Microservice combination optimisation based on improved gray wolf algorithm

Microservices architecture is a new paradigm for application development. The problem of optimising the performance of microservice architectures from a non-functional perspective is a typical Nondeterministic Polynomial (NP) problem. Therefore, aiming to quantify the non-functional requirements of computing microservice systems, while solving the problem of latency in computing the best combination of services with the maximum QoS objective function value, this paper proposes a microservice combination approach based on the QoS model and a CGWO algorithm for optimisation computation for this model. The experimental results verify that the error rate of the method is only 0.528% on the non-functional combination optimisation problem, and the computational efficiency of the algorithm increases by 97.29% when the complexity of the problem search space increases, while CGWO improves 65.97% and 81.25% respectively in the accuracy of optimisation compared to the prototype of the algorithm (GWO), and has a stable optimisation performance, aspect. It proves that the research in this paper has a high advantage in automatically searching for the best QoS for the microservice combination problem.

Automated summary

This paper proposes a microservice combination approach based on the QoS model and a CGWO algorithm for the optimization computation. Experimental results show that the error rate of the method is only 0.528% on the non-functional combination optimization problem, and the computational efficiency of the algorithm increases by 97.29%. CGWO improves the accuracy of optimization by 65.97% and 81.25% respectively compared to the prototype algorithm (GWO), and has a stable optimization performance.