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In this paper, the influence of correlated data from different sensors on the location of the sensors and the consumed energy of wireless sensor network are introduced, and the performance of a joint entropy encoding strategy which compresses the correlated data along routing is analyzed. During transmission, relay sensors jointly encode their own sampled data and the data received from upward sensors. The consumed energy of the network is minimized through optimally choosing the location of sensors. For the sake of prolonging network lifetime, a scheme to balance the consumed energy between different sensors is proposed, which combines the correlation between data and the amounts of data transmitted by different sensors, to make the transmitted energy consumed by different sensors tend to be uniform by adjusting the distance between sensors. The applications of the schemes in one-dimensional wireless sensor network are presented and the numerical results show that these schemes have excellent performance.