Power-aware scheduling algorithms for sporadic tasks in real-time systems

In this paper, we consider the canonical sporadic task model with the system-wide energy management problem. Our solution uses a generalized power model, in which the static power and the dynamic power are considered. We present a static solution to schedule the sporadic task set, assuming worst-case execution time for each sporadic tasks release, and propose a dynamic solution to reclaim the slacks left by the earlier completion of tasks than their worst-case estimations. The experimental results show that the proposed static algorithm can reduce the energy consumption by 20.63%-89.70% over the EDF* algorithm and the dynamic algorithm consumes 2.06%-24.89% less energy than that of the existing DVS algorithm. (C) 2013 Elsevier Inc. All rights reserved.