Hybrid Approach on Cache Aware Real-Time Scheduling for Multi-Core Systems

Abstract

The Worst-Case Execution Time of a task is important in real-time systems. This metric is used by the scheduler in order to schedule all tasks before their deadlines. However, cache memory has a significant impact on the execution time and thus the WCET. Therefore, different cache analysis methodologies exist to determine the WCET, each with their own advantages and/or disadvantages. In this paper, a new hybrid approach is proposed which combines the strengths of two common analysis techniques. This hybrid methodology tackles the problem that can be described as ’the gap between thinking like a machine and thinking like a human being’. The two-layer hybrid model splits the code of tasks into so-called basic blocks. The WCET can be determined by performing execution time measurements on each block and statically combining those results. The COBRA-HPA framework is specially developed to facilitate the process of generating a hybrid block model and corresponding source files for time measurements. Additionally, the framework is able to generate timed automata models for UPPAAL. In conclusion, the results show that the block size has a great influence on the performance of the hybrid analysis. Thus, future work will focus on improving the hybrid model and determining the optimal size of the blocks.