Clustering Algorithms for Wireless Sensor Networks Survey

This paper aims to discuss a comprehensive survey on clustering algorithms for wireless sensor networks (WSN). The several real-time applications adopted the WSN with the advance features. But the capacity and size of the battery used in the sensor nodes are limited. Battery replacement or recharging is very difficult in most outdoor applications. Hence handling this kind of network is one of the issues. One of the best solutions to the energy issue is Clustering. Clustering is to balance the energy consumption of the whole network by cluster-based architecture to prolong the network lifetime. Sensor nodes grouped into clusters; one sensor node selects as the cluster head for each cluster. The cluster head sensor node collects the data from their sensor member nodes and forwards them to the sink node. In cluster-based architecture, cluster formation and the selection of the cluster head node decides the network lifetime. The paper discusses the for and against various clustering algorithms. It suggests the vital parameters for developing energy-efficient clustering algorithms and steps to overcome the limitations.

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A Node Authentication Model in Wireless Sensor Networks With Locked Cluster Generation

Design Methodologies and Tools for 5G Network Development and Application - Advances in Wireless Technologies and Telecommunication ◽

10.4018/978-1-7998-4610-9.ch012 ◽

2021 ◽

pp. 236-250

Author(s):

C. R. Bharathi ◽

Alapati Naresh ◽

Arepalli Peda Gopi ◽

Lakshman Narayana Vejendla

Keyword(s):

Wireless Sensor Networks ◽

Sensor Networks ◽

Sensor Node ◽

Cluster Formation ◽

Cluster Head ◽

Base Station ◽

Sensor Nodes ◽

Wireless Sensor ◽

Cluster Generation ◽

Secure Network

In wireless sensor networks (WSN), the majority of the inquiries are issued at the base station. WSN applications frequently require collaboration among countless sensor nodes in a network. One precedent is to persistently screen a region and report occasions. A sensor node in a WSN is initially allocated with an energy level, and based on the tasks of that sensor node, energy will be reduced. In this chapter, two proposed methods for secure network cluster formation and authentication are discussed. When a network is established then all the nodes in it must register with cluster head and then authentication is performed. The selection of cluster head is done using a novel selection algorithm and for authenticating the nodes. Also, a novel algorithm for authentication is used in this chapter. The validation and authorization of nodes are carried over by managing the keys in WSN. The results have been analyzed using NS2 simulator with an aid of list of relevant parameters.

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Energy-Efficient Unequal Chain Length Clustering for Wireless Sensor Networks in Smart Cities

Wireless Communications and Mobile Computing ◽

10.1155/2017/5790161 ◽

2017 ◽

Vol 2017 ◽

pp. 1-12 ◽

Cited By ~ 6

Author(s):

Mohammad Baniata ◽

Jiman Hong

Keyword(s):

Wireless Sensor Networks ◽

Sensor Networks ◽

Chain Length ◽

Network Lifetime ◽

Routing Protocol ◽

Energy Efficient ◽

Smart Cities ◽

Cluster Head ◽

Sensor Nodes ◽

Wireless Sensor

The recent advances in sensing and communication technologies such as wireless sensor networks (WSN) have enabled low-priced distributed monitoring systems that are the foundation of smart cities. These advances are also helping to monitor smart cities and making our living environments workable. However, sensor nodes are constrained in energy supply if they have no constant power supply. Moreover, communication links can be easily failed because of unequal node energy depletion. The energy constraints and link failures affect the performance and quality of the sensor network. Therefore, designing a routing protocol that minimizes energy consumption and maximizes the network lifetime should be considered in the design of the routing protocol for WSN. In this paper, we propose an Energy-Efficient Unequal Chain Length Clustering (EEUCLC) protocol which has a suboptimal multihop routing algorithm to reduce the burden on the cluster head and a probability-based cluster head selection algorithm to prolong the network lifetime. Simulation results show that the EEUCLC mechanism enhanced the energy balance and prolonged the network lifetime compared to other related protocols.

