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ONCTR: Optimum Number of Clusters and Transmission Range based Clustering in Wireless Sensor Networks

Sumedha Sirsikar
- Vol. 8, Iss: 3, pp 3454-3462
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TLDR
A new algorithm is proposed, where the number of clusters obtained from proposed method is compared with state-of-the-art methods, and it is revealed that optimum number of cluster obtained is less than state of theart method.
Abstract
The field of Wireless Sensor Network (WSN) is striving for devising ways to minimize energy consumption. Clustering reduces energy consumption and increases scalability along with network lifetime. There is a need to identify appropriate number of clusters to balance traffic in network which is a challenging task for energy efficient WSN. Manually it is difficult to decide number of clusters. Finding optimum number of clusters to minimize energy consumption is the major issue in WSN. Existing algorithms find optimum number of clusters but not optimum transmission range. This paper contributes towards the aforesaid issue by proposing a novel method to find optimum number of clusters and a first attempt to find optimum transmission range. We report a new algorithm, where the number of clusters obtained from proposed method is compared with state-of-the-art methods. Extensive experiments are carried out and result comparison with state-of-the-art approaches demonstrate that our method shows significantly better performance. The analysis reveals that optimum number of clusters obtained by proposed method is less than state-of-the-art method. It is especially suitable for clustering in WSN.

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References
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Journal ArticleDOI

An application-specific protocol architecture for wireless microsensor networks

TL;DR: This work develops and analyzes low-energy adaptive clustering hierarchy (LEACH), a protocol architecture for microsensor networks that combines the ideas of energy-efficient cluster-based routing and media access together with application-specific data aggregation to achieve good performance in terms of system lifetime, latency, and application-perceived quality.
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Determining the number of clusters/segments in hierarchical clustering/segmentation algorithms

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Journal Article

EBK-Means: A Clustering Technique based on Elbow Method and K-Means in WSN

TL;DR: This research is working on the development of a hybrid model using LEACH based energy efficient and K-means based quick clustering algorithms to produce a new cluster scheme for WSNs with dynamic selection of the number of the clusters automatically.
Journal ArticleDOI

Optimal Number of Clusters in Dense Wireless Sensor Networks: A Cross-Layer Approach

TL;DR: This paper suggests a physical (PHY)/medium access control (MAC)/network (NET) cross-layer analytical approach for determining the optimal number of clusters, with the objective of minimizing energy consumption in a high-density sensor network.
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