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New embedded systems offer rich power management features in the form of multiple operational and nonoperational power modes. While they offer mechanisms for better energy efficiency, they also complicate power management decisions in the presence of realtime constraints. A traditional dynamic power management techniques based on localized break-even-time analysis with simple on/off power controls often yield suboptimal if not incorrect results globally. To address these problems, This work presents two core algorithms for reducing idle energy consumption at the component level and system level. The first algorithm discovers the optimal sequence for mode transition over multiple power modes under timing constraints. It assists the second algorithm that performs a sophisticated global search strategy to aggressively explore system-wide energy savings by correctly interpreting the constraints across all subsystems. Experimental results show that in an embedded radio system where idle energy cost matches or exceeds the active energy consumption, our technique can further reduce the idle energy by 50-70%, which translates into 30-50% of overall system energy compared to existing techniques.