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As the quantity and functional complexity of battery powered portable devices continues to rise, energy efficient design of such devices has become increasingly important. Many real-time scheduling algorithms have been developed recently to reduce energy consumption in hard real-time embedded systems that use dynamic voltage scaling (DVS) capable processors. This paper explores an algorithm that seeks to reduce energy consumption by considering tasks in tandem, with the intuition that what may be a good frequency for one task, may be much worse for another. In particular, our algorithm considers pairs of tasks, and optimizes them simultaneously so that their total energy consumption is minimized while all deadlines are met. Experimental results demonstrate that our method is able to effectively improve on the results of look-ahead EDF, one of the best energy-aware schedulers, especially for task sets with moderate utilization, and "harmonious" task periodicity.