Turkish Journal of Computer and Mathematics Education
Journal license

Journal

Turkish Journal of Computer and Mathematics Education


Volume
& Issue

Volume 10, Issue 2


Published
on


Pages

641-648


DOI

Article

An Enhanced Distributed Clustering Methodology and Data Aggregation in Connecting Dissimilar Wireless Sensor Networks


Authors

K. Sundaramoorthy Affiliation:
Professor & Head, Department of Information Technology, Agni College of Technology, Chennai, Tamil Nadu, India
, V. Janakiraman Affiliation:
Professor, Department of Electronics & Communication Engineering, Dhanalakshmi Srinivasan College of Engineering and Technology, Mamallapuram, Tamil Nadu, India
, A. Vivek Yoganand Affiliation:
Associate Professor, Department of Computer Science and Engineering, Jayam College of Engineering and Technology, Dharmapuri, Tamil Nadu, India
, E. Gajendran Affiliation:
Professor, Department of Computer Science and Engineering, Malla Reddy Institute of Technology and Science, Dhulapally, Secunderabad, Telangana, India
and S. Arif Abdul Rahuman Affiliation:
Professor, Department of Computer Science and Engineering, Universal College of Engineering and Technology, Valliyur, Tamil Nadu, India


Abstract

One of the major advantages of wireless sensor network is their ability to operate in unattended, harsh environments in which existing human-in-the-loop monitoring schemes are uncertain, inefficient and sometimes impossible. Therefore, wireless sensors are expected to be deployed randomly in the predetermined area of interest by a relatively uncontrolled manner. Given the huge area to be covered, the short lifespan of the battery-operated wireless sensors and the possibility of having damaged sensor nodes during deployment, large population of sensors are expected in the majority of wireless sensor applications. In centralized clustering, the cluster head is fixed. The rest of the nodes in the cluster act as member nodes. In distributed clustering, the cluster head is not fixed. The cluster head keeps on shifting from node to node within the cluster on the basis of some parameters. Hybrid clustering is the combination of both centralized clustering and distributed clustering mechanisms. This paper gives a brief overview on clustering process in wireless sensor networks and an enhanced distributed clustering methodology and data aggregation in connecting dissimilar wireless sensor Networks. The proposed method is compared with LEACH and HEED Clustering methods.


Keywords

Distributed clustering algorithm, Energy efficiency, Delay, Throughput


Citation

Sundaramoorthy, K., Janakiraman, V., Yoganand, A. V., Gajendran, E., & Rahuman, S. A. A. (2019). An enhanced distributed clustering methodology and data aggregation in connecting dissimilar wireless sensor networks. Turkish Journal of Computer and Mathematics Education, 10(2), 641–648.

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