An Improved SVM based Machine Learning Model for Efficient Energy Optimization in Wireless Sensor Networks

Abstract

 There have been rising concerns well into the Wireless Sensor Networks during recent decades. Sensor nodes are power restricted within Wireless Sensor Networks. Furthermore, some of the significant development hurdles in WSNs seems to be to reduce the energy expended at either the sensor nodes. Machine learning encourages several pragmatic solutions that optimize resource usage as well as enhance network broadcaster's lifespan. Due to the extreme sensor's restricted resources as well as bandwidth limitations, sending almost all of the data directly to an access point further analysis including forming inferences becomes practically impractical.