Recent trends in clustering algorithms for wireless sensor networks: A comprehensive review

Al-Sulaifanie, Adnan Ismail; Al-Sulaifanie, Bayez K.; Biswas, Subir

doi:10.1016/j.comcom.2022.05.006

Cited by 21 publications

(6 citation statements)

References 207 publications

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“…Different methods are investigated based on both conventional and Optimization approaches. However, research priorities does not emphasize multi-hop dynamic transmissions installation of nodes and finding Optimizing issues within 3D networks [2] 2018 More efforts are required to address the problem of mobility and heterogeneity. [5] 2020…”

Section: Related Workmentioning

confidence: 99%

“…The size, simplicity, cost-effectiveness, and ease of use of Wireless Sensor Networks (WSN) make them noteworthy and promising for deployment. It is based on wireless sensor nodes placed in an area of interest to examine and record environmental information from the vibration, sound, temperature and light transmits the data to the base station as a result [1][2][3]. Thus, these node sets have the benefit of ensuring accurate sensing.…”

Section: Introductionmentioning

confidence: 99%

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Survey on Various Aspects of Clustering in Wireless Sensor Networks Employing Classical, Optimization, and Machine Learning Techniques

Gunjal

Kulkarni

2023

IJRITCC

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A wide range of academic scholars, engineers, scientific and technology communities are interested in energy utilization of Wireless Sensor Networks (WSNs). Their extensive research is going on in areas like scalability, coverage, energy efficiency, data communication, connection, load balancing, security, reliability and network lifespan. Individual researchers are searching for affordable methods to enhance the solutions to existing problems that show unique techniques, protocols, concepts, and algorithms in the wanted domain. Review studies typically offer complete, simple access or a solution to these problems. Taking into account this motivating factor and the effect of clustering on the decline of energy, this article focuses on clustering techniques using various wireless sensor networks aspects. The important contribution of this paper is to give a succinct overview of clustering.

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Section: Related Workmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Survey on Various Aspects of Clustering in Wireless Sensor Networks Employing Classical, Optimization, and Machine Learning Techniques

Gunjal

Kulkarni

2023

IJRITCC

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“…Note that the detailed policies for the identification of clusters and the consequent selection of cluster members is out of the scope of the current paper. For an extensive discussion of the design of clustering algorithms for ad hoc and sensor networks that are guaranteed to have an assigned number of cluster members, please refer to [26].…”

Section: Overview Of Cinementioning

confidence: 99%

Clustered Distributed Learning Exploiting Node Centrality and Residual Energy (CINE) in WSNs

Galluccio

Mertens

Morabito

2023

Network

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With the explosion of big data, the implementation of distributed machine learning mechanisms in wireless sensor networks (WSNs) is becoming required for reducing the number of data traveling throughout the network and for identifying anomalies promptly and reliably. In WSNs, the above need has to be considered along with the limited energy and processing resources available at the nodes. In this paper, we tackle the resulting complex problem by designing a multi-criteria protocol CINE that stands for “Clustered distributed learnIng exploiting Node centrality and residual Energy” for distributed learning in WSNs. More specifically, considering the energy and processing capabilities of nodes, we design a scheme that assumes that nodes are partitioned in clusters and selects a central node in each cluster, called cluster head (CH), that executes the training of the machine learning (ML) model for all the other nodes in the cluster, called cluster members (CMs). In fact, CMs are responsible for executing the inference only. Since the CH role requires the consumption of more resources, the proposed scheme rotates the CH role among all nodes in the cluster. The protocol has been simulated and tested using real environmental data sets.

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“…Due to their low price, sensor nodes are generally used in large numbers, and due to the environmental limitations of the application scenario, timely battery replacement cannot be achieved. Given the above problems, MWSN needs a clustering communication protocol with low power consumption and high transmission efficiency [5]. The construction of the protocol especially needs to consider how to effectively alleviate the impact of node movement on cluster stability and link connection time.…”

Section: Introductionmentioning

confidence: 99%

“…Many clustering routing protocols [5,[8][9][10][11][12][13][14][15] were developed to alleviate the impact of node movement on clustering. These protocols fall broadly into three categories, depending on the different methods, namely multi-hop routing [8][9][10], improved weighted algorithm with movement factor [5,11,12], and hybrid protocols combining active and reactive protocols [13][14][15]. The weighted clustering algorithm comprehensively considers the parameters of network nodes.…”

Section: Introductionmentioning

confidence: 99%

Research on Stability-Enhanced Clustering Algorithm Based on Distributed Node Status Judgment in MWSN

Lei

Zhang

et al. 2022

Electronics

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Node mobility improves the self-deployment capability of the network; meanwhile, it also leads to frequent interruption of communication links and severe packet loss. Mitigating the negative impact of node movement on cluster stability is a new challenge. Existing clustering protocols try to use multi-hop data transmission, but they do not deal with the increase in communication overhead. This paper proposes a distributed node status judgment-based weighted clustering algorithm to solve the problems of easily broken communication links and excessive node reaffiliation in mobile wireless sensor networks (MWSNs). The protocol establishes intra-cluster second-level communication in order to solve the problem of the sudden interruption of dynamic communication links. A node status judgment algorithm was constructed to analyze the motion behavior of sensor nodes, distinguish the node states, and screen multiple communication nodes, thereby alleviating the transmission delay caused by complex routing. The extended Kalman filter (EKF) was used to filter the sensor noise in a non-ideal environment and to predict the actual position of nodes. The simulation results explain that the proposed protocol can effectively reduce node reaffiliation and the dominant set’s update frequency when the node runs at medium and high speeds while simultaneously maintaining low energy consumption.

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Recent trends in clustering algorithms for wireless sensor networks: A comprehensive review

Cited by 21 publications

References 207 publications

Survey on Various Aspects of Clustering in Wireless Sensor Networks Employing Classical, Optimization, and Machine Learning Techniques

Survey on Various Aspects of Clustering in Wireless Sensor Networks Employing Classical, Optimization, and Machine Learning Techniques

Clustered Distributed Learning Exploiting Node Centrality and Residual Energy (CINE) in WSNs

Research on Stability-Enhanced Clustering Algorithm Based on Distributed Node Status Judgment in MWSN

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