Performance analysis of machine learning techniques for energy efficient routing and target tracking in WSN

Abstract

Wireless Sensor Network WSN comprises diverse sensor nodes to present an optimal data delivery between the source and destination nodes In WSN data gathering is the procedure of collecting more number of data from distributed sensor nodes and sends these data to sink node for effective communication Energy preservation during data packet transmission helps in enhancing the network lifetime Recently several research works are designed for increasing the efficiency of routing in WSN However energy efficiency is considered a major concern in the target object tracking owing to the insufficient battery capacity of sensor nodes During target tracking several problems are said to occur including data aggregation routing scheduling and energy conservation This in turns leads to minimize the network lifetime Therefore proposed works focus on developing the performance of the energy efficient routing and target tracking for data packet broadcasting from source to the destination node in WSN newline