Abstract: With the increasing demand for remote sensing common products in various industries,the application of high-perfor-mance remote sensing product production system is increasing.As a key component of the system,excellent task scheduling algorithm can significantly improve its production efficiency.However,there are unique challenges in the production process of remote sensing generic products.If a large number of workflows are submitted for production in a short time,there are problems of dou-ble calculation and data processing in the processing of these workflows,and the amount of data required to generate generic pro-ducts is often large,and the process processing time is long,which easily leads to resource waste and production efficiency decline.In order to solve this problem,this paper proposes a task division strategy based on product reuse model,which focuses on optimizing workflow processing.Firstly,workflow submitted by users is packaged into a process package according to task repetition,and processes with repetitive tasks are assigned to the same computing node to reduce the data transmission time between nodes.Then,a product reuse model is introduced to allow different processing processes to reuse the obtained product results,reduce repetitive calculation and data processing,so as to improve production efficiency and meet the high efficiency needs of common product production.In order to verify the effectiveness of the proposed algorithm,the proposed algorithm and other traditional algorithms FCFS and SJF are simulated in the CloudSim simulation simulator respectively.The results show that the proposed scheduling algorithm has significantly lower total task completion time and average task response time than the other two algorithms,showing better performance.

Key words: High performance computing, Generic Remote sensing products, Product reuse, Task divison strategy, CloudSim