Zone Divisional Approach for Energy Balanced Clustering Protocol in Wireless Sensor Network

Assari, Younes El; Arioua, Mounir; Oualkadi, Ahmed El; Ez‐zazi, Imad

doi:10.1145/3102304.3102330

Cited by 7 publications

(5 citation statements)

References 21 publications

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“…But, present works over deterministic unequal clustering method were discussed as it relatively close to the projected method. At present times, depending on the weight-based methods, many clustering methods (Lalitha et al, 2017;El Assari et al, 2017) were presented. In Lalitha et al (2017), the monitoring region is divided into grids with fixed sizes and depending on distance among the grid midpoints, it chooses the CHs.…”

Section: Related Workmentioning

confidence: 99%

Social spider-based unequal clustering protocol for wireless sensor environment for smart cities

Buvanesvari

Begum

2020

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Wireless sensor networks involve a massive number of sensor nodes often deployed to observe the physical world. Energy efficiency is the challenging issue in the design of WSN. For attaining energy efficient characteristic, clustering techniques has been employed. But, it suffers from hot spot issue which defines that the cluster heads (CHs) closet to base station are burdened with more traffic compared to CHs located far away from BS due to multihop communication. To resolving this, we present a social spider-based unequal clustering protocol (SSUCP) for WSN. SSUCP is based on the nature of social spiders to select the proper CHs and cluster size. Based on the fitness functions and node parameters, the interested decision of selecting the proper CHs and cluster size were made. The SSUCP is implemented in MATLAB and an extensive experimentation takes place under three situations based on distance to BS for ensuring the consistent results of the proposed method. In addition, the SSUCP is validated in terms of energy efficiency and network lifetime analysis. The attained experimental outcome verified that the SSUCP is the superior one over the compared methods.

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Section: Related Workmentioning

confidence: 99%

Social spider-based unequal clustering protocol for wireless sensor environment for smart cities

Buvanesvari

Begum

2020

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“…ECUC divides the network into coronas with an equal thickness ( Fig.1.a). Then it is divided into constant angle sectors ( Fig.1.b) called Clustered Corona-based WSN (CCWSN) [28]. By employing the clustering on CBWSNs, energy efficiency, easier management and scalability can be achieved [22].…”

Section: System Modelmentioning

confidence: 99%

Energy-Efficient and Coverage-Guaranteed Unequal-Sized Clustering for Wireless Sensor Networks

et al. 2019

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In the last years, due to the limited resources of consumer products, energy-saving is known as one of the design challenges of Wireless Sensor Networks (WSNs). Clustering is a practical technique to enhance the performance of the network including energy efficiency, network scalability, and network easier management. In cluster-based networks, the size of clusters has a key role in the network power consumption. Non-optimized clustering results in increasing the power consumption of the whole network. The small size clusters leads to appear coverage hole in the network, as well as this property is the opposite of being the scalability of the network. In addition, in non-optimized clusters, reducing the energy consumption of the nodes as the key objective of clustering, cannot be pursued, thus the clustering will result contrary. Consequently, the energy consumption reduction after clustering can be guaranteed by considering the power consumption of nodes before clustering in cluster size optimization. Hence, in this paper, an Energyefficient and Coverage-guaranteed Unequal-sized Clustering (ECUC) scheme is proposed which considers both energy and coverage issues simultaneously in optimizing the cluster size. Based on the simulation results, the proposed scheme remarkably enhances the network lifetime by reducing the total dissipated energy while guarantying the coverage issue. INDEX TERMS Wireless sensor networks, clustering; cluster size, coverage hole, energy efficiency.

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“…Several clustering approaches [18,19,20,21,22,23,24,25,26] have been proposed recently based on the weight-based technique. Among them, the proposed approach presented in Ref.…”

Section: Literature Reviewmentioning

confidence: 99%

“…Similarly, the proposal in Ref. [19] divides the monitoring area into fixed sized zones and selects the CHs based on the residual energy. Again, the approach presented in Ref.…”

Section: Literature Reviewmentioning

confidence: 99%

Energy-Balancing Unequal Clustering Approach to Reduce the Blind Spot Problem in Wireless Sensor Networks (WSNs)

Islam

Dey

Sampalli

2018

Sensors

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Wireless Sensor Networks (WSNs) have become a significant part of surveillance techniques. With unequal clustering approaches and multi-hop communication, WSNs can balance energy among the clusters and serve a wide monitoring area. Recent research has shown significant improvements in unequal clustering approaches by forming clusters prior to the selection of cluster heads. These improvements adopt different geometric fractals, such as the Sierpinski triangle, to divide the monitoring area into multiple clusters. However, performance of such approaches can be improved further by cognitive partitioning of the monitoring area instead of adopting random fractals. This paper proposes a novel clustering approach that partitions the monitoring area in a cognitive way for balancing the energy consumption. In addition, the proposed approach adopts a two-layered scrutinization process for the selection of cluster heads that ensures minimum energy consumption from the network. Furthermore, it reduces the blind spot problem that escalates once the nodes start dying. The proposed approach has been tested in terms of number of alive nodes per round, energy consumption of nodes and clusters, and distribution of alive nodes in the network. Results show a significant improvement in balancing the energy consumption among clusters and a reduction in the blind spot problem.

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Zone Divisional Approach for Energy Balanced Clustering Protocol in Wireless Sensor Network

Cited by 7 publications

References 21 publications

Social spider-based unequal clustering protocol for wireless sensor environment for smart cities

Social spider-based unequal clustering protocol for wireless sensor environment for smart cities

Energy-Efficient and Coverage-Guaranteed Unequal-Sized Clustering for Wireless Sensor Networks

Energy-Balancing Unequal Clustering Approach to Reduce the Blind Spot Problem in Wireless Sensor Networks (WSNs)

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