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Engineering dynamic real-time distributed systems: architecture,system description language, and middleware

机译:工程动态实时分布式系统:体系结构,系统描述语言和中间件

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The paper presents an architectural framework and algorithms fornengineering dynamic real-time distributed systems using commercialnoff-the-shelf technologies. In the proposed architecture, a real-timensystem application is developed in a general-purpose programmingnlanguage. Further, the architectural-level description of the systemnsuch as composition and interconnections of application software andnhardware, and the operational requirements of the system such asntimeliness and survivability are specified in a system descriptionnlanguage. The specification of the system is automatically translatedninto an intermediate representation (IR) that models the system in anplatform-independent manner. The IR is augmented with dynamicnmeasurements of the system by a language runtime system to produce andynamic system model. The dynamic model is used by resource managementnmiddleware strategies to perform resource management that achievesntimeliness and survivability requirements. We present two classes ofnalgorithms: predictive and availability-based, for performing resourcenallocation. To validate the viability of the approach, we use anreal-time benchmark application that functionally approximates dynamicnreal-time command and control systems. The benchmark results illustratenthat the middleware is able to achieve the desired timelinessnrequirements during a number of load situations. Furthermore,navailability-based allocation algorithms perform resource allocationnless frequently, whereas predictive algorithms give a better steadynstate performance for the application
机译:本文提出了一种使用现成的商用技术来设计动态实时分布式系统的架构框架和算法。在提出的体系结构中,以通用编程语言开发了实时系统应用程序。此外,在系统描述语言中指定了系统的体系结构级别的描述,例如应用程序软件和硬件的组成和互连,以及系统的操作要求,例如及时性和可生存性。系统规范会自动转换为以平台无关的方式对系统进行建模的中间表示(IR)。通过语言运行时系统对IR进行系统的动态测量,从而生成动态系统模型。资源管理中间件策略使用动态模型来执行实现及时性和生存性要求的资源管理。我们提出两类算法:用于执行资源分配的预测算法和基于可用性的算法。为了验证该方法的可行性,我们使用了一个实时基准测试应用程序,该应用程序在功能上近似于动态实时命令和控制系统。基准测试结果表明,在许多负载情况下,中间件都能达到所需的及时性。此外,基于可用性的分配算法无需频繁执行资源分配,而预测算法为应用程序提供了更好的稳态性能

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