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Energy Efficient Clustering using Modified Multi-Hop Clustering

Energy Efficient Clustering using Modified Multi-Hop Clustering

Vimala M., Rajeev Ranjan
Copyright: © 2019 |Volume: 8 |Issue: 2 |Pages: 13
ISSN: 2155-6261|EISSN: 2155-627X|EISBN13: 9781522567615|DOI: 10.4018/IJWNBT.2019070103
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MLA

Vimala M., and Rajeev Ranjan. "Energy Efficient Clustering using Modified Multi-Hop Clustering." IJWNBT vol.8, no.2 2019: pp.18-30. http://doi.org/10.4018/IJWNBT.2019070103

APA

Vimala M. & Ranjan, R. (2019). Energy Efficient Clustering using Modified Multi-Hop Clustering. International Journal of Wireless Networks and Broadband Technologies (IJWNBT), 8(2), 18-30. http://doi.org/10.4018/IJWNBT.2019070103

Chicago

Vimala M., and Rajeev Ranjan. "Energy Efficient Clustering using Modified Multi-Hop Clustering," International Journal of Wireless Networks and Broadband Technologies (IJWNBT) 8, no.2: 18-30. http://doi.org/10.4018/IJWNBT.2019070103

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Abstract

In recent years, WSN has been widely used for building the decision support system (DSS) for solving the real-world problem. Moreover, out of several fields, one of the interesting fields that requires DSS is the monitoring of agriculture environment. Nowadays, monitoring an agricultural environment has become one of the essential fields. IoT has been one of the eminent technologies in recent years and WSN model has played the parallel role into it. These sensors have a limited power supply and this affects the efficiency of the algorithm. In the past, several methods have been proposed for efficient clustering, however, these methods fail to provide satisfactory accuracy. Hence, this article proposes an energy efficient methodology named modified multi-hop clustering (MMHC). This methodology takes three steps. The first step is assembling the nodes where the nodes are assembled, the second step couples the nodes, and the third step detects the redundant nodes and discard them. The main advantage of MMHC is that it can select multiple redundant nodes at one time and discard, and this makes the algorithm more fast and efficient. Moreover, in order to evaluate the algorithm several parameters have been considered, such as energy consumption, number of failed nodes, number of active nodes, and communication overhead.

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