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clustering routing protocol Based on Tuna Swarm Optimization and Fuzzy Control Theory in Wireless Sensor Networks

IEEE SENSORS JOURNAL 2024年第10期24卷 17102-17115页

作者： Yao, Yin-Di Li, Hui-Cong Zeng, Zhi-Bin Wang, Chen Zhang, Yi-Qian Univ Posts & Telecommun Sch Commun & Informat Engn Shaanxi Key Lab Informat Commun Network & Secur Xian 710121 Peoples R China Xidian Univ Sch Microelect Xian 710071 Peoples R China Xidian Univ Sch Commun & Informat Engn Xian 710126 Peoples R China

Wireless sensor networks (WSNs) are composed of a large number of sensor nodes, typically powered by batteries. Once the energy is exhausted, the sensor nodes will stop working, which will have a serious impact on network performance. Therefore, energy consumption has always been a bottleneck in the development of WSNs. To balance the network energy and improve energy efficiency, this article proposes a clustering routing protocol based on tuna swarm optimization and fuzzy control theory (TSFC). First, tuna swarm optimization (TSO) is utilized to optimize network clustering by considering the average and standard deviation of distances from nodes to their respective cluster centers, which improves the compactness of cluster structure. Therefore, communication distance within the cluster is reduced, thereby reducing the energy consumption of communication within the cluster. Then, in the cluster head (CH) selection stage, a fuzzy controller for selecting CHs is designed based on the fuzzy control theory. The residual energy of nodes, distance to the base station (BS), and average distance to other nodes in the cluster are taken as inputs for the fuzzy controller, which outputs a fitness value of the node to become the CH. This method optimizes the CH selection, thereby reducing node energy consumption and balancing network energy consumption. Simulation results demonstrate that the proposed protocol can reduce network energy consumption, improve energy efficiency, and balance network energy. Furthermore, the network lifetime is 45.9%, 33.5%, and 10.0% longer than that of gray wolf optimization (GWO-C), energy-efficient LEACH (EE-LEACH), and enhanced fuzzy-based LEACH (E-FLEACH), respectively.

关键词： Wireless sensor networks Energy consumption Sensors routing protocols routing Particle swarm optimization Fuzzy logic clustering routing protocol fuzzy control theory tuna swarm optimization (TSO) wireless sensor networks (WSNs)

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A hybrid clustering routing protocol based on machine learning and graph theory for energy conservation and hole detection in wireless sensor network

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INTERNATIONAL JOURNAL OF DISTRIBUTED SENSOR NETWORKS 2019年第6期15卷 1-19页

作者： Masoud, Mohammad Z. Jaradat, Yousef Jannoud, Ismael Al Sibahee, Mustafa A. Al Zaytoonah Univ Jordan ZUJ Dept Elect Engn Commun & Comp POB 130 Amman 11733 Jordan Huazhong Univ Sci & Technol Comp Sci Dept Wuhan Hubei Peoples R China

In this work, a new hybrid clustering routing protocol is proposed to prolong network life time through detecting holes and edges nodes. The detection process attempts to generate a connected graph without any isolated nodes or clusters that have no connection with the sink node. To this end, soft clustering/estimation maximization with graph metrics, PageRank, node degree, and local cluster coefficient, has been utilized. Holes and edges detection process is performed by the sink node to reduce energy consumption of wireless sensor network nodes. The clustering process is dynamic among sensor nodes. Hybrid clustering routing protocol-hole detection converts the network into a number of rings to overcome transmission distances. We compared hybrid clustering routing protocol-hole detection with four different protocols. The accuracy of detection reached 98%. Moreover, network life time has prolonged 10%. Finally, hybrid clustering routing protocol-hole detection has eliminated the disconnectivity in the network for more than 80% of network life time.

关键词： Hole detection energy consumption wireless sensor network (WSN) graph metrics soft clustering clustering routing protocol

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Multihop clustering routing protocol Based on Improved Coronavirus Herd Immunity Optimizer and Q-Learning in WSNs

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IEEE SENSORS JOURNAL 2023年第2期23卷 1645-1659页

作者： Yao, Yin-Di Wang, Chen Li, Xiong Zeng, Zhi-Bin Zhao, Bo-Zhan Su, Zhan Li, Hui-Cong Xian Univ Posts & Telecommun Sch Commun & Informat Engn Xian 710121 Peoples R China Xian Univ Posts & Telecommun Shaanxi Key Lab Informat Commun Network & Secur Xian 710121 Peoples R China Beijing Univ Posts & Telecommun Sch Informat & Commun Engn Beijing 100876 Peoples R China Xidian Univ Sch Microelect Xian 710071 Peoples R China

