Improving the Performance of Wireless Sensor Networks: Recent Polices and Approaches

摘要

Soft computing paradigm play a major role in improving the performance of WSN where it works on maximizing the system performance by using simple reward feedback for the agent to learn its behavior. It has the largest number of publications on our research area. Reinforcement learning (RL) proves to be the most appropriate and usable soft computing paradigm in WSN routing. Position of sensor nodes in the network and the distance from sink node greatly affect the level of energy consumption in each node. Each node needs an adaptive energy consumption and optimization algorithm to improve performance and preserve the energy of the network.