With the wider application of satellite remote sensing technology in numerous fields and the development of network technology, the number of remote sensing satellites required to receive is constantly increasing. At the same time, the development of remote sensing imaging technology has made the structure of remote sensing data more complex, resulting in an increase in the total number of remote sensing data packets. The simultaneous increase in the scale and total amount of remote sensing data has put forward higher requirements for the storage, scheduling, and forwarding capabilities of remote sensing data at the receiving station under multi task concurrency. This article focus on a scheduling technique for tasks with different priority levels. This technology evaluates the usage of data transmission resources by implementing monitoring server status, analyzing the CPU, memory, I0, network bandwidth status, and network load capacity of the device, and achieving dynamic allocation of resources.