title: Applying dynamic priority scheduling scheme to static systems of pinwheel task model in power-aware scheduling.
abstract: Power-aware scheduling reduces CPU energy consumption in hard real-time systems through dynamic voltage scaling (DVS). In this paper, we deal with pinwheel task model which is known as static and predictable task model and could be applied to various embedded or ubiquitous systems. In pinwheel task model, each task's priority is static and its execution sequence could be predetermined. There have been many static approaches to power-aware scheduling in pinwheel task model. But, in this paper, we will show that the dynamic priority scheduling results in power-aware scheduling could be applied to pinwheel task model. This method is more effective than adopting the previous static priority scheduling methods in saving energy consumption and, for the system being still static, it is more tractable and applicable to small sized embedded or ubiquitous computing. Also, we introduce a novel power-aware scheduling algorithm which exploits all slacks under preemptive earliest-deadline first scheduling which is optimal in uniprocessor system. The dynamic priority method presented in this paper could be applied directly to static systems of pinwheel task model. The simulation results show that the proposed algorithm with the algorithmic complexity of O(n) reduces the energy consumption by 10-80% over the existing algorithms.
authors.affiliation: Green Energy Institute, Sangmyung University, Seoul 110-743, Republic of Korea.
authors.forename: Ye-In
authors.identifier: 0000-0001-6316-1926
authors.initials: YI
authors.lastname: Seol
authors.affiliation: Deptartment of Computer Science & Engineering, Chungnam Nat'l University, Daejeon 305-764, Republic of Korea.
authors.forename: Young-Kuk
authors.identifier: 0000-0002-8329-9348
authors.initials: YK
authors.lastname: Kim
mesh_terms: D000465:Algorithms; D001071:Appointments and Schedules; D003198:Computer Simulation; D006801:Humans; D008962:Models, Theoretical; D012984:Software; D013647:Task Performance and Analysis