Redundant ClusterHead Selection and Quality of Data Reconstruction Through Clustering for Large-Scale WSNs

Authors

  • Edali Jasmine Cleticia I  PG Scholar, CSE Department, SRM University, Chennai, TamilNadu, India
  • Feiroz Khan T H  Assistant Professor (OG) CSE Department, SRM University, Chennai, TamilNadu, India
  • Rosy Jacob  Scholar Software Engineering Department, University of Westmister, London, UK

DOI:

https://doi.org/10.32628/CSEIT217218

Keywords:

Cluster Head Selection, Clustering, Data Quality, Energy Efficiency, Wireless Sensor Network.

Abstract

WSN is a large network that consists of a group of spatially distributed sensors nodes. Sensor nodes are partial in power, computational capacities and memory. Sensor nodes compactly installed to monitor physical or environmental conditions, such as temperature, pressure, pollutants. This study examines a Cluster Head Selection (CHs) and takes the CH with the maximum outstanding energy node and less broadcast distance between the CH and BS. It discovered ideal stability between data quality, energy expenditure, and community management ease. The key decision is that the proposal of WSN algorithms must be processing-oriented. i.e., the process of energy on both the Clustering and in-network processing, which ensures both energy efficiency and data quality. Hence, it is more operational to achieve the wireless sensor networks' major loads, which persist the network lifetime.

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Published

2021-04-30

Issue

Section

Research Articles

How to Cite

[1]
Edali Jasmine Cleticia I, Feiroz Khan T H, Rosy Jacob, " Redundant ClusterHead Selection and Quality of Data Reconstruction Through Clustering for Large-Scale WSNs" International Journal of Scientific Research in Computer Science, Engineering and Information Technology(IJSRCSEIT), ISSN : 2456-3307, Volume 7, Issue 2, pp.62-69, March-April-2021. Available at doi : https://doi.org/10.32628/CSEIT217218