Battery lifetime enhancement is a critical design parameter for mobile computing devices. Maximizing battery life-time is a particularly difficult problem due to the non-linearity of the battery behavior and its dependence on the characteristics of the discharge profile. In this paper we address the problem of dynamic task scheduling with voltage scaling in a battery-powered DVS system. The objective is to maximize the battery performance measured in terms of charge consumption during execution of the tasks. We present a new battery-aware dynamic task scheduling algorithm,  darEDF , based on an efficient slack utilization scheme that employs dynamic speed setting of tasks in run queue. We compare  darEDF  with three state of the art energy-efficient algorithms,  lpfpsEDF, lppsEDF, lpSEH , with respect to battery performance and energy consumption. We show that  darEDF  has better performance than  lpSEH  (which has close to optimal energy value), and has lower run-time complexity.
['Jianli Zhuo', 'Chaitali Chakrabarti']
An efficient dynamic task scheduling algorithm for battery powered DVS systems