Decision Stump Bootstrap Aggregative Firefly Resource Optimized Dual Cluster Head Selection for Data Transmission in WSN

Resumen

A wireless sensor network (WSN) comprises sensor nodes that gather the data by sensing the
events and transmits the data to a sink or base station. Clustering is defined as the process of
grouping the data with similar characteristics to form the clusters. Due to limited capabilities,
the sensor nodes have suffered from energy issues and direct data transmission failure. In
order to solve these limitations, a Decision Stump Bootstrap Aggregative Firefly Resource
Optimized Dual Cluster Head Selection (DSBAFRODCHS) technique is introduced for
efficient data transmission in WSN with a higher packet delivery ratio. Experimental
evaluation is conducted on factors such as clustering accuracy, packet delivery ratio, energy
consumption, and an end-to-end delay with respect to a number of sensor nodes and packets.
The observed simulation results show that the DSBAFRODCHS technique effectively
improves the data packet delivery, clustering accuracy and minimizes the energy
consumption, as well as end to end delay than the state-of-the-art methods