FDBSCAN: Fuzzy based DBSCAN Algorithms for Densely Deployed Wireless Sensor Network for Prolonging Network Lifetime
DOI:
https://doi.org/10.18486/ijcsnt/6.2.080Keywords:
Lifetime, Energy, WSN, LEACH, IC-ACOAbstract
In wireless sensor networks the nodes are spatially distributed and spread over application-specific experimental fields. The primary role of these nodes is to gather the information for various intended fields like sound, temperature, and vibration etc. In this paper, a new energy efficient clustering algorithm for the densely deployed network has been proposed. The efforts have been made to prolong the network lifetime by reducing the energy consumption of nodes by considering the critical issues of dense deployment. Every node will limit its chance of participation in any cluster based on the local sensor density. The proposed algorithm performs better in the case where the sensor nodes are randomly deployed. The network area is divided into high and low-density areas using the DBSCAN algorithm. The nodes in low-density areas are considered critical since there is very less probability for transmission of redundant information by these nodes. The separation of high density and low-density areas using DBSCAN helps in sleep management. Sleep management helps in the energy optimization in dense areas and thus adds in prolonged network lifetime with the improved stable region. It has been observed through the computer simulation that the proposed algorithm is more energy efficient than the LEACH and IC-ACO in densely deployed network areas while maintaining similar performance otherwise.
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