Skip to Main Content
In this paper, we present a power-aware, best-effort real-time task scheduling algorithm called PA-BTA that optimizes real-time performance and power consumption. The algorithm considers a timeliness model where task timing constraints are described using Jensen's (1992) benefit functions and a system-level power model. We propose a metric called "energy and real-time performance grade" (ERG) to measure real-time performance and power consumption in a unified way. Since the scheduling problem is NP-hard, PA-BTA heuristically computes schedules to maximize ERG, incurring a worst-case computational cost of O(n2). Our simulation results indicate that the algorithm performs close to the optimal algorithm and better than other algorithms considered in the study.