Applications of learning automata in wireless sensor networks

We are dealing with a host of challenging issues in wireless sensor networks like: limited energy supply of a sensor which is a threat for network life time, QOS needs and energy efficient routing. Researchers have proposed a variety of approaches to deal with these issues, but when it comes to dynamic, unpredictable environments, some of these solutions lose their effectiveness. The question is whether there is an adaptive approach which could adapt itself with the changing nature of the environment? “Learning Automaton” is the answer to this question. If we equip the sensors with some intelligent automata, our network earns the ability of adapting itself with the environment when it changes. In other words, the WSN uses the power of learning and becomes intelligent as time passes. In this paper we introduce several proposed algorithms which use the learning automata to deal with the issues mentioned above, intelligently.