Wireless Sensor Networks(WSNs)have become foundational in numerous real-world applications,ranging from environmental monitoring and industrial automation to healthcare systems and smart city development.As these netw...Wireless Sensor Networks(WSNs)have become foundational in numerous real-world applications,ranging from environmental monitoring and industrial automation to healthcare systems and smart city development.As these networks continue to grow in scale and complexity,the need for energy-efficient,scalable,and robust communication protocols becomes more critical than ever.Metaheuristic algorithms have shown significant promise in addressing these challenges,offering flexible and effective solutions for optimizing WSN performance.Among them,the Grey Wolf Optimizer(GWO)algorithm has attracted growing attention due to its simplicity,fast convergence,and strong global search capabilities.Accordingly,this survey provides an in-depth review of the applications of GWO and its variants for clustering,multi-hop routing,and hybrid cluster-based routing in WSNs.We categorize and analyze the existing GWO-based approaches across these key network optimization tasks,discussing the different problem formulations,decision variables,objective functions,and performance metrics used.In doing so,we examine standard GWO,multi-objective GWO,and hybrid GWO models that incorporate other computational intelligence techniques.Each method is evaluated based on how effectively it addresses the core constraints of WSNs,including energy consumption,communication overhead,and network lifetime.Finally,this survey outlines existing gaps in the literature and proposes potential future research directions aimed at enhancing the effectiveness and real-world applicability of GWO-based techniques for WSN clustering and routing.Our goal is to provide researchers and practitioners with a clear,structured understanding of the current state of GWO in WSNs and inspire further innovation in this evolving field.展开更多
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...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.展开更多
To avoid uneven energy consuming in wireless sen- sor networks, a clustering routing model is proposed based on a Bayesian game. In the model, Harsanyi transformation is introduced to convert a static game of incomple...To avoid uneven energy consuming in wireless sen- sor networks, a clustering routing model is proposed based on a Bayesian game. In the model, Harsanyi transformation is introduced to convert a static game of incomplete information to the static game of complete but imperfect information. In addition, the existence of Bayesian nash equilibrium is proved. A clustering routing algorithm is also designed according to the proposed model, both cluster head distribution and residual energy are considered in the design of the algorithm. Simulation results show that the algorithm can balance network load, save energy and prolong network lifetime effectively.展开更多
Wireless Sensor Network(WSN)comprises a massive number of arbitrarily placed sensor nodes that are linked wirelessly to monitor the physical parameters from the target region.As the nodes in WSN operate on inbuilt bat...Wireless Sensor Network(WSN)comprises a massive number of arbitrarily placed sensor nodes that are linked wirelessly to monitor the physical parameters from the target region.As the nodes in WSN operate on inbuilt batteries,the energy depletion occurs after certain rounds of operation and thereby results in reduced network lifetime.To enhance energy efficiency and network longevity,clustering and routing techniques are commonly employed in WSN.This paper presents a novel black widow optimization(BWO)with improved ant colony optimization(IACO)algorithm(BWO-IACO)for cluster based routing in WSN.The proposed BWO-IACO algorithm involves BWO based clustering process to elect an optimal set of cluster heads(CHs).The BWO algorithm derives a fitness function(FF)using five input parameters like residual energy(RE),inter-cluster distance,intra-cluster distance,node degree(ND),and node centrality.In addition,IACO based routing process is involved for route selection in inter-cluster communication.The IACO algorithm incorporates the concepts of traditional ACO algorithm with krill herd algorithm(KHA).The IACO algorithm utilizes the energy factor to elect an optimal set of routes to BS in the network.The integration of BWO based clustering and IACO based routing techniques considerably helps to improve energy efficiency and network lifetime.The presented BWO-IACO algorithm has been simulated using MATLAB and the results are examined under varying aspects.A wide range of comparative analysis makes sure the betterment of the BWO-IACO algorithm over all the other compared techniques.展开更多
The imbalance of energy consumption in wireless sensor networks(WSNs)easily results in the“hot spot”problem that the sensor nodes in a particular area die due to fast energy consumption.In order to solve the“hot s...The imbalance of energy consumption in wireless sensor networks(WSNs)easily results in the“hot spot”problem that the sensor nodes in a particular area die due to fast energy consumption.In order to solve the“hot spot”problem in WSNs,we propose an unequal clustering routing algorithm based on genetic algorithm(UCR-GA).In the cluster head election phase,the fitness function is constructed based on the residual energy,density and distance between nodes and base station,and the appropriate node is selected as the cluster head.In the data transmission phase,the cluster head selects single-hop or multi-hop communication mode according to the distance to the base station.After we comprehensively consider the residual energy of the cluster head and its communication energy consumption with the base station,an appropriate relay node is selected.The designed protocal is simulated under energy homogeneous and energy heterogeneity conditions,and the results show that the proposed routing protocal can effectively balance energy consumption,prolong the life cycle of network,and is appicable to heterogeneous networks.展开更多
