A task that suspends itself to wait for an I/O completion or to wait for an event from another node in distributed environments is called an I/O blocking task. Conventional hard real-time scheduling theories use framework of rate monotonic analysis (RMA) to schedule such I/O blocking tasks. However, most of them are pessimistic. In this paper, we propose effective algorithms that can schedule a task set which has I/O blocking tasks under dynamic priority assignment. We present a new critical instant theorem for the multi-frame task set under dynamic priority assignment. The schedulability is analyzed under the new critical instant theorem. For the schedulability analysis, this paper presents saturation summation which is used to calculate the maximum interference function (MIF). With saturation summation, the schedulability of a task set having I/O blocking tasks can be analyzed more accurately. We propose an algorithm which is called Frame Laxity Monotonic Scheduling (FLMS). A genetic algorithm (GA) is also applied. From our experiments, we can conclude that FLMS can significantly reduce the calculation time, and GA can improve task schedulability ratio more than is possible with FLMS.

As a next-generation CAN (Controller Area Network), CAN FD (CAN with flexible data rate) has attracted much attention recently. However, how to use the improved bus bandwidth efficiently in CAN FD is still an issue. Contrasting with existing methods using greedy approximate algorithms, this paper proposes a genetic algorithm for CAN FD frame packing. It tries to minimize the bandwidth utilization by considering the different periods of signals when packing them in the same frame. Moreover, it also checks the schedulability of packed frames to guarantee the real-time constraints of each frame and proposed a merging algorithm to improve the schedulability for signal set with high bus load. Experimental results validate that the proposed algorithm can achieve significantly less bandwidth utilization and improved schedulability than existing methods for a given set of signals.

An advanced communication system, the FlexRay system, has been developed for future automotive applications. It consists of time-triggered clusters, such as drive-by-wire in cars, in order to meet different requirements and constraints between various sensors, processors, and actuators. In this paper, an approach to static scheduling for FlexRay systems is proposed. Our experimental results show that the proposed scheduling method significantly reduces up to 36.3% of the network traffic compared with a past approach.