Constructing energy efficient data aggregation trees based on information entropy in wireless sensor networks

Hierarchical structure possesses many advantages in the organization of wireless sensor networks (WSNs). Moreover, the life of a hierarchical WSN can be prolonged since many sensor nodes can be put into the sleep state most of the time. Therefore, in real applications, hierarchical network structure has become the focus of research due to limited energy resources in wireless sensor nodes. Aimed at solving the problem of imbalance on energy consumption of wireless sensor nodes in WSNs, in this paper, we propose a method for the construction of data aggregation trees based on information entropy in which the minimum spanning tree and the theory of information entropy are applied to the design of the protocol to reduce the amount of communication during data transmission. Simulation results show that our proposed method outperforms some comparable approaches in the area of energy efficiency.