Clustering Techniques in Wireless Sensor Network: A Review
15 Dec 2017-International Journal of Computer Applications (Foundation of Computer Science (FCS), NY, USA)-Vol. 179, Iss: 5, pp 30-34
TL;DR: This paper examines the various methods of clustering which are centralized, distributed and hybrid utilized in Sensor Networks and presents a comparative study of various clustering algorithms and the issues of clusters in WSNs.
Abstract: Wireless sensor system includes hundreds to thousands of sensor nodes that helps in collecting different information including temperature, sound, area, etc. It’s generally difficult to recharge or change the sensor nodes which may have confined battery capacity. Energy efficiency is therefore a key problem in sustaining the network. Certainly one of the most used alternatives to make WSNs energy-efficient is to cluster the networks. Various clustering techniques are accustomed to effectively optimize or enhance the energy of sensor nodes. In this paper we have examined the various methods of clustering which are centralized, distributed and hybrid utilized in Sensor Networks. This paper also presents a comparative study of various clustering algorithms and the issues of clustering in WSNs.
Citations
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TL;DR: This study primarily concentrated on multihop routing in a clustering environment and provided useful information to the audience to be used while they investigate their research ideas and to develop a novel model in order to overcome the drawbacks that are present in the WSN-based clustering models.
Abstract: In today’s sensor network research, numerous technologies are used for the enhancement of earlier studies that focused on cost-effectiveness in addition to time-saving and novel approaches. This survey presents complete details about those earlier models and their research gaps. In general, clustering is focused on managing the energy factors in wireless sensor networks (WSNs). In this study, we primarily concentrated on multihop routing in a clustering environment. Our study was classified according to cluster-related parameters and properties and is subdivided into three approach categories: (1) parameter-based, (2) optimization-based, and (3) methodology-based. In the entire category, several techniques were identified, and the concept, parameters, advantages, and disadvantages are elaborated. Based on this attempt, we provide useful information to the audience to be used while they investigate their research ideas and to develop a novel model in order to overcome the drawbacks that are present in the WSN-based clustering models.
26 citations
TL;DR: In this article, a novel concept for clustering is introduced which is multi weight chicken swarm based genetic algorithm for energy efficient clustering (MWCSGA), which mainly consists of six sections: system model, chicken swarm optimization, genetic algorithm, CCSO-GA cluster head selection, multi weight clustering model, inter cluster and intra cluster communication.
Abstract: Nowadays due to smart environment creation there is a rapid growth in wireless sensor network (WSN) technology real time applications. The most critical resource in in WSN is battery power. One of the familiar methods which mainly concentrate in increasing the power factor in WSN is clustering. In this research work, a novel concept for clustering is introduced which is multi weight chicken swarm based genetic algorithm for energy efficient clustering (MWCSGA). It mainly consists of six sections. They are system model, chicken swarm optimization, genetic algorithm, CCSO-GA cluster head selection, multi weight clustering model, inter cluster, and intra cluster communication. In the performance evaluation the proposed model is compared with few earlier methods such as Genetic Algorithm-Based Energy-Efficient Adaptive Clustering Protocol For Wireless Sensor Networks (GA-LEACH), Low energy adaptive Clustering hierarchy approach for WSN (MW-LEACH) and Chicken Swarm Optimization based Genetic Algorithm (CSOGA). During the comparison it is proved that our proposed method performed well in terms of energy efficiency, end to end delay, packet drop, packet delivery ratio and network throughput.
22 citations
01 Jul 2020
TL;DR: The various clustering approaches used by wireless sensor networks got to learn and analyzed and it is shown how these approaches help in sustaining the network.
Abstract: Wireless sensor networks are used in diverse areas such as battlefields, security, hospitals, universities, etc. It has been used in our everyday lives. Its development is rising day by day. Wireless sensor network includes hundreds to thousands of sensor nodes which aid in gathering various information like temperature, sound, location, etc. Recharging or modifying sensor nodes which might have limited battery power is usually difficult. Therefore, energy conservation is a crucial concern in sustaining the network. Clustering the networks is definitely one of the most common solutions for rendering WSNs energy. In this paper, the various clustering approaches used by wireless sensor networks got to learn and analyzed.
10 citations
01 Mar 2020
TL;DR: Particle Swarm Optimization (PSO) based load balancing clustering algorithm with optimal placement of CHs is proposed and the lifetime, fitness values and convergence plot for three different scenarios are simulated and it is revealed that the lifetime of optimal CH placement is superior.
Abstract: Energy efficiency is the major concern in Wireless Sensor Networks (WSNs) as it is the key factor for lifetime enhancement. Due to the limited and irreplaceable battery source of WSNs, optimal usage of energy resources is very essential. Therefore, Clustering is an efficient methodology for extending the network lifetime by reducing the energy consumption. The objective of this paper is to maximize the lifetime of WSNs. In this paper, Particle Swarm Optimization (PSO) based load balancing clustering algorithm with optimal placement of CHs is proposed and the lifetime, fitness values and convergence plot for three different scenarios are simulated. Finally, the lifetime of optimal CH placement is compared with the fixed CH placement and the results revealed that the lifetime of optimal CH placement is superior.
