Energy Efficient Load Balancing and Routing Using Multi-Objective Based Algorithm in WSN

In wireless sensor network(WSN),the gateways which are placed far away from the base station(BS)forward the collected data to the BS through the gateways which are nearer to the BS.This leads to more energy consumption because the gateways nearer to the BS manages heavy traffic load.So,to over-come this issue,loads around the gateways are to be balanced by presenting energy efficient clustering approach.Besides,to enhance the lifetime of the net-work,optimal routing path is to be established between the source node and BS.For energy efficient load balancing and routing,multi objective based beetle swarm optimization(BSO)algorithm is presented in this paper.Using this algo-rithm,optimal clustering and routing are performed depend on the objective func-tions routingfitness and clusteringfitness.This approach leads to decrease the power consumption.Simulation results show that the performance of the pro-posed BSO based clustering and routing scheme attains better results than that of the existing algorithms in terms of energy consumption,delivery ratio,through-put and network lifetime.Namely,the proposed scheme increases throughput to 72%and network lifetime to 37%as well as it reduces delay to 37%than the existing optimization algorithms based clustering and routing schemes.

SI-INSPIRED ENERGY AWARE QoS ROUTING TREE FOR WSN

A heuristic theoretical optimal routing algorithm （TORA） is presented to achieve the data-gathering structure of location-aided quality of service （QoS） in wireless sensor networks （WSNs）. The construction of TORA is based on a kind of swarm intelligence （SI） mechanism, i. e. , ant colony optimization. Firstly, the ener- gy-efficient weight is designed based on flow distribution to divide WSNs into different functional regions, so the routing selection can self-adapt asymmetric power configurations with lower latency. Then, the designs of the novel heuristic factor and the pheromone updating rule can endow ant-like agents with the ability of detecting the local networks energy status and approaching the theoretical optimal tree, thus improving the adaptability and en- ergy-efficiency in route building. Simulation results show that compared with some classic routing algorithms, TORA can further minimize the total communication energy cost and enhance the QoS performance with low-de- lay effect under the data-gathering condition.

Hybrid Marine Predators Optimization and Improved Particle Swarm Optimization-Based Optimal Cluster Routing in Wireless Sensor Networks(WSNs)

Wireless Sensor Networks(WSNs)play an indispensable role in the lives of human beings in the fields of environment monitoring,manufacturing,education,agriculture etc.,However,the batteries in the sensor node under deployment in an unattended or remote area cannot be replaced because of their wireless existence.In this context,several researchers have contributed diversified number of cluster-based routing schemes that concentrate on the objective of extending node survival time.However,there still exists a room for improvement in Cluster Head(CH)selection based on the integration of critical parameters.The meta-heuristic methods that concentrate on guaranteeing both CH selection and data transmission for improving optimal network performance are predominant.In this paper,a hybrid Marine Predators Optimization and Improved Particle Swarm Optimizationbased Optimal Cluster Routing(MPO-IPSO-OCR)is proposed for ensuring both efficient CH selection and data transmission.The robust characteristic of MPOA is used in optimized CH selection,while improved PSO is used for determining the optimized route to ensure sink mobility.In specific,a strategy of position update is included in the improved PSO for enhancing the global searching efficiency of MPOA.The high-speed ratio,unit speed rate and low speed rate strategy inherited by MPOA facilitate better exploitation by preventing solution from being struck into local optimality point.The simulation investigation and statistical results confirm that the proposed MPOIPSO-OCR is capable of improving the energy stability by 21.28%,prolonging network lifetime by 18.62%and offering maximum throughput by 16.79%when compared to the benchmarked cluster-based routing schemes.

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 vastrange of applications. The energy problem is one of the important problems influencingthe complete application. Sensor nodes use very small batteries as a powersource and replacing them is not an easy task. With this restriction, the sensornodes 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 alllayers of the protocol stack to save energy. So, energy management efficiencybecomes a key requirement in WSN design. The efficiency of these networks ishighly 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 batalgorithm called ECO-BAT (Energy Consumption Optimization with BAT algorithmfor WSN) to prolong the network lifetime. We use an objective function thatgenerates an optimal number of sensor clusters with cluster heads (CH) to minimizeenergy consumption. The performance of the proposed approach is comparedwith Low-Energy Adaptive Clustering Hierarchy (LEACH) and EnergyEfficient cluster formation in wireless sensor networks based on the Multi-Objective Bat algorithm (EEMOB) protocols. The results obtained are interestingin terms of energy-saving and prolongation of the network lifetime.