Wireless sensor networks (WSNs) are composed of a large number of spatially distributed sensor nodes to monitor and transmit information from the environment. However, the batteries used by these sensor nodes have limited energy and cannot be charged or replaced due to the harsh deployment environment. This energy limitationwill seriously affect the lifetime of the network. Therefore, the purpose of this research is to reduce energy consumption and balance the load of sensor nodes by clustering routing protocols, so as to prolong the lifetime of the network. First, the coronavirus herd immune optimizer is improved and used to optimize the network clustering. Second, the cluster heads (CHs) are selected according to the energy and location factors in the clusters, and a reasonable CH replacement mechanism is designed to avoid the extra communication energy consumption caused by the frequent replacement of CHs. Finally, amultihop routingmechanism between the CHs and the base station is constructedbyQ-learning. Simulation results show that the proposed work can improve the structure of clusters, enhance the load balance of nodes, reduce network energy consumption, and prolong the network lifetime. The appearance time of the first energy-depleted node is delayed by 25.8%, 85.9%, and 162.2% compared with IGWO, ACA-LEACH, and DEAL in the monitoring area of 300 x 300 m, respectively. In addition, the proposed protocol shows better adaptability in varying dynamic conditions.

关键词： clustering routing protocol improved coronavirus herd immunity optimizer Q-learning wireless sensor networks (WSNs)

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Energy-balanced clustering routing protocol Based on Task Separation in Wireless Sensor Networks 8

Energy-balanced Clustering Routing Protocol Based on Task Se...

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8th International Conference on BioMedical Engineering and Informatics (BMEI)

作者： Sun, Wei Song, Xiaoying Wang, Fasheng Dalian Neusoft Univ Informat Liaoning Key Lab Network Secur & Comp Technol Dalian Peoples R China Northeastern Univ Software Ctr Shenyang Peoples R China

ISBN: (纸本)9781509000227

clustering protocol for data gathering is one of the effective ways to solve the energy hole problem in wireless sensor networks. However, most of the existing clustering protocols focus on the network model with uniform node distribution. They cannot effectively apply to the real network where the sensor nodes are randomly non-uniformly deployed. In this paper, we propose an energy-balanced clustering routing protocol (EBCRP) based on task separation. In this scheme, the network is firstly divided into clusters by using global information. And each of them has the same number of sensor nodes in order to balance the energy consumption of intra-cluster. In succession, task separation, the tasks of traditional single cluster head are separated and achieved by two cluster heads respectively, is proposed to reduce the traffic burden for single cluster head. Then, we explore an energy-efficient and reliable inter-cluster routing algorithm, which considers comprehensively three factors: residual energy, distance and available buffer space of nodes. Simulation results and performance evaluation of EBCRP show significant improvement in network lifetime and energy balance.

关键词： wireless sensor networks balancing energy consumption task separation clustering routing protocol random deployment

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Energy Balanced clustering routing protocol for Wireless Sensor Networks

Energy Balanced Clustering Routing Protocol for Wireless Sen...

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IEEE/CIC International Conference on Communications in China (ICCC)

作者： He, Xu Ning, Zhongzheng Liang, Siyuan Du, Jianbo Nie, Ting Xian Univ Posts & Telecommun Sch Commun & Informat Engn Xian Peoples R China

ISBN: (纸本)9781665439442

Energy consumption has become the research focus of large-scale wireless sensor networks, so it is very important to design an efficient and energy-saving routing protocol. In order to reduce the energy consumption of nodes in the wireless sensor network and extend the life cycle of the network, a energy-balanced clustering routing protocol was proposed. On the basis of sine cosine algorithm, the differential evolution algorithm and adaptive inertia weight are embedded to enhance the convergence accuracy of the algorithm, and the fitness function is constructed by the distance between nodes, between nodes and the base station, and the remaining energy of nodes. The improved sine cosine algorithm is used to select the optimal cluster head. At the same time, a selective multi-hop transmission mechanism of cluster head nodes is designed in the data transmission stage between clusters. Simulation results show that, compared with the Low Energy Adaptive clustering Hierarchy protocol, the proposed protocol can prolong the stability cycle and life cycle of the network by 61.22% and 19.08%, respectively.

关键词： Wireless sensor network clustering routing protocol cluster head election sine cosine algorithm

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Location-based Markov clustering routing protocol versus Density-based clustering routing protocol for Wireless Sensor Networks

Location-based Markov clustering routing protocol versus Den...

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International Symposium on Innovative Informatics of Biskra (ISNIB)

作者： Abbad, Leila Nacer, Azzedine Abbad, Houda Brahim, Mohammed Taieb ENST High Sch LIT Lab Dept Elect Engn & Ind Comp Algiers Algeria USTHB Univ Dept Instrumentat LCDEP Lab Bab Ezzouar Algeria Univ Djillali Liabes Sidi Bel Abbes EEDIS Lab Dept Comp Sci Sidi Bel Abbes Algeria

ISBN: (纸本)9798350320657

As the Internet of Things (IoT) continues to develop, Wireless Sensor Networks (WSNs) are being utilized more and more. The most pressing issue in these networks is the need to reduce energy consumption as much as possible to ensure the longevity of the network. A novel routing protocol, WMCL-BCRP, has been proposed which is based on Markovian clustering and sensor weighting. It is a hybrid solution that combines the grouping of the network sensors in a centralized way using Markov clustering and the implementation of a new decentralized approach for the election of the cluster heads(CH) and sensors involved in the routing according to two criteria, which are the density of sensors and their residual energy. WMCL-BCRP is an improved version of MCL-BCRP, which utilizes the same clustering system and selects cluster heads, and sends sensors based on their location and energy levels. Simulations of the WMCL-BCRP protocol show significant network lifespan increases compared to its successor MCL-BCRP and LEACH.

