Abstract

Relational Database Management System (RDBMS) is commonly applied in Small, Medium, and Enterprise businesses. In this research, we investigated Quality of Service (QoS) perimeters over day-to-day operations in RDBMS and how the running process able to be expedited with the adaptation and combination of autonomic computing approach using MAPE-K (Monitor, Analyse, Plan, Execute, and Knowledge Base) and Fuzzy rules. The core function of the system is to monitor student attendance, assessment, and lastly escalation of identified student issues to the department of academic. In a nutshell, it is called the Student Involvement Report (Sir). Two segments have been analysed and focused on errors in request time out, bandwidth, hits, and user activities. The outcomes of this are significant on activities that related to the peak of academic activity, due to the submission of student reports and escalation among departments. The MAPE-K and Fuzzy rules can capture the scenarios and identify rules that are significantly important to reduce and enhance the Request Time Out and Hits activities.

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