Soft Real-Time Fuzzy Task Scheduling for the Performance Evaluation of Distributed Systems

All practical real-time scheduling algorithms in distributed systems present a trade-off between performance and computational complexity. In real-time distributed systems, tasks have to be performed correctly and timely. The research till date on task scheduling has primarily focused upon computation time, laxity, priority etc. Further all existing task scheduling algorithms are based upon Boolean Arithmetic. Introduction of Fuzzy theory in scheduling algorithms can really make the study very interesting. Finding an optimal schedule in distributed systems, with real-time constraints is shown to be NP-hard. Deterministic and reliable behavior is an important characteristic for system's robustness analysis. The intrinsic uncertainty in dynamic real-time systems increases the difficulties of scheduling algorithms. To alleviate these deficiencies, we have proposed a fuzzy scheduling approach to arrange real-time periodic and non-periodic tasks, their inter-processor communication time, execution time and deadline with reference to optimal utilization of distributed processors. The present piece of research has been simulated on MATLAB 7.0.4 Mamdani Fuzzy Inference Engine to evaluate the performance of the proposed methodology. Experimental results have shown that the proposed fuzzy scheduler creates feasible schedules for homogeneous and heterogeneous tasks.