This paper presents a framework for the purpose of energy optimization of the embedded systems. Our framework is synthetic, that is, multiple techniques optimize the target application simultaneously. The main technique of our approach is to utilize the trade-off between energy and performance of the embedded processor configuration. Additionally, the optimization technique about the memory allocation is employed in our framework. Our framework is also gradual, that is, the target application is optimized in a step-by-step manner. The characteristic and behavior of target application are optimized in both intra-task and inter-task level at the static time. Based on the results of the static optimization, the energy-optimal processor configuration is dynamically changed according to the behavior of the application. Moreover, we implemented the presented framework as a toolchain and a real-time operating system. The energy minimization in the average case can be achieved with keeping the real-time performance.This paper presents a framework for the purpose of energy optimization of the embedded systems. Our framework is synthetic, that is, multiple techniques optimize the target application simultaneously. The main technique of our approach is to utilize the trade-off between energy and performance of the embedded processor configuration. Additionally, the optimization technique about the memory allocation is employed in our framework. Our framework is also gradual, that is, the target application is optimized in a step-by-step manner. The characteristic and behavior of target application are optimized in both intra-task and inter-task level at the static time. Based on the results of the static optimization, the energy-optimal processor configuration is dynamically changed according to the behavior of the application. Moreover, we implemented the presented framework as a toolchain and a real-time operating system. The energy minimization in the average case can be achieved with keeping the real-time performance.