Data storage is a basic operation of data management in wireless sensor networks. In mobile low-duty-cycle sensor networks

due to the mobility of the nodes

each node needs to frequently update the set of its neighbor nodes

which making energy consumption of the node too large. At the same time

each node is sleeping in most of its time

and wakes up to work in only a small portion of time. This sleeping/working mode results in excessive communication delay for data backup. A fast data storage mechanism with low energy consumption is proposed. First

each source node performs piecewise linear fitting compression on its sensing data based on continuous time series. Then

the node calculates a reasonable number of compressed data backups based on an estimated failure probability and the size of its storage space. On this basis

a dynamic adaptive transmission protocol is designed. Experimental simulations show that this mechanism has lower energy consumption of transmission and lower communication delay compared with existing storage algorithms.