Wireless sensor network(WSN)includes a set of self-organizing and homogenous nodes employed for data collection and tracking applications.It comprises a massive set of nodes with restricted energy and processing abili...Wireless sensor network(WSN)includes a set of self-organizing and homogenous nodes employed for data collection and tracking applications.It comprises a massive set of nodes with restricted energy and processing abilities.Energy dissipation is a major concern involved in the design of WSN.Clustering and routing protocols are considered effective ways to reduce the quantity of energy dissipation using metaheuristic algorithms.In order to design an energy aware cluster-based route planning scheme,this study introduces a novel Honey Badger Based Clustering with African Vulture Optimization based Routing(HBAC-AVOR)protocol for WSN.The presented HBAC-AVOR model mainly aims to cluster the nodes in WSN effectually and organize the routes in an energy-efficient way.The presented HBAC-AVOR model follows a two stage process.At the initial stage,the HBAC technique is exploited to choose an opti-mal set of cluster heads(CHs)utilizing afitness function involving many input parameters.Next,the AVOR approach was executed for determining the optimal routes to BS and thereby lengthens the lifetime of WSN.A detailed simulation analysis was executed to highlight the increased outcomes of the HBAC-AVOR protocol.On comparing with existing techniques,the HBAC-AVOR model has outperformed existing techniques with maximum lifetime.展开更多
LEACH protocol randomly selects cluster head nodes in a cyclic manner. It may cause network to be unstable, if the low energy node is elected as the cluster head. If the size of cluster is too large or too small, it w...LEACH protocol randomly selects cluster head nodes in a cyclic manner. It may cause network to be unstable, if the low energy node is elected as the cluster head. If the size of cluster is too large or too small, it will affect the survival time of the network. To address this issue, an improved solution was proposed. Firstly, the scheme considered the average and standard deviation of the nodes’ residual energy and the distance between the node and the base station, then considered the distance between the node and the cluster head and the energy of the cluster head to optimize the cluster head selection and clustering. The performance analysis results showed this scheme could reduce premature deaths of the cluster heads and too high energy consumption of some clusters. Thus, the proposed algorithm could prompt the stability and prolong the lifetime of the network.展开更多
In the wireless sensor networks(WSN),the sensor nodes have limited battery life and are deployed in hostile environments.It is very difficult to recharging or replacement of the batteries after deployment for the sens...In the wireless sensor networks(WSN),the sensor nodes have limited battery life and are deployed in hostile environments.It is very difficult to recharging or replacement of the batteries after deployment for the sensor nodes in inaccessible areas.Therefore,how to increase the network lifetime of the WSN is deserved to be studied.In this study,a WSN routing algorithm was proposed based on block clustering and springboard nodes to increase the network lifetime of the WSN.Firstly,by analyzing the influence of communication transmission distance on network energy consumption,block clustering was introduced to control node transmission distance in order to reduce total network energy consumption.In addition,a network transmission model was proposed based on springboard nodes and the advantages of network energy consumption of this model against multi-hop between clusters were analyzed.The simulation results show that,compared with the LEACH algorithm,EECPK-means algorithm and energy centroid clustering algorithm,the proposed routing algorithm effectively prolongs the network lifetime of WSN.展开更多
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 dep...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.展开更多
Wireless Sensor Networks(WSNs)have emerged as crucial tools for real-time environmental monitoring through distributed sensor nodes(SNs).However,the operational lifespan of WSNs is significantly constrained by the lim...Wireless Sensor Networks(WSNs)have emerged as crucial tools for real-time environmental monitoring through distributed sensor nodes(SNs).However,the operational lifespan of WSNs is significantly constrained by the limited energy resources of SNs.Current energy efficiency strategies,such as clustering,multi-hop routing,and data aggregation,face challenges,including uneven energy depletion,high computational demands,and suboptimal cluster head(CH)selection.To address these limitations,this paper proposes a hybrid methodology that optimizes energy consumption(EC)while maintaining network performance.The proposed approach integrates the Low Energy Adaptive Clustering Hierarchy with Deterministic(LEACH-D)protocol using an Artificial Neural Network(ANN)and Bayesian Regularization Algorithm(BRA).LEACH-D improves upon conventional LEACH by ensuring more uniform energy usage across SNs,mitigating inefficiencies from random CH selection.The ANN further enhances CH selection and routing processes,effectively reducing data transmission overhead and idle listening.Simulation results reveal that the LEACH-D-ANN model significantly reduces EC and extends the network’s lifespan compared to existing protocols.This framework offers a promising solution to the energy efficiency challenges in WSNs,paving the way for more sustainable and reliable network deployments.展开更多