An Energy Balanced Reliable Routing Metric in WSNs

In WSNs’ applications, not only the reliable end-to-end communications are must be ensured, but also the reduction of energy consumption and the entire network’s lifetim e should be optimized. All of the above have become to be an important way to evaluate the performance of routing protocols. In this paper, an op-timization model for WSNs’ lifetime is firstly advanced. Secondly, the shortage of ETX based routing metric is solved with the help of the optimization model. Thirdly, an energy balanced routing metric is advanced which is called EBRM in this paper. The result of simulation in NS-2 shows that, the EBRM metric can not only prolong the network’s lifetime, but also can ensure the reliable end-to-end communication.

A Direct Trust dependent Link State Routing Protocol Using Route Trusts for WSNs (DTLSRP)

The traditional cryptographic security techniques are not sufficient for secure routing of message from source to destination in Wireless Sensor Networks (WSNs), because it requires sophisticated software, hardware, large memory, high processing speed and communication bandwidth. It is not economic and feasible because, depending on the application, WSN nodes are high-volume in number (hence, limited resources at each node), deployment area may be hazardous, unattended and/or hostile and sometimes dangerous. As WSNs are characterized by severely constrained resources and requirement to operate in an ad-hoc manner, security functionality implementation to protect nodes from adversary forces and secure routing of message from source node to base station has become a challenging task. In this paper, we present a direct trust dependent link state routing using route trusts which protects WSNs against routing attacks by eliminating the un-trusted nodes before making routes and finding best trustworthy route among them. We compare our work with the most prevalent routing protocols and show its benefits over them.

Adaptive Route Sink Relocation Using Cluster Head Chain Cycling Model in WSN

Wireless Sensor Networks(WSN)have revolutionized the processes involved in industrial communication.However,the most important challenge faced by WSN sensors is the presence of limited energy.Multiple research inves-tigations have been conducted so far on how to prolong the energy in WSN.This phenomenon is a result of inability of the network to have battery powered-sensor terminal.Energy-efficient routing on packetflow is a parallel phenomenon to delay nature,whereas the primary energy gets wasted as a result of WSN holes.Energy holes are present in the vicinity of sink and it is an important efficient-routing protocol for WSNs.In order to solve the issues discussed above,an energy-efficient routing protocol is proposed in this study named as Adaptive Route Decision Sink Relocation Protocol using Cluster Head Chain Cycling approach(ARDSR-CHC2H).The proposed method aims at improved communica-tion at sink-inviting routes.At this point,Cluster Head Node(CHN)is selected,since it consumes low energy and permits one node to communicate with others in two groups.The main purpose of the proposed model is to reduce energy con-sumption and define new interchange technology.A comparison of simulation results demonstrates that the proposed algorithm achieved low cluster creation time,better network error and high Packet Delivery Rate with less network failure.

基于深度学习的WSN入侵检测系统研究与设计

传统浅层机器学习难以提取现今随时间变化的高维且非线性的海量数据的本质特征,入侵检测准确率低,算法复杂且训练时间过长。对此,采用分簇式网络拓扑,改进NCRP算法的路由协议降低网络能耗,在簇头节点使用SAESM进行压缩且异常检测提高簇头节点传送给基站节点的有效信息量及快速有效响应,在基站使用SLSTM的高级检测算法进行精准识别攻击行为与类型。分析仿真实验结果此算法入侵检测准确率较高,泛化能力较强,实时性好。

一种能耗均衡的WSN高吞吐量路由协议研究

无线传感器网络(WSN)由若干个传感器节点通过多跳自组织的方式构成,这些节点的能量和处理能力都受到极大地限制,因此研究节能高效的路由协议具有较大的意义。为延长WSN的生存时间和提高网络吞吐量,提出了一种能耗均衡的WSN高吞吐量路由协议,该协议利用K⁃means聚类算法对节点进行分簇,并结合节点剩余能量和距离计算权重值,选择最佳节点作为簇首,此外,还利用无线收发器的参数和信道状况确定最佳固定分组大小。在数据传输阶段,使用Dijkstra算法计算多目标权重函数作为链路成本。实验结果表明该方案在网络节点节能方面优于CERP和TEEN路由协议,且提高了整个系统的吞吐量和生存时间。

