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“Multi-Criteria Group Decision Making Approach for Scheduling Algorithms Selection by Short Term Scheduler using Fuzzy TOPSIS”.
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The fundamental objective of the CPU scheduler is to equitably and effectively allocate CPU time among competing processes. Within the realm of schedulers, the short-term scheduler specifically addresses this objective by selecting processes from the ready queue for execution on the CPU, guided by various scheduling algorithms. The critical challenge faced by the short-term scheduler lies in the prudent selection of the most suitable algorithm, as an erroneous choice can detrimentally impact system performance, leading to increased waiting and response times for processes. To surmount this challenge, we employ the Fuzzy TOPSIS method within the framework of Multi-Criteria Decision Making (MCDM) to rank scheduling algorithms, taking into account both quantitative and qualitative factors. The proposed approach involves two steps: firstly, defining criteria for algorithm selection, and secondly, obtaining linguistic ratings from experts for potential alternatives based on the specified criteria. The principal aim of this investigation is to utilize the Fuzzy TOPSIS method, integrating fuzzy sets, to produce comprehensive scores that assist in selecting the optimal alternative.
Science Research Society
Title: “Multi-Criteria Group Decision Making Approach for Scheduling Algorithms Selection by Short Term Scheduler using Fuzzy TOPSIS”.
Description:
The fundamental objective of the CPU scheduler is to equitably and effectively allocate CPU time among competing processes.
Within the realm of schedulers, the short-term scheduler specifically addresses this objective by selecting processes from the ready queue for execution on the CPU, guided by various scheduling algorithms.
The critical challenge faced by the short-term scheduler lies in the prudent selection of the most suitable algorithm, as an erroneous choice can detrimentally impact system performance, leading to increased waiting and response times for processes.
To surmount this challenge, we employ the Fuzzy TOPSIS method within the framework of Multi-Criteria Decision Making (MCDM) to rank scheduling algorithms, taking into account both quantitative and qualitative factors.
The proposed approach involves two steps: firstly, defining criteria for algorithm selection, and secondly, obtaining linguistic ratings from experts for potential alternatives based on the specified criteria.
The principal aim of this investigation is to utilize the Fuzzy TOPSIS method, integrating fuzzy sets, to produce comprehensive scores that assist in selecting the optimal alternative.
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