Recent development methodologies from the industry and the academia for complex real-time systems define a stage in which system functions are deployed onto an execution platform. The deployment consists of the placement of functions on a distributed network of nodes, the partitioning of functions in tasks and the scheduling of tasks and messages. In this paper, we present two approaches towards the efficient deployment of realistic and complex real-time systems by considering tree-shaped functional models. A formal approach to compute optimal deployment and a heuristic approach to scale to industry-size systems. The approaches consider placement, partitioning and scheduling, and are based on mixed integer linear programming (MILP) technique. Furthermore, we present a deep evaluation of the proposed deployment approaches to show the benefits and limits of a MILP-based deployment approach. A set of synthetic use-cases as well as a real-life automotive system are used to assess the quality and scalability of our deployment approaches. Considering use-cases, we show an added value with respect to end-to-end latencies optimization when solving the three stages of the deployment problem at the same time. This is done by comparing the quality of the solutions obtained with our techniques to those returned by the existing approaches.

中文翻译：

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实时系统树状功能图在分布式架构上的优化部署

业界和学术界针对复杂实时系统的最新开发方法定义了将系统功能部署到执行平台上的阶段。部署包括在分布式节点网络上放置功能、任务中的功能分区以及任务和消息的调度。在本文中，我们通过考虑树形功能模型提出了两种有效部署现实和复杂实时系统的方法。计算最佳部署的正式方法和扩展到工业规模系统的启发式方法。这些方法考虑了放置、分区和调度，并且基于混合整数线性规划 (MILP) 技术。此外，我们对提议的部署方法进行了深入评估，以展示基于 MILP 的部署方法的优势和局限性。一组合成用例以及现实生活中的汽车系统用于评估我们部署方法的质量和可扩展性。考虑到用例，当同时解决部署问题的三个阶段时，我们展示了端到端延迟优化方面的附加价值。这是通过将使用我们的技术获得的解决方案的质量与现有方法返回的解决方案的质量进行比较来完成的。当同时解决部署问题的三个阶段时，我们展示了端到端延迟优化方面的附加值。这是通过将使用我们的技术获得的解决方案的质量与现有方法返回的解决方案的质量进行比较来完成的。当同时解决部署问题的三个阶段时，我们展示了端到端延迟优化方面的附加值。这是通过将使用我们的技术获得的解决方案的质量与现有方法返回的解决方案的质量进行比较来完成的。