Real-Time Power Aware Scheduling for Tasks with Type-2 Fuzzy Timing Constraints

The timing constraint of tasks in the mobile real-time computing systems plays the central role in deciding the task schedule as timely completion of the task is very important in such systems. These timing constraints are however completely unquantifiable during the time of system modeling and designing. Thus we consider type-2 fuzzy sets for modeling the timing constraints in mobile and time-critical computing systems and propose a new algorithm FT2EDF (Fuzzy Type-2 Earliest Deadline First) for task scheduling. On the other hand, because of the limitation of the storage power, power efficiency is another foremost design objective for designing mobile real-time computing systems. However, reduction of processor power pulls down the system performance. Timely task completion and power efficiency are therefore two mutually conflicting criteria. In this paper, we propose a heuristic based solution approach that with a modified version of the non-dominated sorting genetic algorithm-II (NSGA-II). Our approach allows that a processor dynamically switches between different voltage levels to ensure optimum reduction in the power requirements without compromising the timeliness of the task completion. The efficacy of our approach is demonstrated with two numerical examples. Comparison with the previous results show that our solution ensures approximately 44% of energy saving as compared to the around 25% of the earlier results.