Pruning-based, energy-optimal, deterministic I/O device scheduling for hard real-time systems

Abstract

Software-controlled (or dynamic) power management (DPM) in embedded systems has emerged as an attractive alternative to inflexible hardware solutions. However, DPM via I/O device scheduling for hard real-time systems has received relatively little attention. In this paper, we present an offline I/O device scheduling algorithm called energy-optimal device scheduler (EDS). For a given set of jobs, it determines the start time of each job such that the energy consumption of the I/O devices is minimized. EDS also ensures that no real-time constraint is violated. The device schedules are provably energy optimal under hard real-time job deadlines. Temporal and energy-based pruning are used to reduce the search space significantly. Since the I/O device scheduling problem is NP-complete, we also describe a heuristic called maximum device overlap (MDO) to generate near-optimal solutions in polynomial time. We present experimental results to show that EDS and MDO reduce the energy consumption of I/O devices significantly for hard real-time systems.