Abstract: The problem of wireless sensor network data clustering analysis is researched.In order to solve the shortcomings that traditional k-means is secsitive for the initial clustering center and easily fall into local optimal solution,a distributed immune genetic algorithm k-means based on sensor network is proposed.In the algorithm,cluster center has been as chromosomes,and through the genetic algorithm to optimize the initial cluster centers of traditional k-means clustering algorithm,meanwhile the selecting operation of immune algorithm is introduced into the genetic evolution of chromosome,causing the concentration and fitness of chromosome will impact whether the chromosome is selected in evolutionary,which can realize chromosome population diversity maintaining mechanism and self regulating function,and the searching achieves the global optimum,so the algorithm can solve the prematurity problem of k-means algorithm better.The experimental results show that,the algorithm has been improved data clustering effect,and made the clustering can converge to the global optimal clustering rapidly,and the clustering has higher accuracy.