Simulated dataset collection method of dynamic quality of services (QoS) metrics

The dynamic behavior of web services is critical for researchers to determine their performance at different times. Many existing studies present the static information of web services that are not so effective for estimating web services' future performance. This research article reveals the acquisition of throughput metric dataset for thirty timestamps by a simulation technique. A simulated setup has been proposed to acquire the dynamic throughput data of benchmark web services from workload modeling. The proposed method is aimed to collect dynamic web services metrics data of five web services (WS1–WS5), which are randomly selected from WS-Dream dataset. Additionally, the collected data has been verified by measuring computer resource usage metrics in four experiments. Experiment results indicate that the varying ‘Central Processing Unit’ (CPU) resource usage metrics do not show changes in the collected ‘Quality of Service’ QoS metric values. The experiment results showed that the proposed method achieves the consistent average response time and throughput metric values. The collected simulated data can be further applied to improve the quality of web services.