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.

Cluster Head Selection and Multipath Routing Based Energy Efficient Wireless Sensor Network

The Wireless Sensor Network(WSN)is a network of Sensor Nodes(SN)which adopt radio signals for communication amongst themselves.There is an increase in the prominence of WSN adaptability to emerging applications like the Internet of Things(IoT)and Cyber-Physical Systems(CPS).Data secur-ity,detection of faults,management of energy,collection and distribution of data,network protocol,network coverage,mobility of nodes,and network heterogene-ity are some of the issues confronted by WSNs.There is not much published information on issues related to node mobility and management of energy at the time of aggregation of data.Towards the goal of boosting the mobility-based WSNs’network performance and energy,data aggregation protocols such as the presently-used Mobility Low-Energy Adaptive Clustering Hierarchy(LEACH-M)and Energy Efficient Heterogeneous Clustered(EEHC)scheme have been exam-ined in this work.A novel Artificial Bee Colony(ABC)algorithm is proposed in this work for effective election of CHs and multipath routing in WSNs so as to enable effective data transfer to the Base Station(BS)with least energy utilization.There is avoidance of the local optima problem at the time of solution space search in this proposed technique.Experimentations have been conducted on a large WSN network that has issues with mobility of nodes.

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.

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.

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。

物联网下的低功耗无线传感器网络路由技术研究

文章基于物联网下的低功耗无线传感器网络,重点研究一种优化的无线传感器网络通信协议,即基于K-means聚类的低能量自适应聚类层次协议(Low Energy Adaptive Clustering Hierarchy,LEACH)。通过对无线传感器网络结构的深入研究,提出一种新的聚类优化方法,以降低网络的总体能耗,并提高能耗均衡性。采用MATLAB进行仿真实验,验证所提优化方法的性能。实验结果表明,所提优化方法在总能耗、簇内能耗均衡性和数据传输成功率等方面均表现良好。为全面评估优化方法的性能,开展8次重复实验,通过分析平均值和标准差,验证实验结果的一致性和稳定性。

基于节点剩余能量和位置的无线传感网络分簇方法

针对分簇方法存在未考虑节点剩余能量、能耗效率低、网络生命周期短、造成节点过早死亡的问题,提出一种基于节点剩余能量和位置的无线传感网络分簇方法(RELCHP),该方法首先采用低功耗低时延协议分簇(LEACH),经稳定阶段后,再进行分簇;再分簇中,建立了节点剩余能量和位置阈值模型,根据该模型选取簇头,确定簇头节点后,广播消息给整个网络,非簇头节点按照接收到的各个簇头的广播消息信号的强弱,请求加入离自己最近的簇头;分簇结束,经稳定阶段后再按照该模型重新进行分簇,直至全部节点能量耗尽。通过OPNET仿真平台进行仿真实验,结果表明:与LEACH、LEACH-F分簇方法相比,该分簇方法的能耗效率比LEACH方法提高了19.4%,比LEACH-F方法提高了8.3%;网络生命周期比LEACH方法提高了29.6%,比LEACH-F方法提高了9.5%。

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。

An Optimized Novel Trust-Based Security Mechanism Using Elephant Herd Optimization

Routing strategies and security issues are the greatest challenges in Wireless Sensor Network(WSN).Cluster-based routing Low Energy adaptive Clustering Hierarchy(LEACH)decreases power consumption and increases net-work lifetime considerably.Securing WSN is a challenging issue faced by researchers.Trust systems are very helpful in detecting interfering nodes in WSN.Researchers have successfully applied Nature-inspired Metaheuristics Optimization Algorithms as a decision-making factor to derive an improved and effective solution for a real-time optimization problem.The metaheuristic Elephant Herding Optimizations(EHO)algorithm is formulated based on ele-phant herding in their clans.EHO considers two herding behaviors to solve and enhance optimization problem.Based on Elephant Herd Optimization,a trust-based security method is built in this work.The proposed routing selects routes to destination based on the trust values,thus,finding optimal secure routes for transmitting data.Experimental results have demonstrated the effectiveness of the proposed EHO based routing.The Average Packet Loss Rate of the proposed Trust Elephant Herd Optimization performs better by 35.42%,by 1.45%,and by 31.94%than LEACH,Elephant Herd Optimization,and Trust LEACH,respec-tively at Number of Nodes 3000.As the proposed routing is efficient in selecting secure routes,the average packet loss rate is significantly reduced,improving the network’s performance.It is also observed that the lifetime of the network is enhanced with the proposed Trust Elephant Herd Optimization.

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.

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。

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。

一种基于LEACH的能耗均衡多跳路由算法

针对LEACH协议中簇头选择的不合理以及多个簇头与基站远距离通信能量消耗过多的问题,提出一种新的能耗均衡的多跳路由算法.在簇头数最优的前提下,充分考虑节点的能量和位置因素,结合PEGASIS协议中节点成链思想构造簇头间的多跳路由,最后由链上担任Leader的节点完成与基站的数据通信.NS2仿真实验表明,与LEACH和LEACH-C相比,该算法能更好的优化簇的结构,均衡网络能耗,延长网络生命周期.

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.

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。