Wireless Sensor Networks(WSNs),as a crucial component of the Internet of Things(IoT),are widely used in environmental monitoring,industrial control,and security surveillance.However,WSNs still face challenges such as ...Wireless Sensor Networks(WSNs),as a crucial component of the Internet of Things(IoT),are widely used in environmental monitoring,industrial control,and security surveillance.However,WSNs still face challenges such as inaccurate node clustering,low energy efficiency,and shortened network lifespan in practical deployments,which significantly limit their large-scale application.To address these issues,this paper proposes an Adaptive Chaotic Ant Colony Optimization algorithm(AC-ACO),aiming to optimize the energy utilization and system lifespan of WSNs.AC-ACO combines the path-planning capability of Ant Colony Optimization(ACO)with the dynamic characteristics of chaotic mapping and introduces an adaptive mechanism to enhance the algorithm’s flexibility and adaptability.By dynamically adjusting the pheromone evaporation factor and heuristic weights,efficient node clustering is achieved.Additionally,a chaotic mapping initialization strategy is employed to enhance population diversity and avoid premature convergence.To validate the algorithm’s performance,this paper compares AC-ACO with clustering methods such as Low-Energy Adaptive Clustering Hierarchy(LEACH),ACO,Particle Swarm Optimization(PSO),and Genetic Algorithm(GA).Simulation results demonstrate that AC-ACO outperforms the compared algorithms in key metrics such as energy consumption optimization,network lifetime extension,and communication delay reduction,providing an efficient solution for improving energy efficiency and ensuring long-term stable operation of wireless sensor networks.展开更多
Cluster-based architectures are one of the most practical solutions in order to cope with the requirements of large-scale wireless sensor networks (WSN). Cluster-head election problem is one of the basic QoS requireme...Cluster-based architectures are one of the most practical solutions in order to cope with the requirements of large-scale wireless sensor networks (WSN). Cluster-head election problem is one of the basic QoS requirements of WSNs, yet this problem has not been sufficiently explored in the context of cluster-based sensor networks. Specifically, it is not known how to select the best candidates for the cluster head roles. In this paper, we investigate the cluster head election problem, specifically concentrating on applications where the energy of full network is the main requirement, and we propose a new approach to exploit efficiently the network energy, by reducing the energy consumed for cluster forming.展开更多
Aiming at the problem that node load is rarely considered in existing clustering routing algorithm for Wireless Sensor Networks (WSNs), a dynamic clustering routing algorithm for WSN is presented in this paper called ...Aiming at the problem that node load is rarely considered in existing clustering routing algorithm for Wireless Sensor Networks (WSNs), a dynamic clustering routing algorithm for WSN is presented in this paper called DCRCL (Dynamic Clustering Routing Considering Load). This algorithm is comprised of three phases including cluster head (CH) selection, cluster setup and inter-cluster routing. First, the CHs are selected based on residual energy and node load. Then the non-CH nodes choose a cluster by comparing the cost function of its neighbor CHs. At last, each CH communicates with base station by using multi-hop communication. The simulation results show that comparing with the existing one, the techniques life cycle and date volume of the network are increased by 30.7 percent and 29.8 percent respectively by using the proposed algorithm DCRCL.展开更多
In wireless sensor networks, clustering of nodes effectively conserves considerable amount of energy resulting in increased network life-time. Clustering protocols do not consider density of nodes in cluster formation...In wireless sensor networks, clustering of nodes effectively conserves considerable amount of energy resulting in increased network life-time. Clustering protocols do not consider density of nodes in cluster formation, which increases the possibility of hotspots in areas where the density of nodes is very less. If the node density is very high, cluster-heads may expend high energy leading to their early death. Existing cluster protocols that concentrate on energy conservation have not exhibited their impact on packet delivery and delay. In this proposed protocol, clusters are constructed based on the range of nodes, distance between neighbouring nodes and density of nodes over a region resulting in the formation of dissimilar clusters. With this method, the entire sensing region is considered to be a large circular region with base station positioned at the centre. Initially, the nodes that can be able to reach base station in a single hop are considered for constructing inner smaller circular regions over the entire region. This method is iterated for n-hop nodes until n-concentric circular regions are formed. These circular boundaries are reconstructed based on a distance metric, density of nodes and a divergence factor. Using this architecture, network analysis is done by routing data to the base station from different sized clusters. Based on simulation results, this new protocol Dynamic Unequal Clustered Routing (D-UCR), despite being energy efficient, showed better data delivery ratio and minimized delay when compared with other traditional clustering algorithms such as Leach and Equal Clustered Routing.展开更多
