PwCOV in cluster-based web server: an assessment of service-oriented computing for COVID-19 disease processing system

In this work, we are introducing a novel assessment methodology for evaluating a prototype web service–based system for COVID-19 disease processing system by using cluster-based web server. We call it as PwCOV. The service generates clinical instructions and process respective information for distributed disease data sets. It follows the business processes and principles of service-oriented computing for each end user request. The assessment methodology illustrates different aspects of service deployment for massive growth of service users. In this study, the PwCOV is observed to be stable up to the stress level of 1700 simultaneous users. The response time of 14.35 s, throughput of 8592 bytes/s, and central processing unit (CPU) utilization of 22.16% with a strong reliability of service execution is observed. However, the reliability of PwCOV execution degrades beyond that execution limit. For 1800 simultaneous users of the service, the response time, throughput and CPU utilization is recorded to be 25.28 s, 15,729 bytes/s, and 39.13%, respectively. During this stress, the service failure rate of 35% is observed. A moderate reliability of 70% of service period is observed for 1800 users. The propose study also discusses the impact of system metric, reliability, and their correlation over the service execution. The statistical analysis is carried out to study the viability, acceptability, applicability of such deployment for COVID-19 disease processing system. The limitation of PwCOV for processing geographically scattered data sets is also discussed.