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An Energy-Aware Method for Selecting Cluster Heads in Wireless Sensor Networks

Applied Sciences ◽

10.3390/app10217886 ◽

2020 ◽

Vol 10 (21) ◽

pp. 7886

Author(s):

Atefeh Rahiminasab ◽

Peyman Tirandazi ◽

M. J. Ebadi ◽

Ali Ahmadian ◽

Mehdi Salimi

Keyword(s):

Wireless Sensor Networks ◽

Sensor Networks ◽

Network Lifetime ◽

Cluster Head ◽

Base Station ◽

Energy Resources ◽

Sensor Nodes ◽

Wireless Sensor ◽

Dynamic Clustering ◽

Clustering Protocol

Wireless sensor networks (WSNs) include several sensor nodes that have limited capabilities. The most critical restriction in WSNs is energy resources. Moreover, since each sensor node’s energy resources cannot be recharged or replaced, it is inevitable to propose various methods for managing the energy resources. Furthermore, this procedure increases the network lifetime. In wireless sensor networks, the cluster head has a significant impact on system global scalability, energy efficiency, and lifetime. Furthermore, the cluster head is most important in combining, aggregating, and transferring data that are received from other cluster nodes. One of the substantial challenges in a cluster-based network is to choose a suitable cluster head. In this paper, to select an appropriate cluster head, we first model this problem by using multi-factor decision-making according to the four factors, including energy, mobility, distance to centre, and the length of data queues. Then, we use the Cluster Splitting Process (CSP) algorithm and the Analytical Hierarchy Process (AHP) method in order to provide a new method to solve this problem. These four factors are examined in our proposed approach, and our method is compared with the Base station Controlled Dynamic Clustering Protocol (BCDCP) algorithm. The simulation results show the proposed method in improving the network lifetime has better performance than the base station controlled dynamic clustering protocol algorithm. In our proposed method, the energy reduction is almost 5% more than the BCDCP method, and the packet loss rate in our proposed method is almost 25% lower than in the BCDCP method.

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Energy Balance Routing Algorithm Based on Virtual MIMO Scheme for Wireless Sensor Networks

Journal of Sensors ◽

10.1155/2014/589249 ◽

2014 ◽

Vol 2014 ◽

pp. 1-7 ◽

Cited By ~ 16

Author(s):

Jianpo Li ◽

Xue Jiang ◽

I-Tai Lu

Keyword(s):

Wireless Sensor Networks ◽

Energy Consumption ◽

Sensor Networks ◽

Energy Balance ◽

Network Lifetime ◽

Routing Algorithm ◽

Cluster Head ◽

Wireless Sensor ◽

Virtual Mimo ◽

Head Node

Wireless sensor networks are usually energy limited and therefore an energy-efficient routing algorithm is desired for prolonging the network lifetime. In this paper, we propose a new energy balance routing algorithm which has the following three improvements over the conventional LEACH algorithm. Firstly, we propose a new cluster head selection scheme by taking into consideration the remaining energy and the most recent energy consumption of the nodes and the entire network. In this way, the sensor nodes with smaller remaining energy or larger energy consumption will be much less likely to be chosen as cluster heads. Secondly, according to the ratio of remaining energy to distance, cooperative nodes are selected to form virtual MIMO structures. It mitigates the uneven distribution of clusters and the unbalanced energy consumption of the whole network. Thirdly, we construct a comprehensive energy consumption model, which can reflect more realistically the practical energy consumption. Numerical simulations analyze the influences of cooperative node numbers and cluster head node numbers on the network lifetime. It is shown that the energy consumption of the proposed routing algorithm is lower than the conventional LEACH algorithm and for the simulation example the network lifetime is prolonged about 25%.

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A Cluster Algorithm for Wireless Sensor Networks Based on Energy Efficiency

Applied Mechanics and Materials ◽

10.4028/www.scientific.net/amm.785.744 ◽

2015 ◽

Vol 785 ◽

pp. 744-750

Author(s):

Lei Gao ◽

Qun Chen

Keyword(s):

Energy Efficiency ◽

Wireless Sensor Networks ◽

Energy Consumption ◽

Sensor Networks ◽

Clustering Algorithm ◽

Cluster Head ◽

Selection Criterion ◽

Sensor Nodes ◽

Wireless Sensor ◽

Head Node

In order to solve the energy limited problem of sensor nodes in the wireless sensor networks (WSN), a fast clustering algorithm based on energy efficiency for wire1ess sensor networks is presented in this paper. In the system initialization phase, the deployment region is divided into several clusters rapidly. The energy consumption ratio and degree of the node are chosen as the selection criterion for the cluster head. Re-election of the cluster head node at this time became a local trigger behavior. Because of the range of the re-election is within the cluster, which greatly reduces the complexity and computational load to re-elect the cluster head node. Theoretical analysis indicates that the timing complexity of the clustering algorithm is O(1), which shows that the algorithm overhead is small and has nothing to do with the network size n. Simulation results show that clustering algorithm based on energy efficiency can provide better load balancing of cluster heads and less protocol overhead. Clustering algorithm based on energy efficiency can reduce energy consumption and prolong the network lifetime compared with LEACH protocol.

