Abstract: In the process of designing and deploying wireless sensor networks (WSNs), due to the changeable deployment environment and limited energy, the load of each node is unbalanced when transmitting data. Therefore, how to make full use of the limited energy to prolong the lifetime of the network, improve the data transmission efficiency and real-time performance of the algorithm has become an urgent problem to be solved. An improved adaptive-genetic-algorithm based clustering protocol (IAGA-C) for WSNs is proposed in this paper. The cluster heads are selected by integrating the factors of the distance between each node and cluster heads, the distance between cluster heads and base station (BS), and the remaining energy of each node. Additionally, in order to improve the real-time performance of clustering algorithm, this paper improves the crossover and mutation mechanism of classical genetic algorithm, and reduces the time consumed in clustering process while ensuring the effectiveness of the algorithm. Simulation results show that, compared with another clustering routing protocols, the proposed method has good performance on improving network life, data transmission efficiency and real-time capability.