Real-Time Systems最新文献

Bounding the Worst-Case Execution Time (WCET) of real-time software requires precise knowledge about the reachable program and hardware states that might be observed at runtime. The analysis of precise cache states is particularly important and challenging. Due to the high cost of cache misses the analysis precision may have an important impact on the obtainable WCET bounds, while the large state space of the cache’s history leads to high analysis complexity. This work explores the use of cache summaries in order to optimize the computation of precise cache states. These cache summaries allow us to pre-compute the impact of executing a portion of a program, typically a function, on the cache state. This allows us, for instance, to skip the analysis of entire functions (including nested function calls) when the cache states within these functions are not relevant for the classification of memory accesses into hits/misses. Furthermore, the summaries can be extended to efficiently compute fully context-sensitive cache states. The summaries then not only allow to derive typical cache hit/miss classifications, but also provide fully context-sensitive cache persistence information.

The use of integer linear programs for solving complex real-time scheduling problems is investigated. The problem of scheduling a workload represented as a directed acyclic graph (DAG) upon a dedicated multiprocessor platform is considered, in which each individual vertex of the DAG is assigned to a specific processor and the entire DAG is required to complete execution within a specified duration. A representation of this scheduling problem as a zero-one integer linear program is obtained. Some guidelines are proposed for identifying scheduling problems amenable to solution by converting to integer linear programs.

Heterogeneous MPSoCs are being used more and more, from cellphones to critical embedded systems. Most of those systems offer heterogeneous sets of identical cores. In this paper, we propose new results on the global scheduling approach. We extend fundamental global scheduling results on unrelated processors to results on unrelated multicore platforms, a more realistic model. We introduce several methods to construct the workload assignment of tasks to cores taking advantage of this new model. Every studied result is optimal regarding schedulability, and all the proposed methods but one have a polynomial time complexity. Thanks to the model, the produced schedules have a limited degree of migrations. The benefits of the methods are demonstrated and compared using synthetic tasks sets. Practical limitations of the global scheduling approach on unrelated platforms are discussed, but we argue that it is still worth investigating considering modern MPSoCs.

We consider the problem of resource provisioning for real-time cyber-physical applications in an open system environment where there does not exist a global resource scheduler that has complete knowledge of the real-time performance requirements of each individual application that shares the resources with the other applications. Regularity-based Resource Partition (RRP) model is an effective strategy to hierarchically partition and assign various resource slices among the applications. However, RRP model does not consider changes in resource requests from the applications at run time. To allow for the run time adaptation to resource requirement changes, we consider in this paper the issues in online resource partition reconfiguration, including semantics issues that arise in configuration transitions that may cause application failures. Based on the reconfiguration semantics, we study the online resource reconfigurability problem under the RRP model where the availability factors of resource partitions may be reconfigured at run time. We formalize and solve the Dynamic Partition Reconfiguration (DPR) problem for uniform environment where the minimal intervals assigned to each task for execution on each resource are the same. Extensive experiments have been conducted to evaluate the performance of the proposed approaches in different scenarios. We also present a case study using the autonomous F1/10 model car; the controller of the F1/10 car requires resource adaptation to satisfy the computing needs of its PID controller and vision system under different operating conditions. Our implementation demonstrates the effectiveness and benefit of online resource partition reconfiguration using the proposed approach in a real-world cyber-physical system.