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首页> 外文期刊>EURASIP journal on embedded systems >Design and Performance Evaluation of an Adaptive Resource Management Framework for Distributed Real-Time and Embedded Systems
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Design and Performance Evaluation of an Adaptive Resource Management Framework for Distributed Real-Time and Embedded Systems

机译：分布式实时和嵌入式系统的自适应资源管理框架的设计和性能评估

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Achieving end-to-end quality of service (QoS) in distributed real-time embedded (DRE) systems require QoS support and enforcement from their underlying operating platforms that integrates many real-time capabilities, such as QoS-enabled network protocols, real-time operating system scheduling mechanisms and policies, and real-time middleware services. As standards-based quality of service (QoS) enabled component middleware automates integration and configuration activities, it is increasingly being used as a platform for developing open DRE systems that execute in environments where operational conditions, input workload, and resource availability cannot be characterized accurately a priori. Although QoS-enabled component middleware offers many desirable features, however, it historically lacked the ability to allocate resources efficiently and enable the system to adapt to fluctuations in input workload, resource availability, and operating conditions. This paper presents three contributions to research on adaptive resource management for component-based open DRE systems. First, we describe the structure and functionality of the resource allocation and control engine (RACE), which is an open-source adaptive resource management framework built atop standards-based QoS-enabled component middleware. Second, we demonstrate and evaluate the effectiveness of RACE in the context of a representative open DRE system: NASA's magnetospheric multiscale mission system. Third, we present an empirical evaluation of RACE's scalability as the number of nodes and applications in a DRE system grows. Our results show that RACE is a scalable adaptive resource management framework and yields a predictable and high-performance system, even in the face of changing operational conditions and input workload.
机译：要在分布式实时嵌入式（DRE）系统中实现端到端服务质量（QoS），需要QoS支持并从其底层操作平台实施，该平台集成了许多实时功能，例如启用QoS的网络协议，及时的操作系统调度机制和策略，以及实时中间件服务。随着启用了基于标准的服务质量（QoS）的组件中间件实现集成和配置活动的自动化，越来越多地将其用作开发开放式DRE系统的平台，该系统在无法准确表征操作条件，输入工作量和资源可用性的环境中执行先验。尽管启用了QoS的组件中间件提供了许多理想的功能，但是从历史上看，它缺乏有效分配资源并使系统适应输入工作量，资源可用性和操作条件波动的能力。本文为基于组件的开放式DRE系统的自适应资源管理研究提供了三点贡献。首先，我们描述资源分配和控制引擎（RACE）的结构和功能，该引擎是在基于标准的，支持QoS的组件中间件之上构建的开源自适应资源管理框架。其次，我们在具有代表性的开放式DRE系统的背景下演示和评估RACE的有效性：NASA的磁层多尺度任务系统。第三，随着DRE系统中节点和应用程序数量的增长，我们对RACE的可伸缩性进行了经验评估。我们的结果表明，RACE是一种可扩展的自适应资源管理框架，即使面对不断变化的运营条件和投入的工作量，也能产生可预测的高性能系统。

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