Processor partitioning and hierarchical scheduling have been widely used for composing hard real-time systems on a shared hardware platform while preserving the timing requirements of the systems. Due to the safety critical nature of hard real-time systems, a conservative analysis is often used for deriving a sufficient partition size. Applying the exact same analysis for deriving the partition sizes for soft real-time systems result in unnecessary processors overallocation and consequently waste of the CPU resource.In this paper, to address the problem of composing soft and hard real-time systems on a resource constrained shared hardware, we present a multi-level adaptive hierarchical scheduling framework. In our framework, we adapt the processor partition sizes of soft real-time systems according to their need at each time point by on-line monitoring their processor demand. Furthermore, we implement our adaptive framework in the Linux kernel and show the performance of our framework using a case study.
When designing complex mixed-critical systems on multiprocessor platforms, a huge number of design alternatives has to be evaluated. Therefore, there is a need for tools which systematically find and analyze the ample alternatives and identify solutions that satisfy the design constraints. The recently proposed design space exploration (DSE) tool DeSyDe uses constraint programming (CP) to find implementations with performance guarantees for multiple applications with potentially mixed-critical design constraints on a shared platform. A key component of the DeSyDe tool is its throughput analysis component, called a throughput propagator in the context of CP. The throughput propagator guides the exploration by evaluating each design decision and is therefore executed excessively throughout the exploration. This paper presents two throughput propagators based on different analysis methods for DeSyDe. Their performance is evaluated in a range of experiments with six different application graphs, heterogeneous platform models and mixed-critical design constraints. The results suggest that the MCR throughput propagator is more efficient.
Contemporary distributed embedded systems in many domains have become highly complex due to ever-increasing demand on advanced computer controlled functionality. The resource reservation techniques can be effective in lowering the software complexity, ensuring predictability and allowing flexibility during the development and execution of these systems. This paper proposes a novel end-to-end resource reservation model for distributed embedded systems. In order to support the development of predictable systems using the proposed model, the paper provides a method to design resource reservations and an end-to-end timing analysis. The reservation design can be subjected to different optimization criteria with respect to runtime footprint, overhead or performance. The paper also presents and evaluates a case study to show the usability of the proposed model, reservation design method and end-to-end timing analysis.
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