中圖分類號：TP302 文獻標志碼：A DOI: 10.16157/j.issn.0258-7998.245404
中文引用格式： 高先周,，郭敬東,，何陽，等. 高并發(fā)的數(shù)據安全能力微服務架構及調度算法[J]. 電子技術應用,，2024,，50(9)：18-24.
英文引用格式： Gao Xianzhou，Guo Jingdong,，He Yang,，et al. Microservice architecture and scheduling algorithm of high concurrency data security capability[J]. Application of Electronic Technique，2024,，50(9)：18-24.

Microservice architecture and scheduling algorithm of high concurrency data security capability

Abstract： Currently, the business operations of power systems primarily rely on microservices, resulting in significant changes in business architecture. Data security capabilities need to be deeply integrated with business operations. However, existing data security measures are still based on traditional software and hardware architectures, making them inadequate for the dynamic and elastic protection required in cross-domain scenarios, and unable to adapt to the evolving business architecture. There is an urgent need to develop data sharing and interaction security protection technologies based on microservices architecture. Given the massive amount of data generated by power systems and the varying security requirements of different data types, ordinary microservices architectures struggle to address load imbalances under high concurrency scenarios in power systems. To tackle these issues, this paper proposes a microservice scheduling algorithm for data security capabilities based on the Kepler Optimization Algorithm (KOA), aiming to achieve load balancing and enhance the system's high concurrency handling capacity. By thoroughly modeling the resources of cloud cluster nodes and the performance of microservices, an optimization model is constructed with the goal of balancing cluster load and minimizing microservice runtime. Experimental results show that the KOA-based data security capability microservice scheduling algorithm significantly improves server load balancing, enhances cluster system processing efficiency, and reduces task response time, effectively boosting the system's concurrency performance.

Key words : microservices,；load balancing；high concurrency,；Kepler Optimization Algorithm