QoS Accurate Matching Algorithm Based on Service Resource Scheduling on Cloud Platform and Its Application

Using Quality of Service (QoS) as the standard for resource scheduling is a common method for service resource scheduling on cloud platforms. However, there are both mutually supportive and restrictive multiple technical parameters based on software and hardware resource consumption, and the transparent introduction of a large number of third-party service resources leads to incomplete or even missing QoS attribute values, making service performance evaluation inaccurate and often resulting in problems such as inadequate resource allocation or excessive resource allocation. To address these issues, this paper defines software and hardware QoS attributes and their calculation methods, proposes a dynamic model training method based on FM, and an accurate matching algorithm for service resource scheduling. We design and implement test cases that are the same as the actual operating environment and achieve the expected results after testing.