Optimizing to Memory Application in Embedded Multimedia Device

The modern embedded multimedia electronic devices rely on dynamically-allocated data structures to store and process their data, as a result, the demand of its memory capacity and dynamic are increasing unceasingly. In order to better solve the memory application optimization in embedded device, this paper represents multimedia application’s dynamic data structures optimization flow and improved or modified NSGA-II multi-objective evolutionary algorithm (MNSGA-II), and uses three objective functions: embedded device’s memory accesses, memory use and energy consumption. The MNSGA-II algorithm adopts repeat crowded distance sorting tactics to improve NSGA-II based on keeping the advantage of the original NSGA-II for multi-objective optimization problem. The experiment results show that MNSGA-II has better performance of the convergence and the diversity of solutions than original NSGA-II, and the optimal dynamic data structure implementation is successful by performing our method for one real embedded multimedia device’s memory application.