One of the major constraints of wireless sensor networks is limited energy available to sensor nodes because of the small size of the batteries they use as source of power. Clustering is one of the routing techniques ...One of the major constraints of wireless sensor networks is limited energy available to sensor nodes because of the small size of the batteries they use as source of power. Clustering is one of the routing techniques that have been using to minimize sensor nodes’ energy consumption during operation. In this paper, A Novel Clustering Algorithm for Energy Efficiency in Wireless Sensor Networks (ANCAEE) has been proposed. The algorithm achieves good performance in terms of minimizing energy consumption during data transmission and energy consumptions are distributed uniformly among all nodes. ANCAEE uses a new method of clusters formation and election of cluster heads. The algorithm ensures that a node transmits its data to the cluster head with a single hop transmission and cluster heads forward their data to the base station with multi-hop transmissions. Simulation results show that our approach consumes less energy and effectively extends network utilization.展开更多
Wireless sensor networks are widely used for its flexibility, but they also suffer from problems like limited capacity, large node number and vulnerability to security threats. In this paper, we propose a multi-path r...Wireless sensor networks are widely used for its flexibility, but they also suffer from problems like limited capacity, large node number and vulnerability to security threats. In this paper, we propose a multi-path routing protocol based on the credible cluster heads. The protocol chooses nodes with more energy remained as cluster heads at the cluster head choosing phase, and then authenticates them by the neighbor cluster heads. Using trust mechanisms it creates the credit value, and based on the credit value the multi-path cluster head routing can finally be found. The credit value is created and exchanged among the cluster heads only. Theoretical analysis combined with simulation results demonstrate that this protocol can save the resource, prolong the lifetime, and ensure the security and performance of the network.展开更多
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 t...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.展开更多
In the wireless sensor networks, high efficient data routing for the limited energy resource networks is an important issue. By introducing Antcolony algorithm, this paper proposes the wireless sensor network routing ...In the wireless sensor networks, high efficient data routing for the limited energy resource networks is an important issue. By introducing Antcolony algorithm, this paper proposes the wireless sensor network routing algorithm based on LEACH. During the construction of sensor network clusters, to avoid the node premature death because of the energy consumption, only the nodes whose residual energy is higher than the average energy can be chosen as the cluster heads. The method of repeated division is used to divide the clusters in sensor networks so that the numbers of the nodes in each cluster are balanced. The basic thought of ant-colony algorithm is adopted to realize the data routing between the cluster heads and sink nodes, and the maintenance of routing. The analysis and simulation showed that the proposed routing protocol not only can reduce the energy consumption, balance the energy consumption between nodes, but also prolong the network lifetime.展开更多
As a representative of chain-based protocol in Wireless Sensor Networks (WSNs), EEPB is an elegant solution on energy efficiency. However, in the latter part of the operation of the network, there is still a big probl...As a representative of chain-based protocol in Wireless Sensor Networks (WSNs), EEPB is an elegant solution on energy efficiency. However, in the latter part of the operation of the network, there is still a big problem: reserving energy of the node frequently presents the incapacity of directly communicating with the base station, at the same time capacity of data acquisition and transmission as normal nodes. If these nodes were selected as LEADER nodes, that will accelerate the death process and unevenness of energy consumption distribution among nodes.This paper proposed a chain routing algorithm based ontraffic prediction model (CRTP).The novel algorithmdesigns a threshold judgment method through introducing the traffic prediction model in the process of election of LEADER node. The process can be dynamically adjusted according to the flow forecasting. Therefore, this algorithm lets the energy consumption tend-ing to keep at same level. Simulation results show that CRTP has superior performance over EEPB in terms of balanced network energy consumption and the prolonged network life.展开更多
