Research on Cloud Test Resource Allocation Based on Improved Fuzzy Clustering PSO Algorithm

There are few related researches on cloud hardware test resource allocation, and the existing common methods have low reliability and slow solution speed. The matching calculation based on fuzzy clustering and the resource allocation method based on improved PSO are proposed. Firstly, seven typical parameters of cloud test resources are proposed, and the dynamic resource matching effectiveness evaluation model is established. Secondly, the Delphi method is used to evaluate the parameters fuzzyly. The resource matching degree is calculated based on fuzzy rules and cosine similarity. Then the cloud test resource necessity and priority matching are proposed. Strategy, using the improved PSO algorithm to achieve approximate optimal resource allocation; Finally, the algorithm is used to verify and analyze the algorithm, and applied to a cloud test platform. The results show that the method not only solves faster, but also improves the quality of resource matching.