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.

Reducing energy consumption optimization selection of path transmission routing algorithm in opportunistic networks

Opportunistic networks are random networks and do not communicate with each other among respective communication areas.This situation leads to great difficulty in message transfer.This paper proposes a reducing energy consumption optimal selection of path transmission(OSPT) routing algorithm in opportunistic networks.This algorithm designs a dynamic random network topology,creates a dynamic link,and realizes an optimized selected path.This algorithm solves a problem that nodes are unable to deliver messages for a long time in opportunistic networks.According to the simulation experiment,OSPT improves deliver ratio,and reduces energy consumption,cache time and transmission delay compared with the Epidemic Algorithm and Spray and Wait Algorithm in opportunistic networks.

Energy and Throughput Optimized, Cluster Based Hierarchical Routing Algorithm for Heterogeneous Wireless Sensor Networks

We propose a novel cluster based distributed routing algorithm in a generalized form for heterogeneous wireless sensor networks. Heterogeneity with respect to number/types of communication interfaces, their data rates and that with respect to energy dissipation model have been exploited for energy and throughput efficiency. The algorithm makes routing assignment optimized for throughput and energy and has a complexity of N/K*logN+k2logk approximately, where N is the number of nodes and k is the number of kcluster heads. Performance experiments confirm the effectiveness of throughput and energy optimizations. The importance of choosing an optimal cluster radius has been shown. The energy consumption in the network scales up well with respect to the network size.

LOA-RPL:Novel Energy-Efficient Routing Protocol for the Internet of Things Using Lion Optimization Algorithm to Maximize Network Lifetime

Energy conservation is a significant task in the Internet of Things(IoT)because IoT involves highly resource-constrained devices.Clustering is an effective technique for saving energy by reducing duplicate data.In a clustering protocol,the selection of a cluster head(CH)plays a key role in prolonging the lifetime of a network.However,most cluster-based protocols,including routing protocols for low-power and lossy networks(RPLs),have used fuzzy logic and probabilistic approaches to select the CH node.Consequently,early battery depletion is produced near the sink.To overcome this issue,a lion optimization algorithm(LOA)for selecting CH in RPL is proposed in this study.LOA-RPL comprises three processes:cluster formation,CH selection,and route establishment.A cluster is formed using the Euclidean distance.CH selection is performed using LOA.Route establishment is implemented using residual energy information.An extensive simulation is conducted in the network simulator ns-3 on various parameters,such as network lifetime,power consumption,packet delivery ratio(PDR),and throughput.The performance of LOA-RPL is also compared with those of RPL,fuzzy rule-based energyefficient clustering and immune-inspired routing(FEEC-IIR),and the routing scheme for IoT that uses shuffled frog-leaping optimization algorithm(RISARPL).The performance evaluation metrics used in this study are network lifetime,power consumption,PDR,and throughput.The proposed LOARPL increases network lifetime by 20%and PDR by 5%–10%compared with RPL,FEEC-IIR,and RISA-RPL.LOA-RPL is also highly energy-efficient compared with other similar routing protocols.

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.

A Novel Energy Efficient Routing Protocol in Wireless Sensor Networks

Wireless sensor networks are employed in several applications, including military, medical, environmental and household. In all these applications, energy usage is the determining factor in the performance of wireless sensor networks. Consequently, methods of data routing and transferring to the base station are very important because the sensor nodes run on battery power and the energy available for sensors is limited. In this paper we intend to propose a new protocol called Fair Efficient Location-based Gossiping (FELGossiping) to address the problems of Gossiping and its extensions. We show how our approach increases the network energy and as a result maximizes the network life time in comparison with its counterparts. In addition, we show that the energy is balanced (fairly) between nodes. Saving the nodes energy leads to an increase in the node life in the network, in comparison with the other protocols. Furthermore, the protocol reduces propagation delay and loss of packets.

Energy Aware Metaheuristic Optimization with Location Aided Routing Protocol for MANET

A mobile ad hoc network(MANET)involves a group of wireless mobile nodes which create an impermanent network with no central authority and infrastructure.The nodes in the MANET are highly mobile and it results in adequate network topology,link loss,and increase the re-initialization of the route discovery process.Route planning in MANET is a multi-hop communication process due to the restricted transmission range of the nodes.Location aided routing(LAR)is one of the effective routing protocols in MANET which suffers from the issue of high energy consumption.Though few research works have focused on resolving energy consumption problem in LAR,energy efficiency still remains a major design issue.In this aspect,this study introduces an energy aware metaheuristic optimization with LAR(EAMO-LAR)protocol for MANETs.The EAMO-LAR protocol makes use of manta ray foraging optimization algorithm(MRFO)to help the searching process for the individual solution to be passed to the LAR protocol.The fitness value of the created solutions is determined next to pass the solutions to the objective function.The MRFO algorithm is incorporated into the LAR protocol in the EAMO-LAR protocol to reduce the desired energy utilization.To ensure the improved routing efficiency of the proposed EAMO-LAR protocol,a series of simulations take place.The resultant experimental values pointed out the supreme outcome of the EAMO-LAR protocol over the recently compared methods.The resultant values demonstrated that the EAMO-LAR protocol has accomplished effectual results over the other existing techniques.