Based on the analysis of the existing classic clustering routing algorithm HEED, this paper proposes an efficient dynamic clustering routing algorithm ED-HEED. In the cluster selection process, in order to optimize th...Based on the analysis of the existing classic clustering routing algorithm HEED, this paper proposes an efficient dynamic clustering routing algorithm ED-HEED. In the cluster selection process, in order to optimize the network topology and select more proper nodes as the cluster head, the proposed clustering algorithm considers the shortest path prediction of the node to the destination sink and the congestion situation. In the data transmission procedure, the high-efficiency CEDOR opportunistic routing algorithm is applied into the ED-HEED as the data transmission mode between cluster headers. A novel adaptive dynamic clustering mechanism is also considered into the algorithm, as well as the data redundancy and security control. Our Simulation demonstrates that the ED-HEED algorithm can reduce the energy consumption, prolong the network life and keep the security and availability of the network compared with the HEED algorithm.展开更多
文摘Wireless Sensor Networks(WSNs)have become foundational in numerous real-world applications,ranging from environmental monitoring and industrial automation to healthcare systems and smart city development.As these networks continue to grow in scale and complexity,the need for energy-efficient,scalable,and robust communication protocols becomes more critical than ever.Metaheuristic algorithms have shown significant promise in addressing these challenges,offering flexible and effective solutions for optimizing WSN performance.Among them,the Grey Wolf Optimizer(GWO)algorithm has attracted growing attention due to its simplicity,fast convergence,and strong global search capabilities.Accordingly,this survey provides an in-depth review of the applications of GWO and its variants for clustering,multi-hop routing,and hybrid cluster-based routing in WSNs.We categorize and analyze the existing GWO-based approaches across these key network optimization tasks,discussing the different problem formulations,decision variables,objective functions,and performance metrics used.In doing so,we examine standard GWO,multi-objective GWO,and hybrid GWO models that incorporate other computational intelligence techniques.Each method is evaluated based on how effectively it addresses the core constraints of WSNs,including energy consumption,communication overhead,and network lifetime.Finally,this survey outlines existing gaps in the literature and proposes potential future research directions aimed at enhancing the effectiveness and real-world applicability of GWO-based techniques for WSN clustering and routing.Our goal is to provide researchers and practitioners with a clear,structured understanding of the current state of GWO in WSNs and inspire further innovation in this evolving field.
文摘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.
基金supported by the National Natural Science Fundation of China (60974082 60874085)+2 种基金the Fundamental Research Funds for the Central Universities (K50510700004)the Technology Plan Projects of Guangdong Province (20110401)the Team Project of Hanshan Normal University (LT201001)
文摘To avoid uneven energy consuming in wireless sen- sor networks, a clustering routing model is proposed based on a Bayesian game. In the model, Harsanyi transformation is introduced to convert a static game of incomplete information to the static game of complete but imperfect information. In addition, the existence of Bayesian nash equilibrium is proved. A clustering routing algorithm is also designed according to the proposed model, both cluster head distribution and residual energy are considered in the design of the algorithm. Simulation results show that the algorithm can balance network load, save energy and prolong network lifetime effectively.
文摘Wireless Sensor Network(WSN)comprises a massive number of arbitrarily placed sensor nodes that are linked wirelessly to monitor the physical parameters from the target region.As the nodes in WSN operate on inbuilt batteries,the energy depletion occurs after certain rounds of operation and thereby results in reduced network lifetime.To enhance energy efficiency and network longevity,clustering and routing techniques are commonly employed in WSN.This paper presents a novel black widow optimization(BWO)with improved ant colony optimization(IACO)algorithm(BWO-IACO)for cluster based routing in WSN.The proposed BWO-IACO algorithm involves BWO based clustering process to elect an optimal set of cluster heads(CHs).The BWO algorithm derives a fitness function(FF)using five input parameters like residual energy(RE),inter-cluster distance,intra-cluster distance,node degree(ND),and node centrality.In addition,IACO based routing process is involved for route selection in inter-cluster communication.The IACO algorithm incorporates the concepts of traditional ACO algorithm with krill herd algorithm(KHA).The IACO algorithm utilizes the energy factor to elect an optimal set of routes to BS in the network.The integration of BWO based clustering and IACO based routing techniques considerably helps to improve energy efficiency and network lifetime.The presented BWO-IACO algorithm has been simulated using MATLAB and the results are examined under varying aspects.A wide range of comparative analysis makes sure the betterment of the BWO-IACO algorithm over all the other compared techniques.
