Loading

WSN Clustering Based on EECI (Energy Efficient Clustering using Interconnection) Method
Gajendran Malshetty1, Basavaraj Mathapati2

1Gajendran Malshetty, Assistant Professor, Computer Science & Engineering, Appa Institute of Engineering & Technology, Kalaburgi.
2Dr. Basavaraj Mathapati, Professor, Computer Science & Engineering, Appa Institute of Engineering & Technology, Kalaburgi, India.

Manuscript received on October 11, 2019. | Revised Manuscript received on 23 October, 2019. | Manuscript published on November 10, 2019. | PP: 3564-3571 | Volume-9 Issue-1, November 2019. | Retrieval Number: L37991081219/2019©BEIESP | DOI: 10.35940/ijitee.A3799.119119
Open Access | Ethics and Policies | Cite | Mendeley | Indexing and Abstracting
© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)

Abstract: In WSN, clustering gives an effective way to enhance the network lifetime. Moreover It has been observed that the clustering algorithm utilizes the two main technique first is selection of cluster head and cycling it periodically in order to distribute the energy among the clusters and this in terms increases the lifetime of network. Another challenge comes with this is minimize the energy consumption. In past several algorithm has been proposed to increase the lifetime of the network and energy consumption, however these methodologies lacks from efficiency. In this paper, we have proposed a methodologies named as EE-CI (Energy Efficient Clustering using Interconnection), along with the random updation. Here the networks are parted into different clusters, the cluster updation are done based on the CHC scheme. Moreover, in proposed methodology cluster updation and data sample is determined through the change in sensor data. Here we propose a method for sampling sensor and CHC for selecting the cluster head to balance the energy and improvise the energy efficiency. Moreover, the proposed methodology is evaluated and the result is demonstrated by considering the Leach as existing methodology, experiments results shows that the proposed methodology outperforms the existing methodology.
Keywords: WSN, Clustering, EECI.
Scope of the Article: Clustering