Power aware scheduling for AND/OR graphs in multi-processor real-time systems

Power aware computing has become popular recently and many techniques have been proposed to manage the energy consumption for traditional real-time applications. We have previously proposed two greedy slack sharing scheduling algorithms for such applications on multi-processor systems. In this paper, we are concerned mainly with real-time applications that have different execution paths consisting of different number of tasks. The AND/OR graph model is used to represent the application's data dependence and control flow. The contribution of this paper is twofold. First, we extend our greedy slack sharing algorithm for traditional applications to deal with applications represented by AND/OR graphs. Then, using the statistical information about the applications, we propose a few variations of speculative scheduling algorithms that intend to save energy by reducing the number of speed changes (and thus the overhead) while ensuring that the applications meet the timing constraints. The performance of the algorithms is analyzed with respect to energy savings. The results surprisingly show that the greedy scheme is better than some speculative schemes and that the greedy scheme is good enough when a reasonable minimal speed exists in the system.