Microservices Partitioning Based on Computing Power and Its Computing Resource Allocation

Yiping Yan, Qiwei Shen

Abstract: This study addresses the issue of service partitioning and allocation of computing resources in microservices architecture, aiming to propose a method for microservices partitioning based on computing power and a method for allocating computing resources based on Game theory. Through a summary and comparative analysis of existing methods for microservices partitioning, this study finds that current methods have limitations, especially in the lack of research and practice based on computing power as an index for microservices partitioning. For services with high computing power, current microservices partitioning schemes cannot effectively solve the problems of poor throughput and low real-time performance of high-computing microservices. Therefore, this study proposes a new method for microservices partitioning from the perspective of computing power, which aims to reduce computing power and enhance system performance. This method is simple, easy to use, and highly operational. Meanwhile, this study proposes a method for allocating computing resources based on Nash equilibrium theory in the context of microservices architecture to achieve balance and efficiency among various services in the microservices architecture. This provides new ideas and methods for computing resource management in the microservices itecture.