关键词： WSN Markov clustering (MCL) sensor density sensor location sensor weight clustering routing protocol energy consumption network lifetime

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Research on clustering routing protocol of MANET

Research on Clustering Routing Protocol of MANET

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2011年第十届分布式计算及其应用国际学术研讨会

作者： Zheng Sihai Li Layuan Li Yong Yuan Junchun College of Computer Science and Technology Wuhan University of Technology

In general,each cluster consists of a cluster head and several member nodes in clustering routing protocol of *** advantages are obvious,such as better scalability,less control overhead,and it a

ISBN: (纸本)9781457703270

In general,each cluster consists of a cluster head and several member nodes in clustering routing protocol of *** advantages are obvious,such as better scalability,less control overhead,and it a

关键词： MANET average delay clustering routing protocol weight Mobile ad hoc networks clustering routing protocol mean delay clustering algorithms Network topology cluster head Residual energy

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An Improved clustering routing protocol using Particle Swarm Optimization for Wireless Sensor Networks

An Improved Clustering Routing Protocol using Particle Swarm...

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International Conference on Broadcast Technology and Multimedia Communication(BTMC 2010)

作者： Changjiang Jiang,Min Xiang,Xianlun Tang Key Laboratory of Network Control and Intelligent Instrument of Ministry of Education Chongqing University of Posts and Telecommunications Chongqing,China Weiren Shi Department of Automation Chongqing University Chongqing,China

One of the key problem in cluster-based routing protocols for wireless sensor networks is how to cluster all nodes in the optimal way,which can not only decrease the energy consumption of the individual node,but also balance the energy dissipation of the *** this paper,a new centralized clustering protocol of two-layer hierarchy is proposed,which is compact,energy-aware and *** the lower layer,the optimal clustering of all nodes using PSO algorithm is *** the purpose of avoiding unbalanced energy dissipation among the cluster heads,the chief-clusterhead,which is responsible for collecting,aggregating the data of all cluster heads and sending the fused data to the base station,is selected in the upper *** results demonstrate that the protocol can efficiently decrease the dead speed of the nodes and prolong the network lifetime.

关键词： wireless sensor network clustering routing protocol PSO algorithm two-layer hierarchy.

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Research on clustering routing protocol of MANET

Research on Clustering Routing Protocol of MANET

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第十届电子商务、工程及科学领域的分布式计算和应用（DCABES）国际学术研讨会

作者： Zheng Sihai,Li Layuan,Li Yong,Yuan Junchun College of Computer Science and Technology Wuhan University of Technology Wuhan,China

In general,each cluster consists of a cluster head and several member nodes in clustering routing protocol of *** advantages are obvious,such as better scalability,less control overhead,and it also reduce the number of nodes sharing the same *** it needs a clustering algorithm to maintain the hierarchy so that it can adapt well to changes of network topology,and the routing elected by the clustering algorithm is not always *** paper proposes a new clustering routing protocol *** protocol takes into account the mobility and residual energy;it significantly improves network *** results of simulation show EARP is much better than CBRP routing protocol.

关键词： MANET clustering routing protocol average delay weight

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A survey of energy-efficient clustering routing protocols for wireless sensor networks based on metaheuristic approaches

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ARTIFICIAL INTELLIGENCE REVIEW 2023年第9期56卷 9699-9770页

作者： Del-Valle-Soto, Carolina Rodriguez, Alma Ascencio-Pina, Cesar Rodolfo Univ Panamericana Fac Ingn Alvaro Portillo 49 Zapopan 45010 Jalisco Mexico Univ Guadalajara Dept Elect & Comp CUCEI Ave Revoluc 1500 Guadalajara 44430 Jalisco Mexico Ctr Ensenanza Tecn Ind Desarrollo Software Providencia Secc 5a Calle Nueva Escocia 1885 ColomosGuadalajara 44638 Jal Mexico

The increase in proposed clustering routing protocols for Wireless Sensor Networks has motivated the development of survey studies that provide quick access to clear and meaningful information about state-of-the-art approaches. This review focuses on the most recent clustering routing protocols for WSNs based on metaheuristic techniques. Since there is a lack of survey studies that provide a comprehensive analysis of this field, we present a more in-depth study of different metaheuristic-based strategies mainly for selecting optimal cluster heads. The primary objective of the proposed work is to review approaches that have developed novel cluster-based routing protocols primarily for reducing the energy consumption of WSNs. In this survey, we examine every protocol considering its methodology and properties from the perspective of the metaheuristic community. Additionally, we present a comparative analysis of the reviewed approaches regarding the implemented network structure, the network characteristics, the metaheuristic algorithm used, the proposed search strategy, reported metrics, and the obtained results.

关键词： Wireless sensor networks clustering routing protocol Metaheuristic algorithms Energy-efficiency Bio-inspired algorithms Cluster heads selection

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