Efficient Hybrid Energy Optimization Method in Location Aware Unmanned WSN

The growth of Wireless Sensor Networks(WSNs)has revolutionized thefield of technology and it is used in different application frameworks.Unmanned edges and other critical locations can be monitored using the navigation sensor node.The WSN required low energy consumption to provide a high network and guarantee the ultimate goal.The main objective of this work is to propose hybrid energy optimization in local aware environments.The hybrid proposed work consists of clustering,optimization,direct and indirect communication and routing.The aim of this research work is to provide and framework for reduced energy and trusted communication with the shortest path to reach source to destination in WSN and an extending lifetime of wireless sensors.The proposed Artificial Fish Swarm Optimization algorithm is used for energy optimization in military applications which is simulated using Network Simulator(NS)tool.This work optimizes the energy level and the same is compared with various genetic algorithms(GA)and also the cluster selection process was compared with thefission-fusion(FF)selection method.The results of the proposed work show,improvement in energy optimization,throughput and time delay.

基于铀尾矿库核素监测的WSN粒子群优化路由算法

为提高铀尾矿库无线传感器网络(WSN)现有路由算法的网络寿命,提出一种基于铀尾矿库核素监测的WSN粒子群优化路由算法(EBPSO)。首先,在簇头(CH)选举阶段,考虑传感器节点的能量、簇内节点距离、CH到基站的距离等参数,利用粒子群优化(PSO)算法选出最合理的CH,并将筛选出来的CH节点应用于铀尾矿库核素监测组建WSN;其次,在数据传输阶段,提出转发节点的选择方法;然后,用能量阈值重分簇方案来减少能量消耗;最后,对比基于PSO优化模糊C均值的分簇路由算法(POFCA)、低功耗自适应分簇(LEACH)以及高效非均匀分簇算法(EEUC)性能。结果表明:在网络生命周期上,EBPSO算法比POFCA、LEACH、EEUC分别提升1.7%、24.7%、9.2%。EBPSO算法能够延长网络生命周期,适用于铀尾矿库核素监测应用场景。

Fuzzy with Metaheuristics Based Routing for Clustered Wireless Sensor Networks

Wireless sensor network(WSN)plays a vital part in real time tracking and data collection applications.WSN incorporates a set of numerous sensor nodes(SNs)commonly utilized to observe the target region.The SNs operate using an inbuilt battery and it is not easier to replace or charge it.Therefore,proper utilization of available energy in the SNs is essential to prolong the lifetime of the WSN.In this study,an effective Type-II Fuzzy Logic with Butterfly Optimization Based Route Selection(TFL-BOARS)has been developed for clustered WSN.The TFL-BOARS technique intends to optimally select the cluster heads(CHs)and routes in the clustered WSN.Besides,the TFL-BOARS technique incorporates Type-II Fuzzy Logic(T2FL)technique with distinct input parameters namely residual energy(RE),link quality(LKQ),trust level(TRL),inter-cluster distance(ICD)and node degree(NDE)to select CHs and construct clusters.Also,the butterfly optimization algorithm based route selection(BOARS)technique is derived to select optimal set of routes in the WSN.In addition,the BOARS technique has computed afitness function using three parameters such as communication cost,distance and delay.In order to demonstrate the improved energy effectiveness and prolonged lifetime of the WSN,a wide-ranging simulation analysis was implemented and the experimental results reported the supremacy of the TFL-BOARS technique.

An improved evaporation rate water cycle algorithm for energy-efficient routing protocol in WSNs

Purpose-The paper aims to introduce an efficient routing algorithm for wireless sensor networks(WSNs).It proposes an improved evaporation rate water cycle(improved ER-WC)algorithm and outlining the systems performance in improving the energy efficiency of WSNs.The proposed technique mainly analyzes the clustering problem of WSNs when huge tasks are performed.Design/methodology/approach-This proposed improved ER-WC algorithm is used for analyzing various factors such as network cluster-head(CH)energy,CH location and CH density in improved ER-WCA.The proposed study will solve the energy efficiency and improve network throughput in WSNs.Findings-This proposed work provides optimal clustering method for Fuzzy C-means(FCM)where efficiency is improved in WSNs.Empirical evaluations are conducted to find network lifespan,network throughput,total network residual energy and network stabilization.Research limitations/implications-The proposed improved ER-WC algorithm has some implications when different energy levels of node are used in WSNs.Practical implications-This research work analyzes the nodes’energy and throughput by selecting correct CHs in intra-cluster communication.It can possibly analyze the factors such as CH location,network CH energy and CH density.Originality/value-This proposed research work proves to be performing better for improving the network throughput and increases energy efficiency for WSNs.