SIMULATED ANNEALING BASED POLYNOMIAL TIME QOS ROUTING ALGORITHM FOR MANETS

Multi-constrained Quality-of-Service (QoS) routing is a big challenge for Mobile Ad hoc Networks (MANETs) where the topology may change constantly. In this paper a novel QoS Routing Algorithm based on Simulated Annealing (SA_RA) is proposed. This algorithm first uses an energy function to translate multiple QoS weights into a single mixed metric and then seeks to find a feasible path by simulated annealing. The pa- per outlines simulated annealing algorithm and analyzes the problems met when we apply it to Qos Routing (QoSR) in MANETs. Theoretical analysis and experiment results demonstrate that the proposed method is an effective approximation algorithms showing better performance than the other pertinent algorithm in seeking the (approximate) optimal configuration within a period of polynomial time.

Distributed Multi-hop Clustering Approach with Low Energy Consumption in WSN

The purpose of sensing the environment and geographical positions,device monitoring,and information gathering are accomplished using Wireless Sensor Network(WSN),which is a non-dependent device consisting of a distinct collection of Sensor Node(SN).Thus,a clustering based on Energy Efficient(EE),one of the most crucial processes performed in WSN with distinct environments,is utilized.In order to efficiently manage energy allocation during sensing and communication,the present research on managing energy efficiency is performed on the basis of distributed algorithm.Multiples of EE methods were incapable of supporting EE routing with MIN-EC in WSN in spite of the focus of EE methods on energy harvesting and minimum Energy Consumption(EC).The three stages of performance are proposed in this research work.At the outset,during routing and Route Searching Time(RST)with fluctuating node density and PKTs,EC is reduced by the Hybrid Energy-based Multi-User Routing(HEMUR)model proposed in this work.Energy efficiency and an ideal route for various SNs with distinct PKTs in WSN are obtained by this model.By utilizing the Approximation Algorithm(AA),the Bregman Tensor Approximation Clustering(BTAC)is applied to improve the Route Path Selection(RPS)efficiency for Data Packet Transmission(DPT)at the Sink Node(SkN).The enhanced Network Throughput Rate(NTR)and low DPT Delay are provided by BTAC.To MAX the Clustering Efficiency(CE)and minimize the EC,the Energy Effective Distributed Multi-hop Clustering(GISEDC)method based on Generalized Iterative Scaling is implemented.The Multi-User Routing(MUR)is used by the HEMUR model to enhance the EC by 20%during routing.When compared with other advanced techniques,the Average Energy Per Packet(AEPP)is enhanced by 39%with the application of proportional fairness with Boltzmann Distribution(BD).The Gaussian Fast Linear Combinations(GFLC)with AA are applied by BTAC method with an enhanced Communication Overhead(COH)for an increase in performance by 19%and minimize the DPT delay by 23%.When compared with the rest of the advanced techniques,CE is enhanced by 8%and EC by 27%with the application of GISEDC method.

Energy Efficiency in ARQ-Based Multi-Hop Systems and the Tradeoff with Throughput

The minimum energy per bit(EPB)as the energy efficiency(EE)metric in an automatic retransmission request(ARQ)based multi-hop system is analyzed under power and throughput constraints.Two ARQ protocols including type-I(ARQ-I)and repetition redundancy(ARQ-RR)are considered and expressions for the optimal power allocation(PA)are obtained.Using the obtained optimal powers,the EE-throughput tradeoff(EETT)is analyzed and the EETT closed-form expressions for both ARQ protocols and in arbitrary average channel gain values are obtained.It is shown that how different throughput requirements,especially the high levels,affect the EE performance.Additionally,asymptotic analysis is made in the feasible high throughput values and lower and upper EETT bounds are derived for ARQ-I protocol.To evaluate the EE a distributed PA scenario,as a benchmark,is presented and the energy savinggain obtained from the optimal PA in comparison with the distributed PA for ARQ-I and ARQ-RR protocols is discussed in different throughput values and node locations.

