ARTOS: adaptive resource scheduling for component-based soft real-time applications

ARTOS：基于组件的软实时应用程序的自适应资源调度

• 批准号: 240634290
• 负责人: Professor Dr.-Ing. Franz J. Hauck
• 金额: --
• 依托单位: Institut für Verteilte Systeme (VS)
• 依托单位国家: 德国
• 项目类别: Research Grants
• 财政年份: 2013
• 资助国家: 德国
• 起止时间: 2012-12-31 至 2016-12-31
• 项目状态: 已结题
• 来源: https://gepris.dfg.de/gepris/projekt/240634290?language=en
• 关键词: ARTOS; adaptive; resource; scheduling; component

Real-time systems mostly need ex ante knowledge of required resource consumptions. This is contradictory to modern usage scenarios where applications (apps) are downloaded and installed on diverse systems, and used concurrently to each other. If applications use already existing components, an exact statement of required resouces is almost impossible. Therefore, our goal is a platform that can support applications with soft real-time requirements, e.g., multimedia applications. These can be dynamically installed and used. Their ex ante unknown resource requirements on CPU time shall be fulflilled considering preferences of the end user. As implementation platform, we use real-time Java (RTSJ) and OSGi.Multiple modes of operation are added to each application. Each mode delivers different quality but also has different resource requirements. Driven by the preferences of the end user, who can favour or penalise applications, the platform takes care of a coordinated and ideal resource distribution by selecting a mode for each application. If resources are too short, less important application are degraded first, or even stopped.The scientific challenges lie in the measurment of the actually needed resources in each mode, even for previously unknown applications, in the automatic configuration of optimal modes and the dynamic adaptation of the system on changes of requirements and of available resources. Special attention is given to keeping the number of reconfigurations as low as possible and to handling periodic peak loads by phase shifts.

实时系统大多需要预先知道所需的资源消耗。这与现代使用场景相矛盾，在现代使用场景中，应用程序（应用程序）被下载并安装在不同的系统上，并且彼此并发使用。如果应用程序使用已经存在的组件，则几乎不可能准确地说明所需的资源。因此，我们的目标是一个平台，可以支持软实时要求的应用程序，例如，多媒体应用。可以动态安装和使用。其对CPU时间的事先未知资源要求应考虑最终用户的偏好来满足。作为实现平台，我们使用实时Java（RTSJ）和OSGi。每种模式提供不同的质量，但也有不同的资源要求。在最终用户偏好的驱动下，该平台可以支持或惩罚应用程序，通过为每个应用程序选择一种模式来协调和理想的资源分配。如果资源太短，不太重要的应用程序首先降级，甚至停止。科学的挑战在于测量每个模式中实际需要的资源，即使是以前未知的应用程序，自动配置最佳模式以及系统对需求和可用资源变化的动态适应。特别注意保持尽可能低的重新配置的数量，并通过相移处理周期性峰值负载。