基金National Natural Science Foundation of China(No.61862038)Lanzhou Talent Innovation and Entrepreneurship Technology Plan Project(No.2019-RC-14)Foundation of a Hundred Youth Talents Training Program of Lanzhou Jiaotong University。
文摘The imbalance of energy consumption in wireless sensor networks(WSNs)easily results in the“hot spot”problem that the sensor nodes in a particular area die due to fast energy consumption.In order to solve the“hot spot”problem in WSNs,we propose an unequal clustering routing algorithm based on genetic algorithm(UCR-GA).In the cluster head election phase,the fitness function is constructed based on the residual energy,density and distance between nodes and base station,and the appropriate node is selected as the cluster head.In the data transmission phase,the cluster head selects single-hop or multi-hop communication mode according to the distance to the base station.After we comprehensively consider the residual energy of the cluster head and its communication energy consumption with the base station,an appropriate relay node is selected.The designed protocal is simulated under energy homogeneous and energy heterogeneity conditions,and the results show that the proposed routing protocal can effectively balance energy consumption,prolong the life cycle of network,and is appicable to heterogeneous networks.
文摘Wireless sensor network(WSN)includes a set of self-organizing and homogenous nodes employed for data collection and tracking applications.It comprises a massive set of nodes with restricted energy and processing abilities.Energy dissipation is a major concern involved in the design of WSN.Clustering and routing protocols are considered effective ways to reduce the quantity of energy dissipation using metaheuristic algorithms.In order to design an energy aware cluster-based route planning scheme,this study introduces a novel Honey Badger Based Clustering with African Vulture Optimization based Routing(HBAC-AVOR)protocol for WSN.The presented HBAC-AVOR model mainly aims to cluster the nodes in WSN effectually and organize the routes in an energy-efficient way.The presented HBAC-AVOR model follows a two stage process.At the initial stage,the HBAC technique is exploited to choose an opti-mal set of cluster heads(CHs)utilizing afitness function involving many input parameters.Next,the AVOR approach was executed for determining the optimal routes to BS and thereby lengthens the lifetime of WSN.A detailed simulation analysis was executed to highlight the increased outcomes of the HBAC-AVOR protocol.On comparing with existing techniques,the HBAC-AVOR model has outperformed existing techniques with maximum lifetime.
文摘LEACH protocol randomly selects cluster head nodes in a cyclic manner. It may cause network to be unstable, if the low energy node is elected as the cluster head. If the size of cluster is too large or too small, it will affect the survival time of the network. To address this issue, an improved solution was proposed. Firstly, the scheme considered the average and standard deviation of the nodes’ residual energy and the distance between the node and the base station, then considered the distance between the node and the cluster head and the energy of the cluster head to optimize the cluster head selection and clustering. The performance analysis results showed this scheme could reduce premature deaths of the cluster heads and too high energy consumption of some clusters. Thus, the proposed algorithm could prompt the stability and prolong the lifetime of the network.
基金National Natural Science Foundation of China(Nos.61661025,61661026)。
文摘In the wireless sensor networks(WSN),the sensor nodes have limited battery life and are deployed in hostile environments.It is very difficult to recharging or replacement of the batteries after deployment for the sensor nodes in inaccessible areas.Therefore,how to increase the network lifetime of the WSN is deserved to be studied.In this study,a WSN routing algorithm was proposed based on block clustering and springboard nodes to increase the network lifetime of the WSN.Firstly,by analyzing the influence of communication transmission distance on network energy consumption,block clustering was introduced to control node transmission distance in order to reduce total network energy consumption.In addition,a network transmission model was proposed based on springboard nodes and the advantages of network energy consumption of this model against multi-hop between clusters were analyzed.The simulation results show that,compared with the LEACH algorithm,EECPK-means algorithm and energy centroid clustering algorithm,the proposed routing algorithm effectively prolongs the network lifetime of WSN.
文摘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.
文摘Wireless Sensor Networks(WSNs)have emerged as crucial tools for real-time environmental monitoring through distributed sensor nodes(SNs).However,the operational lifespan of WSNs is significantly constrained by the limited energy resources of SNs.Current energy efficiency strategies,such as clustering,multi-hop routing,and data aggregation,face challenges,including uneven energy depletion,high computational demands,and suboptimal cluster head(CH)selection.To address these limitations,this paper proposes a hybrid methodology that optimizes energy consumption(EC)while maintaining network performance.The proposed approach integrates the Low Energy Adaptive Clustering Hierarchy with Deterministic(LEACH-D)protocol using an Artificial Neural Network(ANN)and Bayesian Regularization Algorithm(BRA).LEACH-D improves upon conventional LEACH by ensuring more uniform energy usage across SNs,mitigating inefficiencies from random CH selection.The ANN further enhances CH selection and routing processes,effectively reducing data transmission overhead and idle listening.Simulation results reveal that the LEACH-D-ANN model significantly reduces EC and extends the network’s lifespan compared to existing protocols.This framework offers a promising solution to the energy efficiency challenges in WSNs,paving the way for more sustainable and reliable network deployments.
