Static task-scheduling algorithms for battery-powered DVS systems

Battery lifetime enhancement is a critical design parameter for mobile computing devices. Maximizing the battery lifetime is a particularly difficult problem due to the nonlinearity of the battery behavior and its dependence on the characteristics of the discharge profile. In this paper, we address the problem of task scheduling with voltage scaling in a battery-powered single and multiprocessor system such that the residual charge or the battery voltage (the parameters for evaluating battery performance) is maximized. We propose an efficient heuristic algorithm using a charge-based cost function derived from the analytical battery model. Our algorithm first creates a task sequence that ensures battery survival, and then distributes the available delay slack so that the cost function is maximized. The effectiveness of the algorithm has been verified using DUALFOIL, a low-level Li-ion battery simulator. The algorithm has been validated on synthetic examples created from applications running on Compaq's handheld computing research platform, ITSY