For real-time embedded systems, such as control systems used in medical, automotive and avionics industry, tasks deployed on such systems... Show moreFor real-time embedded systems, such as control systems used in medical, automotive and avionics industry, tasks deployed on such systems often have stringent real-time, reliability and energy consumption constraints. How to schedule real-time tasks under various QoS constraints is a challenging issue that has drawn attention from the research community for decades. In this thesis, we study task execution strategies that not only minimize system energy consumption but also guarantee task deadlines and reliability satisfaction. We first consider the scenario when all tasks are of the same criticality. For this case, two task execution strategies, i.e. checkpointing based and task re-execution based strategies are developed. Second, considering the scenario when tasks are of different criticalities, a heuristic search based energy minimization strategy is also proposed. When tasks are of different criticalities, a commonly used approach to guaranteeing high-criticality task deadlines is to remove low-criticality tasks whenever the system is overloaded. With such an approach, the QoS provided to low-criticality tasks is rather poor, it can cause low-criticality tasks to have high deadline miss rate and less accumulated execution time. To overcome this shortcoming, we develop a time reservation based scheduling algorithm and a two-step optimization algorithm to meet high-criticality task deadlines, while minimizing low-criticality task deadline miss rate and maximizing their accumulated execution time, respectively. As many-core techniques mature, many real-time embedded systems are built upon many-core platforms. However, many-core platforms have high wear-out failure rate. Hence, the last issue to be addressed in the thesis is how to replace defective cores on many-core platforms so that deployed applications’ real-time properties can be maintained. We develop an offline and an online application-aware system reconfiguration strategy to minimize the impact of the physical layer changes on deployed real-time applications. All the developed approaches are evaluated through extensive simulations. The results indicate that the developed approaches are more effective in addressing the identified problems compared to the existing ones in the literature. Ph.D. in Computer Science, May 2015 Show less