2 citations
Cites methods from "Clustering Techniques in Wireless S..."
...Several heuristic methods have been extended for lifetime enhancement in WSNs [3] and one such approach is Low-Energy Adaptive Clustering Hierarchy (LEACH)....
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29 Sep 2021
TL;DR: In this article, the authors proposed a head cluster method to support the lifetime of WSN nodes to achieve battery-saving protocol, which will reduce the power consumption in data transmission by using the concept of head cluster and cluster member.
Abstract: Nowadays, wireless sensor networks (wsn) have many implementations in agriculture, animal husbandry, education, and many more. To support the lifetime of wsn nodes to achieve battery-saving protocol, we propose the head cluster method. This protocol will reduce the power consumption in data transmission by using the concept of head cluster and cluster member. In this method, communication using the cluster head is only carried out by the group head to save energy consumed. Based on the simulation results, the network lifetime with the cluster head method can be increased compared to a single hop.
1 citations
References
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TL;DR: A taxonomy and general classification of published clustering schemes for WSNs is presented, highlighting their objectives, features, complexity, etc and comparing of these clustering algorithms based on metrics such as convergence rate, cluster stability, cluster overlapping, location-awareness and support for node mobility.
2,283 citations
TL;DR: This paper synthesises existing clustering algorithms news's and highlights the challenges in clustering.
Abstract: A wireless sensor network (WSN) consisting of a large number of tiny sensors can be an effective tool for gathering data in diverse kinds of environments. The data collected by each sensor is communicated to the base station, which forwards the data to the end user. Clustering is introduced to WSNs because it has proven to be an effective approach to provide better data aggregation and scalability for large WSNs. Clustering also conserves the limited energy resources of the sensors. This paper synthesises existing clustering algorithms in WSNs and highlights the challenges in clustering.
1,097 citations
TL;DR: A survey of routing protocols for Wireless Sensor Network is given and their strengths and limitations are compared.
Abstract: Advances in wireless sensor network (WSN) technology has provided the availability of small and low-cost sensor nodes with capability of sensing various types of physical and environmental conditions, data processing, and wireless communication. Variety of sensing capabilities results in profusion of application areas. However, the characteristics of wireless sensor networks require more effective methods for data forwarding and processing. In WSN, the sensor nodes have a limited transmission range, and their processing and storage capabilities as well as their energy resources are also limited. Routing protocols for wireless sensor networks are responsible for maintaining the routes in the network and have to ensure reliable multi-hop communication under these conditions. In this paper, we give a survey of routing protocols for Wireless Sensor Network and compare their strengths and limitations.
582 citations
TL;DR: A state-of-the-art and comprehensive survey on clustering approaches in WSNs, which surveys the proposed approaches in the past few years in a classified manner and compares them based on different metrics such as mobility, cluster count, cluster size, and algorithm complexity.
433 citations
"Clustering Techniques in Wireless S..." refers background in this paper
...A typical clustered sensor network [2]...
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...Cluster features are divided on the cornerstone of the specifications of clusters, like the number of clusters ,cluster size ,intra-cluster communication ,inter-cluster communication The key portion of each and every clustering algorithm is the CH election, the selected CHs have a considerable impact on the clustering algorithm performance or efficiency and some traits of the CHs are: Mobility ,Node type ,Role , Clustering process ,Method ,CH selection , Algorithm complexity , Clustering nature , Clustering dynamism [2]....
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...Each signal node usually includes a small CPU, storage, receiver/transmitter radio and a power product [2]....
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...Eventually an individual gets the information from the BS through the Internet [2]....
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20 Jun 2004
TL;DR: A cost based comparative study of homogeneous and heterogeneous clustered sensor networks, focusing on the case where the base station is remotely located and the sensor nodes are not mobile, shows that M-LEACH has better energy efficiency than LEACH in many cases.
Abstract: This paper presents a cost based comparative study of homogeneous and heterogeneous clustered sensor networks. We focus on the case where the base station is remotely located and the sensor nodes are not mobile. Since we are concerned with the overall network dimensioning problem, we take into account the manufacturing cost of the hardware as well as the battery energy of the nodes. A homogeneous sensor network consists of identical nodes, while a heterogeneous sensor network consists of two or more types of nodes (organized into hierarchical clusters). We first consider single hop clustered sensor networks (nodes use single hopping to reach the cluster heads). We use LEACH as the representative single hop homogeneous network, and a sensor network with two types of nodes as a representative single hop heterogeneous network. For multihop homogeneous networks (nodes use multihopping to reach the cluster head), we propose and analyze a multihop variant of LEACH that we call M-LEACH. We show that M-LEACH has better energy efficiency than LEACH in many cases. We then compare the cost of multihop clustered sensor networks with M-LEACH as the representative homogeneous network, and a sensor network with two types of nodes (that use in-cluster multi-hopping) as the representative heterogeneous network.
424 citations
"Clustering Techniques in Wireless S..." refers methods in this paper
...In order to assure minimal power usage and uniform load distribution over the network, sensor nodes are arranged into clusters [4] Clustering is one of the very effective methods in data forwarding in providing convenient framework for resource management....
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