Solving Coverage Problem by Self-organizing Wireless Sensor Networks: ( \(\epsilon \) ,h)-Learning Automata Collective Behavior Approach

We propose a novel multi-agent system approach to solve a coverage problem in Wireless Sensor Networks (WSN) based on the collective behavior of ( \(\epsilon \) ,h)-Learning Automata (LAs). The coverage problem can be stated as a request to find a minimal number of sensors spending energy of their batteries to provide the requested level of coverage of the whole monitored area. We propose a distributed self-organizing algorithm based on the participation of LAs in an iterated Spatial Prisoner’s Dilemma game. We show that agents achieve a solution corresponding to Nash equilibrium, which provides maximization of not known for agents a global criterion related to the requested level of the coverage with a minimal number of sensors which turn on their batteries.