Energy-Efficient Routing Using Novel Optimization with Tabu Techniques for Wireless Sensor Network

Wireless Sensor Network(WSN)consists of a group of limited energy source sensors that are installed in a particular region to collect data from the environment.Designing the energy-efficient data collection methods in largescale wireless sensor networks is considered to be a difficult area in the research.Sensor node clustering is a popular approach for WSN.Moreover,the sensor nodes are grouped to form clusters in a cluster-based WSN environment.The battery performance of the sensor nodes is likewise constrained.As a result,the energy efficiency of WSNs is critical.In specific,the energy usage is influenced by the loads on the sensor node as well as it ranges from the Base Station(BS).Therefore,energy efficiency and load balancing are very essential in WSN.In the proposed method,a novel Grey Wolf Improved Particle Swarm Optimization with Tabu Search Techniques(GW-IPSO-TS)was used.The selection of Cluster Heads(CHs)and routing path of every CH from the base station is enhanced by the proposed method.It provides the best routing path and increases the lifetime and energy efficiency of the network.End-to-end delay and packet loss rate have also been improved.The proposed GW-IPSO-TS method enhances the evaluation of alive nodes,dead nodes,network survival index,convergence rate,and standard deviation of sensor nodes.Compared to the existing algorithms,the proposed method outperforms better and improves the lifetime of the network.

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.

Performance Analysis of an Enhanced Load Balancing Scheme for Wireless Sensor Networks

Research interest in sensor networks routing largely considers minimization of energy consumption as a major performance criterion to provide maximum sensors network lifetime. When considering energy conservation, routing protocols should also be designed to achieve fault tolerance in communications. Moreover, due to dynamic topology and random deployment, incorporating reliability into protocols for WSNs is very important. Hence, we propose an improved scalable clustering-based load balancing scheme (SCLB) in this paper. In SCLB scheme, scalability is achieved by dividing the network into overlapping multihop clusters each with its own cluster head node. Simulation results show that the proposed scheme achieves longer network lifetime with desirable reliability at the initial state compare with the existing multihop load balancing approach.

Node deployment strategy optimization for wireless sensor network with mobile base station

The optimization of network performance in a movement-assisted data gathering scheme was studied by analyzing the energy consumption of wireless sensor network with node uniform distribution. A theoretically analytical method for avoiding energy hole was proposed. It is proved that if the densities of sensor nodes working at the same time are alternate between dormancy and work with non-uniform node distribution. The efficiency of network can increase by several times and the residual energy of network is nearly zero when the network lifetime ends.

Improved Routing in Wireless Sensor Networks Using Harmony Search Algorithm

One of the most important issues of wireless sensor networks is how to transfer information from the network nodes to a base station and choose the best possible path for this purpose. Choosing the best path can be based on different factors such as energy consumption, response time, delay, and data transfer accuracy. Increasing the network lifetime is the most challenging problem. One of the latest energy-aware routing methods is to use the harmony search algorithm in the small-scale sensor networks. The aim of this study is to introduce the harmony search algorithm as a successful metaheuristic algorithm for wireless sensor network routing in order to increase the lifetime of such networks. This study is intended to improve the objective function for energy efficiency in the harmony search algorithm to establish balance between the network energy consumption and path length control. Therefore, it is necessary to choose the initial energy of each node randomly from a certain range as the path energy consumption should be low to choose a path which can consider the residual energy. In other words, a path should be chosen to establish balance between the network energy consumption and the minimum residual energy. The simulation results indicate that the proposed objective function provides a longer lifetime by 26.12% compared with EEHSBR.

Wireless Network Security Using Load Balanced Mobile Sink Technique

Real-time applications based on Wireless Sensor Network(WSN)tech-nologies are quickly increasing due to intelligent surroundings.Among the most significant resources in the WSN are battery power and security.Clustering stra-tegies improve the power factor and secure the WSN environment.It takes more electricity to forward data in a WSN.Though numerous clustering methods have been developed to provide energy consumption,there is indeed a risk of unequal load balancing,resulting in a decrease in the network’s lifetime due to network inequalities and less security.These possibilities arise due to the cluster head’s limited life span.These cluster heads(CH)are in charge of all activities and con-trol intra-cluster and inter-cluster interactions.The proposed method uses Lifetime centric load balancing mechanisms(LCLBM)and Cluster-based energy optimiza-tion using a mobile sink algorithm(CEOMS).LCLBM emphasizes the selection of CH,system architectures,and optimal distribution of CH.In addition,the LCLBM was added with an assistant cluster head(ACH)for load balancing.Power consumption,communications latency,the frequency of failing nodes,high security,and one-way delay are essential variables to consider while evaluating LCLBM.CEOMS will choose a cluster leader based on the influence of the fol-lowing parameters on the energy balance of WSNs.According to simulatedfind-ings,the suggested LCLBM-CEOMS method increases cluster head selection self-adaptability,improves the network’s lifetime,decreases data latency,and bal-ances network capacity.

