Designing of vague logic based multilevel feedback queue scheduler

AbstractMultilevel feedback queue scheduler suffers from major issues of scheduling such as starvation for long tasks, fixed number of queues, and static length of time quantum in each queue. These factors directly affect the performance of the scheduler. At many times impreciseness exists in attributes of tasks which make the performance even worse. In this paper, our intent is to improve the performance by providing a solution to these issues. We design a multilevel feedback queue scheduler using a vague set which we call as VMLFQ scheduler. VMLFQ scheduler intelligently handles the impreciseness and defines the optimum number of queues as well as the optimal size of time quantum for each queue. It also resolves the problem of starvation. This paper simulates and analyzes the performance of VMLFQ scheduler with the other multilevel feedback queue techniques using MatLab

Designing of 2-Stage CPU Scheduler Using Vague Logic

In operating system the CPU scheduler is designed in such a way that all the resources are fully utilized. With static priority scheduling the scheduler ensures that CPU time will be assigned according to the highest priority but ignores other factors; hence it affects the performance. To improve the performance, we propose a new 2-stage vague logic based scheduler. In first stage, scheduler handles the uncertainty of tasks using the proposed vague inference system (VIS). In second stage, scheduler uses a vague oriented priority scheduling (VOPS) algorithm for selection of next process. The goal of this work is to handle the uncertainty as well as to optimize both the average and the amount of variation with respect to performance matrices average waiting time, average turnaround time, and average normalized turnaround time. A simulation using MATLAB is also conducted to evaluate the performance. Simulation results show that the proposed scheduler using VOPS algorithm is better than the scheduler with traditional priority scheduling algorithm. Results are based on the dual concept of fuzzy theory and its generalization, vague theory. Additionally, this work comprises the evaluation of VOPS and shortest job first algorithm. The outcome of proposed VOPS algorithm is much closer to the result obtained by traditional shortest job first