BSDCH: New Chain Routing Protocol with Best Selection Double Cluster Head in Wireless Sensor Networks

The Optimum use of energy is one of the significant needs in wireless sensor networks, because sensor devices would usually use the battery power. In this article, we give the suggested routing algorithm (BSDCH) with determining an optimum routine due to the energy use and the number of passed hobs. To transfer date from nodes’ sensor to BS (Base Station), data sending has been utilized in chains. In BSDCH algorithm, the nodes’ space is divided into several regions. In this article, each part is called a cluster. In each cluster, a node which is the best due to energy and distance comparison with other cluster nodes it is continuously selected with a given Formula (4) which is called main CH (Cluster Head) and forms a chain in that cluster and in each node cluster, it is selected by Formula (5) as secondary CH with the least distance and the best situation to BS and main CH. the secondary CH task is to receive data from the main CH and send data to the BS. As far as the main cluster head would waste too much energy to send data to BS, so to send data through secondary CH, we can keep main CH energy for more time. In the time of sending data from nodes to main CH, a multi chain is utilized. In the time of making nodes’ chain, nods are connected straight into its main CH radius and other nodes are connected in their sending radius which would have the least distance to main CH. Finally, also, BSDCH has been compared with PEGASIS [1] and PDCH [2]. The simulation results are shown which are indicator of a better BSDCH performance.

An Energy-Efficient Multi-swarm Optimization in Wireless Sensor Networks

Wireless Sensor Networks are a group of sensors with inadequate power sources that are installed in a particular region to gather information from the surroundings.Designing energy-efficient data gathering methods in large-scale Wireless Sensor Networks(WSN)is one of the most difficult areas of study.As every sensor node has afinite amount of energy.Battery power is the most significant source in the WSN.Clustering is a well-known technique for enhan-cing the power feature in WSN.In the proposed method multi-Swarm optimiza-tion based on a Genetic Algorithm and Adaptive Hierarchical clustering-based routing protocol are used for enhancing the network’s lifespan and routing opti-mization.By using distributed data transmission modification,an adaptive hier-archical clustering-based routing algorithm for power consumption is presented to ensure continuous coverage of the entire area.To begin,a hierarchical cluster-ing-based routing protocol is presented in terms of balancing node energy con-sumption.The Multi-Swarm optimization(MSO)based Genetic Algorithms are proposed to select an efficient Cluster Head(CH).It also improves the network’s longevity and optimizes the routing.As a result of the study’sfindings,the pro-posed MSO-Genetic Algorithm with Hill climbing(GAHC)is effective,as it increases the number of clusters created,average energy expended,lifespan com-putation reduces average packet loss,and end-to-end delay.

优化聚类分簇结合自适应中继策略的双簇首WSNs路由算法

针对无线传感器网络中分簇路由算法节点能量利用率低、能量消耗不均匀等问题,提出了一种优化聚类分簇结合自适应中继策略的双簇首无线传感器网络路由算法.该算法对分簇路由协议中的三个阶段分别进行优化设计.成簇阶段,首先对双簇首模型下最优成簇规模与网络能耗的关系进行理论分析,然后使用改进的算术优化算法计算模糊C均值算法的初始聚类中心,提高了模糊C均值算法聚类成簇的准确率和鲁棒性.簇首选举阶段,引入双簇首策略,以节点的位置、能量和中心度为影响因子,根据承担任务的不同分别为内外簇首设计独立的簇首评价函数,以评价值为依据由节点分布式动态选举簇首减少了广播数量,同时可以将整个簇的能量负载平均分配到每个簇成员节点中.数据传输阶段,设置了多跳中继策略的距离适用条件,并以能量消耗速率为依据选择中继节点,避免了节点提前过载.仿真结果表明:在多种规模的网络中,该算法相较于对比算法在均衡网络负载、提高能量利用效率方面效果更好,从而延长了网络的有效感测时间.

