GECSA: A game theory based energy efficient cluster-head selection approach in Wireless Sensor Networks

In Wireless Sensor Networks (WSNs), sensor nodes suffer from limited battery power. It is a difficult task to work with sensor nodes in an energy efficient way because sensor nodes are placed in various geographical locations and once battery is over it is difficult to change. To work with this challenge, in this work we present a Game Theory Based Energy Efficient Cluster-Head Selection Approach (GECSA) based on the Subgame Perfect Nash Equilibrium (SPNE) of game theory. Then based on SPNE decision, the Cluster-Heads(CHs) are selected. For each round and for each cluster nodes play game with each other and a node which is SPNE is selected as a CH. The simulation results show increase in performance of our proposed approach as compared to the existing protocols such as UCR, DEEC, and BEEG. The simulation results are validated through MATLAB.