Distributed Energy Equilibrium Routing Algorithm Based on Hierarchical Thought and Markov Game in WSN

Abstract

An excellent and efficient energy-balanced routing algorithm plays an important role in the research of WSN (wireless sensor networks). Aiming at the energy hole phenomenon and funneling effect of WSN, based on hierarchical thought and Markov game, a distributed energy equalization routing algorithm is proposed. Based on the traditional cluster structure and hierarchical routing model, this algorithm designs a balanced structure and hierarchical routing model. The core idea is to control the loop distance of each layer to adjust the relationship between the amount of transmitted data, the transmit power and the number of nodes. The average energy consumption of the nodes in each layer is equal, so that the electrical energy loss between the layers reaches an equilibrium, thereby weakening the hot-spot effect and increasing the life of the network. At the same time, in the inner of same level, in order to balance energy consumption, the Markov game model is introduced, and the gain of the node is set to be related to the residual energy of the node, and the possibility of state transition of the sensing node is calculated. The sensing node selects the strategy according to the revenue and state transition matrix, thereby achieving the energy balance consumption of the nodes within the same level. The experimental simulation proves that this method works very well in the place where the local node sharing area is large. Through theoretical calculation and analysis, it is known that when the initial radius is reasonably adjusted, the network life cycle can be extended and the average energy consumption can be reduced.