基于扇形链路策略的改进蚁群分簇路由协议

针对网络覆盖区域较大、节点数量较多的无线传感器网络,容易出现部分节点过早死亡等情况,提出一种基于扇形链路策略的改进蚁群分簇路由协议RACO-SL。通过加入奖惩因子,同时对精英个体采用蚁群优化算法的概率生成新的后代个体,对于普通个体,通过与随机选择的精英个体进行交叉变异操作,改进蚁群优化算法,以整个网络每次通信的能耗为优化目标选取较优的簇头节点集。为待转发簇头节点设计从可动态调节的扇形区域中选择下一跳中继节点的链路转发策略。实验结果表明,与现有协议相比,该协议在延长网络寿命、提高通信链路质量、增强网络覆盖度方面表现良好。

卫星物联网中基于能量感知的自适应节能路由策略

随着5G技术的发展和6G技术的研究,低轨卫星网络在卫星物联网中的地位越发重要,而作为网络核心技术的路由策略仍面临一些挑战。本文针对低轨卫星网络拓扑结构动态变化、链路的不连续性、卫星能量供应受限等问题,为了及时感知星间链路状态和卫星的能量并选择正确的路由,将卫星物联网中的路由选择问题转化为马尔可夫决策过程下的最优策略问题,提出一种基于Dueling DQN(Dueling Deep Q Network)的自适应节能路由算法。该算法通过改进DQN中神经网络的架构,大幅度地提升了学习的效果。仿真结果表明,与传统的DQN算法相比,该算法能有效降低系统能耗,均衡网络负载,提高网络吞吐量。

无线传感器网络中一种基于聚合层次聚类的分簇路由算法

针对无线传感器网络中节点连接以及能量受限不足的问题,为了延长网络寿命,提出了一种基于AHC的分簇路由算法(HACCRA)。该算法首先运用AHC对网络节点分簇,接着为簇首选择、簇形成和路径构建分别定义了恰当的决策目标函数,运用能量阈值、提出距离阈值、并且路由过程优先考虑簇首节点之间的一对一连接,有效解决了路由算法中分簇和路由不衔接的问题。仿真结果表明,与JCR、ICR以及DCK-LEACH相比,HACCRA能够更好地实现网络节点的能耗均衡,保证网络数据传输的连接性,从而延长网络寿命。

基于双簇头的油气物联网节能路由算法

为延长油气物联网寿命,提出一种基于双簇头的油气物联网路由算法。该算法在簇头选举过程中充分考虑了传感器节点当前剩余能量、历史平均能量、节点与基站的距离、邻居节点密度以及节点与能量收集源的距离等因素,并在同一簇群中选举双簇头,同时在数据传输阶段提出一种新型路由方式以均衡簇头能耗。在引入能量采集技术的同时,采用了一种新型的节点工作模式切换策略。仿真实验表明,与传统算法相比,该算法能更有效地均衡网络能耗,延长网络寿命。

基于深广结合算法的迷宫机器人路径规划技术研究

针对矿井中复杂环境下巡检机器人存在路径规划能力较差、任务执行效率偏低的问题,文中将深度和广度路径搜索方法相结合,提出了一种机器人路径规划算法。通过深广融合得到A*路径规划算法,并将其作为全局路径规划的方法。对于算法中存在规划路径过长且平滑度较差的不足,使用人工势能法对局部路径加以优化,以提高路径规划的准确度。同时还利用贝塞尔曲线进行路径平滑操作,进而增强了算法的工程应用能力。实验测试结果表明,该算法在不同尺寸地图中的表现均较为良好,尤其是在大尺寸地图中,其规划的路径最短且运行时间缩短了20 ms以上,证明该算法具有较强的鲁棒性。

基于粒子群优化算法的无线传感器网络路由方法设计

为了减少无线传感网络能量消耗,并延长无线传感网络生命周期,设计基于粒子群优化算法的无线传感网络路由方法。构建无线传感器网络模型,初步划分无线传感器网络簇,通过自适应压缩因子粒子群算法获取传感网络最优簇首,簇首为成员性节点分配TDMA时隙,簇中各成员节点按各自所拥有TDMA时隙,向簇首发送数据信息,并由簇首执行有效数据融合操作后,把数据信息以簇间路由方式发送给基站。实验结果表明,该方法能够实现无线传感器网络路由,均衡无线传感器网络能量消耗,并延长其生命周期,为实际工作提供可靠依据与参考。

针对无线自组织网络的节能路由协议研究

无线自组织网络具有移动变换属性,传统静态路由协议存在丢包率大、传输时延长、网络吞吐量小的问题,因此提出了无线自组织网络的节能路由协议研究方法。确定路由请求标志符所在位置,综合考虑节点剩余能量,估算节点生存时间,发现存活节点。采用LEACH算法选举存活节点簇头,融合成数据形式。通过相邻节点区域分布方式,检测冗余节点,计算能量消耗,调度休眠冗余节点。从相邻簇头集合中选择最佳下一跳路径,充分考虑节点剩余能量,设计簇间多跳路由。由实验结果可知,该方法最高丢包率为2.3%,最长时延为9 ms,最大吞吐量为157 b/s,提高了网络可靠性。