Power-aware scheduling of mixed task sets in priority-driven systems

We propose power-aware on-line task scheduling algorithms for mixed task sets which consist of both periodic and aperiodic tasks. The proposed algorithms utilize the execution behaviors of scheduling servers for aperiodic tasks. Since there is a trade-off between the energy consumption and the response time of aperiodic tasks, the proposed algorithms focus on bounding the response time degradation of aperiodic tasks while they use a more aggressive slack estimation technique for higher energy savings in mixed task sets. We also propose a new slack distribution method which gives better response times with slight energy increases. Experimental results show that the proposed algorithms reduce the energy consumption by 25% and 18% over the non-DVS scheme under the RM scheduling and the EDF scheduling, respectively.