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Since the lifetime of a battery directly impacts the lifetime of sensor networks, one of the key considerations in the design of sensor networks is the ability to maximize battery lifetime. In this paper, we present (1) a task modeling methodology and (2) a battery-aware real-time task scheduling technique for sensor networks. The task modeling is achieved based on task classification in terms of the usage of resources on a micro-sensor system. For exploiting the recovery effect of battery, the battery-aware task scheduling algorithm composed of three phases is designed to maximize the lifetime of a battery while meeting the timing constraint of each task.