节点设置一个能量阈值,小于该值则不能当选为簇头,因此提高了网络的健壮性。理论分析和仿真结果表明,改进后的算法比LEACH算法生命周期提高117%~351%,且能耗更加均匀,同时与PEGASIS相比,时延提高290%。

无线传感器网络簇头半径自适应调节路由算法

针对LEACH(low energy adaptive clustering hierarchy)算法以随机概率轮选簇头,存在簇头分布不均匀、簇头数量波动大以及簇头选取时未考虑节点剩余能量等问题,提出簇头半径自适应层次型路由算法(cluster-head range adaptive adjustment clus-tering routing,CRACR),引入节点剩余能量作为权重因子选取簇头,采用自适应调节机制控制簇头广播消息的广播半径大小,根据节点的位置和剩余能量分配时隙。通过仿真实验,结果表明CRACR算法的第1个节点死亡"回合"数比LEACH提高了55%以上,节能性能得到了明显的提高。

基于最佳簇数的无线传感器网络粒子群分簇协议

对层簇式无线传感器网络中的分簇协议进行了探讨。研究了经典的LEACH协议,分析了其缺陷,并提出了ILEACH协议。ILEACH协议首先按照一定的原则来计算最佳簇数目,并以此作为分簇的目标。簇重组阶段选择新簇首时,兼顾了节点的剩余能量与位置分布两个因素,并采用粒子群优化算法来计算,取得了较好的结果。仿真表明,ILEACH协议有效的节省了能量,延长了网络的生存时间。

一种能耗均衡的无线传感器网络分簇算法

以无线传感器网络中的LEACH和HEED分簇算法为背景,提出一种基于能耗均衡的自适应网络分簇算法EBACA。算法的主要特点是传感器节点根据自身状态信息自主竞争簇头,簇头选择标准考虑了随机概率与节点剩余能量结合,并引入了节点能量预测和能量阈值;为均衡各个节点的能耗,通过重新规划时间片来调节节点的工作频率;为减少簇头的能量开销,簇头之间通过多跳方式将各个簇内收集到的数据发送给特定簇首节点,并由此簇首节点将整个网络收集的数据发送给基站。设计的目标是均衡网络能耗,进而最大化网络寿命。分析和仿真结果表明,相对于几种重要的分簇算法,如LEACH和HEED,EBACA在平衡节点能量消耗和延长网络寿命方面具有更优越的性能。

基于双簇头聚类分簇和数据融合的无线传感器网络路由算法

针对无线传感器网络中基于低能量自适应聚类层次(LEACH)算法进行分簇时出现的簇分布不均匀及路由能量消耗过快问题,提出一种基于双簇头聚类和数据融合的分簇算法.该算法在分好的簇中选择两个级别的簇头,两个簇头履行不同职责,能更好地均摊能量消耗,提高了分簇均匀性.仿真实验结果表明,该算法降低了网络能耗,提升了网络生命周期.

无线传感器网络LEACH协议的改进

延长传感器网络的生存周期,降低传感器节点的能耗成为无线传感器网络(WSN)研究的重点。基于LEACH协议中簇头生成算法提出了改进、调整节点竞选簇头的阀值函数,并在非簇头节点选择适合自己的最优簇头时综合考虑了候选簇头节点的剩余能量以及距基站的距离等因素,给出了新的成簇机制的适合因子的计算公式。仿真结果表明,新型簇首选择机制能够有效平衡节点的能耗分布,延长节点与网络的寿命。

基于LEACH协议的水产养殖参数智能监控系统

提出了基于LEACH(Low energy adaptive clustering hierarchy)协议的水产养殖溶解氧参数低功耗无线测量网络和溶解氧浓度的智能变频控制技术。无线传感网络中簇首对测量节点的数据先进行融合,然后发送到基站。针对水体溶解氧参数变化缓慢的特点,规定在每一帧内变化小于0.1 mg/L时,不再向簇首发送数据。簇首调整各节点在该帧内数据发送时隙,延长簇首和节点的休眠时间,降低了功耗。PLC根据溶解氧参数的变化一方面通过变频器控制叶轮增氧机,在白天水体溶解氧质量浓度大于5.0 mg/L时,叶轮增氧机低速'耕水',充分利用自然界的风能、光能和藻类的光合作用改善水质;另一方面当溶解氧质量浓度低于5.0 mg/L下限时,采用模糊变频控制迅速缩小误差,在接近控制目标后,变频器输出稳定。通过试验验证,相对于人工粗略控制,节约电能42.3%以上,产量提高11.8%,综合经济收益提高41.3%。

无线传感器网络LEACH路由协议研究与改进

针对LEACH算法随机选取簇头,未考虑节点剩余能量及单跳与sink节点通信造成能量损耗过快的问题。引入以剩余能量及邻居节点数作为权重因子的时间等候簇头竞争模式选取簇头,并提出LEACH与蚁群算法相结合建立簇间路由机制,采用局部信息素更新,综合簇头节点的剩余能量及节点距离,为簇首与sink节点通信建立多跳路由,达到降低簇头节点能耗过快的目的。仿真实验结果表明,改进算法在降低能耗、延长网络生命周期等方面较LEACH算法有较大提高。

WSN中一种基于LEACH协议的改进算法

在无线传感器网络(wireless sensor network,WSN)中P,如何解决漏斗效应、有效平衡节点的能量分布,是延长网络生存时间的关键问题.针对漏斗效应提出一种基于低功耗自适应集簇分层型(1ow energy adaptive clusteringhierarchy,LEACH)协议的改进簇首控制算法(cluster control based on LEACH,CC-LEACH),通过sink辅助选择簇首分布.仿真证明,这种新型簇首选择机制能更好地进行能量均衡,延长网络生命周期.