Directional Routing Algorithm for Deep Space Optical Network

With the development of science, economy and society, the needs for research and exploration of deep space have entered a rapid and stable development stage. Deep Space Optical Network(DSON) is expected to become an important foundation and inevitable development trend of future deepspace communication. In this paper, we design a deep space node model which is capable of combining the space division multiplexing with frequency division multiplexing. Furthermore, we propose the directional flooding routing algorithm(DFRA) for DSON based on our node model. This scheme selectively forwards the data packets in the routing, so that the energy consumption can be reduced effectively because only a portion of nodes will participate the flooding routing. Simulation results show that, compared with traditional flooding routing algorithm(TFRA), the DFRA can avoid the non-directional and blind transmission. Therefore, the energy consumption in message routing will be reduced and the lifespan of DSON can also be prolonged effectively. Although the complexity of routing implementation is slightly increased compared with TFRA, the energy of nodes can be saved and the transmission rate is obviously improved in DFRA. Thus the overall performance of DSON can be significantly improved.

WSNs中基于占空比间隔优化的延迟约束路由算法

针对WSNs中现有路由算法存在的各种不足,提出了一种基于占空比间隔优化的延迟约束路由算法;具体来说,在提出的算法中,首先,将端到端延迟分布估计为占空比间隔和潜在转发器数量的函数,在给定的网络模型和参数下,其分布可以近似地估计;然后,选择满足延迟约束成功率要求的占空比间隔最大值,每个节点独立地调度其休眠和唤醒时间,发送端节点将数据包转发给潜在转发器中最先唤醒的节点,从而确保数据包以要求的概率即DCSR到达接收器,同时最大化占空比间隔;仿真实验结果表明,提出的路由算法不仅能够满足要求的DSCR,并在ETE延迟、数据包交付率和实际得到的DCSR方面都优于现有的先进算法。

WSN中基于区域感知的改进AODV路由协议

AODV路由协议是无线自组网中的经典协议,适用于无线传感器网络(WSN)。但是该协议在路由发现阶段通过跳数建立路径,导致网络拥塞严重、部分节点过早失效以及活动路由频繁断裂,从而引起传输时延延长、路由开销增大、网络寿命缩短等问题。针对WSN中能量分布不均衡以及对邻居节点依赖性强的特点,提出基于区域感知的改进AODV路由协议。在路由发现阶段,引入QoS需求参数中的时延作为路径主权重,并计算区域变化率对路径主权重产生的正负增益,采用最优路径选择算法选取权重最小的路径,并将其作为最优路径。在路由维护阶段,通过计算区域能量和节点距离,丢弃区域中质量较差的节点,减少冗余拓扑和链路故障现象的发生。实验结果表明,相比传统的AODV协议,该协议的端到端时延和路由开销分别降低47.73%和48.00%,分组转发率和网络生存时间分别提升6.97%和14.80%。

一种新的基于WSNHC的安全路由机制研究

针对WSN中路由安全问题与传统安全路由算法之间的矛盾以及WSN的特点,通过采用WSNHC加密和认证,解决路由信息泄露、路由信息篡改、DoS攻击以及回放攻击问题。同时通过采取随机获取路由信息、中间节点应答以及优化路由等方法,解决WSN路由的效率问题。

TM-WSN模型的智能化设计

本文主要对TM-WSN模型采用了软件工程的方法进行了总体设计,并详细的对其智能化进行了设计阐述。

基于自适应粒子群优化的WSNs非均匀分簇路由算法

针对无线传感器网络(WSNs)中存在的能量空洞问题,提出了一种基于自适应粒子群优化(PSO)的WSNs非均匀分簇路由(APSO-NUCR)算法。在簇首选举阶段,引入一个能量阈值从网络中筛选出候选簇首,候选簇首根据竞争半径构造规模大小不一的簇。引入PSO算法来确定簇首,建立基于节点能量和位置的适应度函数,根据适应度值来确定最终簇首。根据粒子当前适应度值计算惯性权重和学习因子,更新速度和位置,平衡算法的全局和局部搜索能力。在数据传输阶段,簇内采用单跳传输方式,簇间数据传输基于Prim最小生成树的最优多跳路径。仿真结果表明:APSO-NUCR算法在利用能量和均衡网络能耗方面有良好的性能,延长了网络寿命。