基金funded by the Natural Science Foundation of Xinjiang Uygur Autonomous Region:No.22D01B148Bidding Topics for the Center for Integration of Education and Production and Development of New Business in 2024:No.2024-KYJD05+1 种基金Basic Scientific Research Business Fee Project of Colleges and Universities in Autonomous Region:No.XJEDU2025P126Xinjiang College of Science&Technology School-level Scientific Research Fund Project:No.2024-KYTD01.
文摘Wireless Sensor Networks(WSNs),as a crucial component of the Internet of Things(IoT),are widely used in environmental monitoring,industrial control,and security surveillance.However,WSNs still face challenges such as inaccurate node clustering,low energy efficiency,and shortened network lifespan in practical deployments,which significantly limit their large-scale application.To address these issues,this paper proposes an Adaptive Chaotic Ant Colony Optimization algorithm(AC-ACO),aiming to optimize the energy utilization and system lifespan of WSNs.AC-ACO combines the path-planning capability of Ant Colony Optimization(ACO)with the dynamic characteristics of chaotic mapping and introduces an adaptive mechanism to enhance the algorithm’s flexibility and adaptability.By dynamically adjusting the pheromone evaporation factor and heuristic weights,efficient node clustering is achieved.Additionally,a chaotic mapping initialization strategy is employed to enhance population diversity and avoid premature convergence.To validate the algorithm’s performance,this paper compares AC-ACO with clustering methods such as Low-Energy Adaptive Clustering Hierarchy(LEACH),ACO,Particle Swarm Optimization(PSO),and Genetic Algorithm(GA).Simulation results demonstrate that AC-ACO outperforms the compared algorithms in key metrics such as energy consumption optimization,network lifetime extension,and communication delay reduction,providing an efficient solution for improving energy efficiency and ensuring long-term stable operation of wireless sensor networks.
文摘Cluster-based architectures are one of the most practical solutions in order to cope with the requirements of large-scale wireless sensor networks (WSN). Cluster-head election problem is one of the basic QoS requirements of WSNs, yet this problem has not been sufficiently explored in the context of cluster-based sensor networks. Specifically, it is not known how to select the best candidates for the cluster head roles. In this paper, we investigate the cluster head election problem, specifically concentrating on applications where the energy of full network is the main requirement, and we propose a new approach to exploit efficiently the network energy, by reducing the energy consumed for cluster forming.
文摘Aiming at the problem that node load is rarely considered in existing clustering routing algorithm for Wireless Sensor Networks (WSNs), a dynamic clustering routing algorithm for WSN is presented in this paper called DCRCL (Dynamic Clustering Routing Considering Load). This algorithm is comprised of three phases including cluster head (CH) selection, cluster setup and inter-cluster routing. First, the CHs are selected based on residual energy and node load. Then the non-CH nodes choose a cluster by comparing the cost function of its neighbor CHs. At last, each CH communicates with base station by using multi-hop communication. The simulation results show that comparing with the existing one, the techniques life cycle and date volume of the network are increased by 30.7 percent and 29.8 percent respectively by using the proposed algorithm DCRCL.
文摘In wireless sensor networks, clustering of nodes effectively conserves considerable amount of energy resulting in increased network life-time. Clustering protocols do not consider density of nodes in cluster formation, which increases the possibility of hotspots in areas where the density of nodes is very less. If the node density is very high, cluster-heads may expend high energy leading to their early death. Existing cluster protocols that concentrate on energy conservation have not exhibited their impact on packet delivery and delay. In this proposed protocol, clusters are constructed based on the range of nodes, distance between neighbouring nodes and density of nodes over a region resulting in the formation of dissimilar clusters. With this method, the entire sensing region is considered to be a large circular region with base station positioned at the centre. Initially, the nodes that can be able to reach base station in a single hop are considered for constructing inner smaller circular regions over the entire region. This method is iterated for n-hop nodes until n-concentric circular regions are formed. These circular boundaries are reconstructed based on a distance metric, density of nodes and a divergence factor. Using this architecture, network analysis is done by routing data to the base station from different sized clusters. Based on simulation results, this new protocol Dynamic Unequal Clustered Routing (D-UCR), despite being energy efficient, showed better data delivery ratio and minimized delay when compared with other traditional clustering algorithms such as Leach and Equal Clustered Routing.