Energy-Efficient Routing Protocol with Multi-Hop Fuzzy Logic for Wireless Networks

A Wireless Sensor Network(WSN)becomes a newer type of real-time embedded device that can be utilized for a wide range of applications that make regular networking which appears impracticable.Concerning the energy produc-tion of the nodes,WSN has major issues that may influence the stability of the system.As a result,constructing WSN requires devising protocols and standards that make the most use of constrained capacity,especially the energy resources.WSN faces some issues with increased power utilization and an on going devel-opment due to the uneven energy usage between the nodes.Clustering has proven to be a more effective strategy in this series.In the proposed work,a hybrid meth-od is used for reducing the energy consumption among CHs.A Fuzzy Logic-based clustering protocol FLUC(unequally clustered)and Fuzzy Clustering with Energy-Efficient Routing Protocol(FCERP)are used.A Fuzzy Clustering with Energy Efficient Routing Protocol(FCERP)reduces the WSN power usage and increases the lifespan of the network.FCERP has created a novel cluster-based fuzzy routing mechanism that uses a limit value to combine the clustering and multi-hop routing capabilities.The technique creates uneven groups by using fuz-zy logic with a competitive range to choose the Cluster Head(CH).The input variables include the distance of the nodes from the ground station,concentra-tions,and remaining energy.The proposed FLUC-FCERP reduces the power usage and improves the lifetime of the network compared with the existing algorithms.

Improved Load-Balanced Clustering for Energy-Aware Routing(ILBC-EAR)in WSNs

Sensors are considered as important elements of electronic devices.In many applications and service,Wireless Sensor Networks(WSNs)are involved in significant data sharing that are delivered to the sink node in energy efficient man-ner using multi-hop communications.But,the major challenge in WSN is the nodes are having limited battery resources,it is important to monitor the consumption rate of energy is very much needed.However,reducing energy con-sumption can increase the network lifetime in effective manner.For that,clustering methods are widely used for optimizing the rate of energy consumption among the sensor nodes.In that concern,this paper involves in deriving a novel model called Improved Load-Balanced Clustering for Energy-Aware Routing(ILBC-EAR),which mainly concentrates on optimal energy utilization with load-balanced process among cluster heads and member nodes.For providing equal rate of energy consumption among nodes,the dimensions of framed clusters are measured.Moreover,the model develops a Finest Routing Scheme based on Load-Balanced Clustering to transmit the sensed information to the sink or base station.The evaluation results depict that the derived energy aware model attains higher rate of life time than other works and also achieves balanced energy rate among head node.Additionally,the model also provides higher throughput and minimal delay in delivering data packets.

MimiBS： Mimicking Base-Station to Provide Location PrivacyProtection in Wireless Sensor Networks

In a wireless sensor network (WSN), sink node/base station (BS) gathers data from surrounding nodes and sends them to a remote server via a gateway. BS holds important data. Therefore, it is necessary to hide its location from an inside/outside attacker. Providing BS location anonymity against a local and global adversary, we propose a novel technique called MimiBS 'Mimicking Base-Station'. The key idea is the integration of aggregator nodes (ANs) with sensor nodes (SNs), while fine tuning TTL (time to live) value for fake packets, and setting some threshold value for real packet counter rpctr. MimiBS creates multiple traffic-hotspots (zones), which shifts the focus from BS to the newly created ANs hotspots. Multiple traffic-hotspots confuse the adversary while determining the real BS location information. We defend the BS location information anonymity against traffic analysis attack, and traffic tracing attack. MimiBS gives an illusion of having multiple BSs, and thus, if the attacker knows any about AN, he/she will be deceived between the real BS and ANs. MimiBS outperforms BLAST (base-station location anonymity and security technique), RW (random walk), and SP (shortest path), while conducting routing without fake packets, with fake packets, without energy consideration, and with energy consideration respectively.

