Abstract:In a multi-user edge computing environment, there is a resource scheduling issue between devices and containers. The main objective of this paper is to study and optimize edge terminal resource scheduling to improve system performance and resource utilization efficiency. In order to achieve this goal, edge terminal resource scheduling is modeled and an optimization scheme based on the Gale-Shapley (GS) algorithm is proposed. Firstly, the matching relationship between devices and containers is analyzed by establishing a resource scheduling model in the edge computing environment. Then, GS algorithm is used to allocate resources, and the optimal allocation of resources is realized through bidirectional matching between devices and tasks. In order to verify the effectiveness of the proposed scheme, simulation experiments are conducted to simulate and test the system performance under the condition of different numbers of tasks and devices. Experimental results show that the GS algorithm can effectively reduce system overhead when the number of tasks increases and the number of devices exceeds the number of containers, demonstrating significant advantages compared with traditional resource allocation algorithm. In addition, This paper also proposes strategies to address computational complexity issues, such as parallel computing and intelligent task allocation, to improve the scalability and adaptability of the algorithm.