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Main contributions of this research are:
1. Identification of the key Workload Parameters
2. Identification of the workload type
3. Fuzzy based scheduler to calculate the exact OLTP and DSS percentage of each workload.
4. CBR based Idleness Detection
Results achieved after experimenting over the OLTP and DSS like workload reveals that the proposed workload management is effective and less time consuming as compared to other techniques. In future, this type of research can be performed on other DBMSs, more human intervention can be lessened that ultimately improve the autonomic level of DBMSs. The proposed research is also providing the basis for improving the workload management in Data Warehouses.
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IEEE/ICACT20240293 Slide.19
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