The characteristics of data aggregation with different network environments and dynamic changes in channel availability make some problems in IoT data aggregation. Therefore, this paper proposes an FMA-coverage model for algorithm design based on edge information. The FMA-coverage model includes the method of edge frequency, the method of primitive length (stroke), the texture energy metric of Laws and the method of fractal texture description. The FMA-coverage model can improve the network performance of IoT data aggregation. From the computational analysis, it can be seen that the security of data storage is only 17%. After the improvement of the fast matching algorithm, the security is up to 87%. After the network coding scheme, the IoT performance of data aggregation is up to 95%. It is important to note that, in this case, the required transmission volume in the network can be greatly reduced when the links are long. The IoT performance is up to 97% with the compression-aware scheme. By cross-sectional comparison, the IoT-based mobile model has the highest accuracy, with 98% accuracy of data aggregation. This paper extends the data aggregation mechanism by introducing fast-matching algorithms for device authentication and secure storage.