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QoS-based dynamic allocation in embedded systems: A methodology and a framework

机译:嵌入式系统中基于QoS的动态分配:方法和框架

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This paper focuses on a methodology for the dynamic allocation of embedded resources apt to satisfy requests of service with constraints of Quality of Service (QoS). Given a set of services provided by an embedded system, this methodology suggests how to determine the best match between a requested service and the set of Embedded subSystems (EsSs) able to provide that service. The selection of EsSs is carried out on the basis of the results of an a priori evaluation of the performances of service execution and of the availability of the single embedded resources. Moreover, the proposed methodology defines some guidelines to dynamically schedule and thus to assign the execution of the services to the chosen EsSs. With regard to the selection process this methodology benefits from both the content- and the collaborative-based filtering methods. To evaluate its consistency it has been implemented in a testing framework, named BIOS, that includes a repository of services, of service providers (i.e. of EsSs), of evaluation outcomes of the performances of each EsS in carrying out its own services, of an engine for the dynamic selection of the EsSs able to satisfy the requirements of a given service and of a container of Real-Time Operating Systems (RTOSs) able to efficiently schedule and to assign the execution of the requested services to the chosen EsSs. Considering state-of-the-art services provided by Body Sensor Network (BSN) subsystems, the hybrid solution proposed for the selection process has been tested and it has shown better results in comparison to the content-based filtering technique.
机译:本文着重于一种动态分配嵌入式资源的方法,该方法易于满足服务质量限制(QoS)的服务请求。给定嵌入式系统提供的一组服务,此方法建议如何确定请求的服务与能够提供该服务的一组嵌入式子系统(EsS)之间的最佳匹配。 EsS的选择是基于对服务执行性能和单个嵌入式资源的可用性进行的先验评估的结果进行的。此外,所提出的方法定义了一些准则以动态调度,从而将服务的执行分配给所选的EsS。关于选择过程,此方法既可从基于内容的过滤方法中受益,也可从基于协作的过滤方法中受益。为了评估其一致性,已在名为BIOS的测试框架中实现了该框架,其中包括服务,服务提供商(即EsSs)的存储库,每个EsS在执行其自身服务时的性能评估结果,动态选择能够满足给定服务要求的EsS引擎和实时操作系统(RTOS)容器的能力,这些容器能够有效地调度所请求的服务并将所执行的服务分配给选定的EsS。考虑到人体传感器网络(BSN)子系统提供的最新服务,已经测试了为选择过程建议的混合解决方案,与基于内容的过滤技术相比,它显示出更好的结果。

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