A genetic algorithm for energy efficient device scheduling in real-time systems

Most embedded systems have tight constraints on power consumption because the amount of power available to these systems is limited due to the limitation of battery life. For this reason energy consumption is an important parameter in evaluating performance of embedded systems. DPM (dynamic power management) has gained considerable attention over the last few years as a way to save energy in device that can be turned on and off by operating system control. Scheduling is very important for DPM since it directly affects the efficiency of DPM. We have implemented a customised genetic algorithm which generates a near-optimal device schedule for a set of real-time tasks, with the goal of minimising the power consumed. When compared with other schedulers, the genetic algorithm based system is shown to have less memory and time requirements and scale far better as the problem complexity is increased.