文摘One of the major constraints of wireless sensor networks is limited energy available to sensor nodes because of the small size of the batteries they use as source of power. Clustering is one of the routing techniques that have been using to minimize sensor nodes’ energy consumption during operation. In this paper, A Novel Clustering Algorithm for Energy Efficiency in Wireless Sensor Networks (ANCAEE) has been proposed. The algorithm achieves good performance in terms of minimizing energy consumption during data transmission and energy consumptions are distributed uniformly among all nodes. ANCAEE uses a new method of clusters formation and election of cluster heads. The algorithm ensures that a node transmits its data to the cluster head with a single hop transmission and cluster heads forward their data to the base station with multi-hop transmissions. Simulation results show that our approach consumes less energy and effectively extends network utilization.
文摘Wireless sensor networks are widely used for its flexibility, but they also suffer from problems like limited capacity, large node number and vulnerability to security threats. In this paper, we propose a multi-path routing protocol based on the credible cluster heads. The protocol chooses nodes with more energy remained as cluster heads at the cluster head choosing phase, and then authenticates them by the neighbor cluster heads. Using trust mechanisms it creates the credit value, and based on the credit value the multi-path cluster head routing can finally be found. The credit value is created and exchanged among the cluster heads only. Theoretical analysis combined with simulation results demonstrate that this protocol can save the resource, prolong the lifetime, and ensure the security and performance of the network.
文摘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.
基金Acknowledgements Supported by the Fundamental Research Funds for the Central Universities（72104988）, The National High Technology Research and Development Program of China （ 2009AA01 Z204, 2007AA01Z429, 2007AA01Z405）, The post doctor science foundation of China （20090451495, 20090461415） The National Natural science foundation of China （60874085, 60633020, 60803151 ）, The Natural Science Basic Research Plan in Shaanxi Province of China （Program No. SJ08F13）, The Aviation Sci- ence Foundation of China （2007ZD31003, 2008ZD31001 ）
文摘In the wireless sensor networks, high efficient data routing for the limited energy resource networks is an important issue. By introducing Antcolony algorithm, this paper proposes the wireless sensor network routing algorithm based on LEACH. During the construction of sensor network clusters, to avoid the node premature death because of the energy consumption, only the nodes whose residual energy is higher than the average energy can be chosen as the cluster heads. The method of repeated division is used to divide the clusters in sensor networks so that the numbers of the nodes in each cluster are balanced. The basic thought of ant-colony algorithm is adopted to realize the data routing between the cluster heads and sink nodes, and the maintenance of routing. The analysis and simulation showed that the proposed routing protocol not only can reduce the energy consumption, balance the energy consumption between nodes, but also prolong the network lifetime.
文摘As a representative of chain-based protocol in Wireless Sensor Networks (WSNs), EEPB is an elegant solution on energy efficiency. However, in the latter part of the operation of the network, there is still a big problem: reserving energy of the node frequently presents the incapacity of directly communicating with the base station, at the same time capacity of data acquisition and transmission as normal nodes. If these nodes were selected as LEADER nodes, that will accelerate the death process and unevenness of energy consumption distribution among nodes.This paper proposed a chain routing algorithm based ontraffic prediction model (CRTP).The novel algorithmdesigns a threshold judgment method through introducing the traffic prediction model in the process of election of LEADER node. The process can be dynamically adjusted according to the flow forecasting. Therefore, this algorithm lets the energy consumption tend-ing to keep at same level. Simulation results show that CRTP has superior performance over EEPB in terms of balanced network energy consumption and the prolonged network life.
文摘Based on the analysis of the existing classic clustering routing algorithm HEED, this paper proposes an efficient dynamic clustering routing algorithm ED-HEED. In the cluster selection process, in order to optimize the network topology and select more proper nodes as the cluster head, the proposed clustering algorithm considers the shortest path prediction of the node to the destination sink and the congestion situation. In the data transmission procedure, the high-efficiency CEDOR opportunistic routing algorithm is applied into the ED-HEED as the data transmission mode between cluster headers. A novel adaptive dynamic clustering mechanism is also considered into the algorithm, as well as the data redundancy and security control. Our Simulation demonstrates that the ED-HEED algorithm can reduce the energy consumption, prolong the network life and keep the security and availability of the network compared with the HEED algorithm.
