Energy Efficient Scheduling in Multiprocessor Systems Using Archived Multi-objective Simulated Annealing

In this paper, we have proposed an archived simulated annealing based novel approach for solving multi-objective energy-efficient scheduling on heterogeneous DVS activated processors in high-performance real-time systems. Real-time task scheduling problem is a well-known NP-hard problem. In these systems, tasks are usually associated with deadlines and represented by directed acyclic graphs since they depend on each other. So, system designers face difficulty in finding suitable solutions that can satisfy all the objectives of task scheduling, as warranted for proficient operations of such systems. Hence, this paper introduces a novel algorithm, called archived multi-objective simulated annealing for energy-efficient real-time scheduling (AMOSA-E2RTS) that finds an optimal schedule satisfying the precedence and deadline constraints. In the proposed algorithm, a domination concept leads towards finding the optimal trade-off solutions and tasks are prioritized according to three different policies i.e., latest deadline first (LDF), execution ranking and energy ranking policy. A suitable numerical example is used to demonstrate the working of the proposed approach. Experimental findings suggest that the proposed algorithm is capable of producing energy efficient scheduling decisions which satisfy all related constraints. Statistical analysis of the results has been conducted.