Balancing the Power Consumption Speed in Flat and Hierarchical WSN

A combination of a cluster tree routing protocol and an Ad hoc on demand vector (AODV) routing protocol is used in the latest ZigBee standard wireless sensor networks (WSNs) technology.However,the AODV routing protocol has no means by which to take into consideration the power consumption of the nodes during the routing process.Therefore,a new approach is proposed in this paper to balance the power consumption speed and to distribute the responsibilities of routing among flat wireless sensor nodes and the three levels of hierarchical wireless sensor nodes.These three levels are based on the three types of devices,which are used in the ZigBee standard:the coordinator,the routers,and the end devices.In this paper,we have compared the original AODV routing protocol with our extension approach for the distribution of power consumption.Based on the simulation results,our new approach has achieved better performance in terms of increasing the lifetime of the flat wireless sensor network,the personal area network (PAN) coordinator,the routers,and the whole network of the hierarchical wireless sensor network.Additionally,it has better performance in terms of distributing the power consumption among the key nodes of the wireless sensor network.

Energy-Efficient Clustering Using Optimization with Locust Game Theory

Wireless sensor networks(WSNs)are made up of several sensors located in a specific area and powered by a finite amount of energy to gather environmental data.WSNs use sensor nodes(SNs)to collect and transmit data.However,the power supplied by the sensor network is restricted.Thus,SNs must store energy as often as to extend the lifespan of the network.In the proposed study,effective clustering and longer network lifetimes are achieved using mul-ti-swarm optimization(MSO)and game theory based on locust search(LS-II).In this research,MSO is used to improve the optimum routing,while the LS-II approach is employed to specify the number of cluster heads(CHs)and select the best ones.After the CHs are identified,the other sensor components are allo-cated to the closest CHs to them.A game theory-based energy-efficient clustering approach is applied to WSNs.Here each SN is considered a player in the game.The SN can implement beneficial methods for itself depending on the length of the idle listening time in the active phase and then determine to choose whether or not to rest.The proposed multi-swarm with energy-efficient game theory on locust search(MSGE-LS)efficiently selects CHs,minimizes energy consumption,and improves the lifetime of networks.The findings of this study indicate that the proposed MSGE-LS is an effective method because its result proves that it increases the number of clusters,average energy consumption,lifespan extension,reduction in average packet loss,and end-to-end delay.

Architecture Design of an Integrated Communication and Broadcasting Network

Due to the power limitation of nodes in wire-less sensor networks (WSNs), how to maximize network lifetime has become a critical issue for deployment of WSNs. Although several schemes have been proposed for 2D WSNs, few for 3D WSNs are known. In this paper, we present a scheme to maximize network lifetime for 3D WSNs through balancing energy consumption, as an extension of the existing scheme for 2D WSNs proposed recently [1]. Same as [1], we formulate the energy consumption balancing problem as an problem of optimal distribution of transmitting data by combining the techniques of sphere-corona based network division, mixed-routing and data aggregation. We first present a Tiled-block based routing scheme in order to balance energy consumption among nodes in each sphere-corona. Then we design an algorithm to compute the optimal distribution ratio of transmitting data between direct and hop-by-hop transmission, with the purpose of balancing energy consumption among nodes across different sphere-coronas. We show maximizing network lifetime through computing the optimal number of sphere-coronas. Afterwards a energy consumption balanced data collecting protocol (ECBDC) is designed and a solution to extend ECBDC to largescale WSNs is also presented. Simulaiton results show that ECBDC is superior to conventional direct and multihop transmission schemes in network lifetime.

基于半固定分簇的无线传感器网络节能分簇路由算法

为了解决无线传感器网络中节点能耗不均衡和数据传输能耗大导致的网络生命周期短的问题,提出了基于半固定分簇的节能分簇路由算法。在节点部署完毕后对每个簇进行调整,保证每个簇的节点数相同,从而达到负载均衡的目的。在簇头选择阶段,主要考虑节点间距离以及节点的剩余能量;在数据传输阶段,算法根据节点的剩余能量、节点到基站的距离以及节点之间的距离构建了中继节点选择的优化模型,同时实现了均衡和降低能耗的目标;当网络运行一段时间后,由于簇间的剩余能量差异过大,再次对簇群进行优化,尽可能使得每个簇群能量接近;最后当簇头节点能量低于所设阈值时,再次对簇头进行轮换优化,以延长节点的工作时长。仿真结果表明,所提算法有效降低了节点能耗,延长了网络的生命周期。