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Qualification of Cluster Header and Cluster Member in Wireless Sensor Networks

International Journal of Recent Technology and Engineering - 2 ◽

10.35940/ijrte.b1019.0782s619 ◽

2019 ◽

Vol 8 (2S6) ◽

pp. 101-105

Keyword(s):

Wireless Sensor Networks ◽

Sensor Networks ◽

Data Transmission ◽

Sensor Node ◽

Data Transfer ◽

Cluster Head ◽

Residual Energy ◽

Sensor Nodes ◽

Wireless Sensor ◽

Sink Node

Many researches have been proposed for efficiency of data transmission from sensor nodes to sink node for energy efficiency in wireless sensor networks. Among them, cluster-based methods have been preferred In this study, we used the angle formed with the sink node and the distance of the cluster members to calculate the probability of cluster head. Each sensor node sends measurement values to header candidates, and the header candidate node measures the probability value of the header with the value received from its candidate member nodes. To construct the cluster members, the data transfer direction is considered. We consider angle, distance, and direction as cluster header possibility value. Experimental results show that data transmission is proceeding in the direction of going to the sink node. We calculated and displayed the header possibility value of the neighbor nodes of the sensor node and confirmed the candidates of the cluster header for data transfer as the value. In this study, residual energy amount of each sensor node is not considered. In the next study, we calculate the value considering the residual energy amount of the node when measuring the header possibility value of the cluster.

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An Area Coverage Scheme Based on Fuzzy Logic and Shuffled Frog-Leaping Algorithm (SFLA) in Heterogeneous Wireless Sensor Networks

Mathematics ◽

10.3390/math9182251 ◽

2021 ◽

Vol 9 (18) ◽

pp. 2251

Author(s):

Amir Masoud Rahmani ◽

Saqib Ali ◽

Mohammad Sadegh Yousefpoor ◽

Efat Yousefpoor ◽

Rizwan Ali Naqvi ◽

...

Keyword(s):

Wireless Sensor Networks ◽

Fuzzy Logic ◽

Sensor Networks ◽

Network Lifetime ◽

Sensor Node ◽

Area Coverage ◽

Sensor Nodes ◽

Wireless Sensor ◽

Shuffled Frog Leaping Algorithm ◽

Shuffled Frog Leaping

Coverage is a fundamental issue in wireless sensor networks (WSNs). It plays a important role in network efficiency and performance. When sensor nodes are randomly scattered in the network environment, an ON/OFF scheduling mechanism can be designed for these nodes to ensure network coverage and increase the network lifetime. In this paper, we propose an appropriate and optimal area coverage method. The proposed area coverage scheme includes four phases: (1) Calculating the overlap between the sensing ranges of sensor nodes in the network. In this phase, we present a novel, distributed, and efficient method based on the digital matrix so that each sensor node can estimate the overlap between its sensing range and other neighboring nodes. (2) Designing a fuzzy scheduling mechanism. In this phase, an ON/OFF scheduling mechanism is designed using fuzzy logic. In this fuzzy system, if a sensor node has a high energy level, a low distance to the base station, and a low overlap between its sensing range and other neighboring nodes, then this node will be in the ON state for more time. (3) Predicting the node replacement time. In this phase, we seek to provide a suitable method to estimate the death time of sensor nodes and prevent possible holes in the network, and thus the data transmission process is not disturbed. (4) Reconstructing and covering the holes created in the network. In this phase, the goal is to find the best replacement strategy of mobile nodes to maximize the coverage rate and minimize the number of mobile sensor nodes used for covering the hole. For this purpose, we apply the shuffled frog-leaping algorithm (SFLA) and propose an appropriate multi-objective fitness function. To evaluate the performance of the proposed scheme, we simulate it using NS2 simulator and compare our scheme with three methods, including CCM-RL, CCA, and PCLA. The simulation results show that our proposed scheme outperformed the other methods in terms of the average number of active sensor nodes, coverage rate, energy consumption, and network lifetime.

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Energy-Efficient QoS-Aware Intelligent Hybrid Clustered Routing Protocol for Wireless Sensor Networks

Journal of Sensors ◽

10.1155/2019/8691878 ◽

2019 ◽

Vol 2019 ◽

pp. 1-12

Author(s):

Parvinder Singh ◽

Rajeshwar Singh

Keyword(s):

Wireless Sensor Networks ◽

Sensor Networks ◽

Network Lifetime ◽

Routing Protocol ◽

Large Scale ◽

Fitness Function ◽

Geographical Area ◽

Cluster Head ◽

Sensor Nodes ◽

Wireless Sensor

A wireless sensor network consists of numerous low-power microsensor devices that can be deployed in a geographical area for remote sensing, surveillance, control, and monitoring applications. The advancements of wireless devices in terms of user-friendly interface, size, and deployment cost have given rise to many smart applications of wireless sensor networks (WSNs). However, certain issues like energy efficiency, long lifetime, and communication reliability restrict their large scale utilization. In WSNs, the cluster-based routing protocols assist nodes to collect, aggregate, and forward sensed data from event regions towards the sink node through minimum cost links. A clustering method helps to improve data transmission efficiency by dividing the sensor nodes into small groups. However, improper cluster head (CH) selection may affect the network lifetime, average network energy, and other quality of service (QoS) parameters. In this paper, a multiobjective clustering strategy is proposed to optimize the energy consumption, network lifetime, network throughput, and network delay. A fitness function has been formulated for heterogenous and homogenous wireless sensor networks. This fitness function is utilized to select an optimum CH for energy minimization and load balancing of cluster heads. A new hybrid clustered routing protocol is proposed based on fitness function. The simulation results conclude that the proposed protocol achieves better efficiency in increasing the network lifetime by 63%, 26%, and 10% compared with three well-known heterogeneous protocols: DEEC, EDDEEC, and ATEER, respectively. The proposed strategy also attains better network stability than a homogenous LEACH protocol.

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Cluster Head Relocation Based on Selfish Herd Hypothesis for Prolonging the Life Span of Wireless Sensor Networks

Electronics ◽

10.3390/electronics7120403 ◽

2018 ◽

Vol 7 (12) ◽

pp. 403 ◽

Cited By ~ 1

Author(s):

Goran Popovic ◽

Goran Djukanovic ◽

Dimitris Kanellopoulos

Keyword(s):

Wireless Sensor Networks ◽

Sensor Networks ◽

Network Lifetime ◽

Network Performance ◽

Cluster Head ◽

Base Station ◽

Sensor Nodes ◽

Wireless Sensor ◽

Total Energy Consumption ◽

Selfish Herd

Clustering achieves energy efficiency and scalable performance in wireless sensor networks (WSNs). A cluster is formed of several sensor nodes, one of them selected as the cluster head (CH). A CH collects information from the cluster members and sends aggregated data to the base station or another CH. In such a hierarchical WSN, some nodes are possibly moveable or nomadic (relocated periodically), while others are static. The mobility of sensor nodes can improve network performance and prolong network lifetime. This paper presents the idea of mobile, solar-powered CHs that relocate themselves inside clusters in such a way that the total energy consumption in the network is reduced and the network lifetime is extended. The positioning of CHs is made in each round based on a selfish herd hypothesis, where the leader retreats to the center of gravity. Based on this idea, the CH-active algorithm is proposed in this study. Simulation results show that this algorithm has benefits in terms of network lifetime and in the prolongation of the duration of network stability period.

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Hesitant Fuzzy Entropy-Based Opportunistic Clustering and Data Fusion Algorithm for Heterogeneous Wireless Sensor Networks

Sensors ◽

10.3390/s20030913 ◽

2020 ◽

Vol 20 (3) ◽

pp. 913

Author(s):

Junaid Anees ◽

Hao-Chun Zhang ◽

Sobia Baig ◽

Bachirou Guene Lougou ◽

Thomas Gasim Robert Bona

Keyword(s):

Wireless Sensor Networks ◽

Energy Consumption ◽

Sensor Networks ◽

Data Fusion ◽

Network Lifetime ◽

Cluster Formation ◽

Fuzzy Entropy ◽

Sensor Nodes ◽

Wireless Sensor ◽

Heterogeneous Clustering

Limited energy resources of sensor nodes in Wireless Sensor Networks (WSNs) make energy consumption the most significant problem in practice. This paper proposes a novel, dynamic, self-organizing Hesitant Fuzzy Entropy-based Opportunistic Clustering and data fusion Scheme (HFECS) in order to overcome the energy consumption and network lifetime bottlenecks. The asynchronous working-sleeping cycle of sensor nodes could be exploited to make an opportunistic connection between sensor nodes in heterogeneous clustering. HFECS incorporates two levels of hierarchy in the network and energy heterogeneity is characterized using three levels of energy in sensor nodes. HFECS gathers local sensory data from sensor nodes and utilizes multi-attribute decision modeling and the entropy weight coefficient method for cluster formation and the cluster head election procedure. After cluster formation, HFECS uses the same techniques for performing data fusion at the first hierarchical level to reduce the redundant information flow from the first-second hierarchical levels, which can lead to an improvement in energy consumption, better utilization of bandwidth and extension of network lifetime. Our simulation results reveal that HFECS outperforms the existing benchmark schemes of heterogeneous clustering for larger network sizes in terms of half-life period, stability period, average residual energy, network lifetime, and packet delivery ratio.

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