基于IHBA优化模糊C均值的三维WSN分簇路由算法

针对分簇路由算法在三维场景下能量消耗大、网络生存周期短的问题,提出了一种基于改进蜜獾算法优化模糊C均值的三维无线传感网分簇路由算法IFCRA。IFCRA分别对网络成簇、簇首选举以及数据传输阶段进行了优化。首先,采用改进蜜獾算法优化模糊C均值算法,解决模糊C均值易陷入局部最优的问题,并综合节点的距离和能量特征划分拓扑结构。其次,结合簇内节点的能量和相对距离构建最优簇首函数,平衡簇首负载。最后,采用自适应传输机制寻找中继节点,综合节点距离和能量构建最优传输路径函数,采用改进蜜獾算法进行寻优,均衡数据传输能耗。仿真结果表明,IFCRA在三维异构场景中分簇合理、能耗均衡且生存周期长。

双线轨道无线传感网络节点优化部署策略

针对双线轨道无线传感网络节点部署过程中出现的网络能耗不均衡现象,提出基于六边形分簇的能耗均衡部署策略。将双线轨道划分成面积相等的簇,摒弃传统的簇头选举机制,将簇头设于六边形中心,根据网络模型和节点能耗模型按比例计算簇头节点数量并分配至各簇;利用簇成员节点与簇头节点的能耗关系计算簇成员节点数;节点采用休眠/唤醒工作方式。实验结果表明,该节点部署方法能有效地均衡各区间的能量利用率,提高网络寿命,对于长距离无线传感网络部署具有很好的延伸性。

铁路沿线线型无线传感器网络高效路由协议

为防止网络“热区”现象,针对铁路沿线无线传感器网络多呈线型分布的结构特点,提出一种基于服务质量的能耗均衡分簇路由协议(ECRPQ)。首先,部署网络节点,计算节点能量消耗,建立能耗均衡的非均匀节点部署模型并进行网络分簇。然后,设计路由协议,在簇首选举时引入节点动态剩余能量和节点担任簇首轮次的影响因素,在通信阶段采用TDMA机制和CDMA机制相结合的方式,在进行时间同步校准时严格保证簇内节点时间同步。最后,通过MATLAB进行仿真实验,从网络生命周期、网络吞吐量和节点平均时延3个方面将ECRPQ与LEACH、LEACH-C这2种经典协议进行对比。结果表明:当网络节点总数为200个时,ECRPQ的网络生命周期明显更长,达到600 s;ECRPQ的网络吞吐量更大,分别比LEACH和LEACH-C提高128.7%和84.6%;ECRPQ的节点平均时延更低,分别比LEACH和LEACH-C降低52.8%和43.2%。

基于LEACH协议簇头定位算法研究

无线传感器网络能量消耗受簇头选择的影响很大,能耗对网络寿命起着至关重要的作用。在LEACH协议基础上,针对该协议的缺点,在保证网络簇头节点覆盖最大化基础上,对簇头位置选择边缘化及密度进行优化,提出一种新的分簇方法。仿真结果表明,改进后的LEACH协议,降低了网络的能耗、增加了数据发送的总量、延迟了网络的寿命,是一种比较有效的分簇算法。

面向边缘增强分布式电力无线传感网的资源分配

针对目前传统电力无线传感网络中出现的访问时延高、能耗大以及用户服务质量恶化等问题,引入移动边缘计算(mobile edge computing,MEC),建立访问时延和网络能耗联合优化模型,目标为最小化时延和能耗的联合函数;随后在射频拉远单元的剩余资源量、负载排队等待时延和中心单元/分布单元的剩余资源量的共同约束下,通过控制负载转移过程中的等待时延,从而确定中心单元/分布单元的总资源处理量;接着根据MEC服务器的资源利用率,通过减少活跃的MEC服务器数量,来减少传感器设备的能耗。仿真分析了权重系数大小对目标函数的影响,以及算法在不同业务流量和时刻下的对比。结果表明:提出的分配机制在降低访问时延和设备能耗方面,效果优于其他对比算法。该机制能有效提高传感器的通信质量和系统工作效率,延长传感器设备寿命,降低网络成本开销。

基于簇头节点能量均衡选择的LEACH优化算法

针对无线传感网络中LEACH协议在进行簇头节点选择时能量消耗过快导致的生存周期短、数据吞吐量低等问题,提出了一种基于簇头节点能量均衡选择的LEACH优化算法。该算法选取WSNs中剩余能量高的普通节点作为簇头节点,同时考虑普通节点与簇头节点、簇头节点与基站之间的距离,以及所有节点的剩余能量和平均能量等因素来选择通信方式和传输路径。通过MATLAB工具,对提出的算法进行了仿真实验。结果表明,在100 m×100 m的小面积监测区域和200 m×200 m的大面积监测区域内,与LEACH、DEEC、IMP-LEACH算法相比,该算法降低了WSNs中节点的能量消耗,延长了生存周期,同时提高了数据吞吐量。