用SosADL应对物联网系统体系结构建模中的不确定性

F. Oquendo
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引用次数: 6

摘要

在系统的系统(so)的体系结构设计中,一个具有挑战性的问题是如何处理由于对实际部署so的操作环境以及在运行时具体参与so的组成系统的有限知识所带来的不确定性。特别是在物联网(IoT)上构建的sos。事实上,由于物联网的开放性和动态性,一方面,在设计时,大多数情况下,SoS架构师不知道哪些将是具体的物联网系统,这些系统将成为SoS的组成部分,这些系统主要在运行时识别;另一方面,正确的架构不仅取决于组成物联网系统,而且在很大程度上取决于SoS将在物联网上定位的操作环境。因此,随之而来的研究问题是如何以足够灵活的方式设计和描述SoS体系结构,以应对这些不同的不确定性。为了解决这一挑战,本文研究了SoS中不确定性的概念,并介绍了SosADL(一种正式的SoS体系结构描述语言(ADL))如何能够处理SoS体系结构建模中的不确定性。它提出了一些概念和结构,使描述SoS体系结构成为可能,这些体系结构将在物联网的不可预测环境中运行,基于SosADL对处理部分知识的支持,基于并发约束。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Coping with Uncertainty in Systems-of-Systems Architecture Modeling on the IoT with SosADL
A challenging issue in the architectural design of a System-of-Systems (SoS) is how to cope with the uncertainty raised by the limited knowledge of the operational environment where the SoS will actually be deployed as well as the constituent systems which will concretely participate in the SoS at run-time. It is especially the case of SoSs being architected on the Internet-of-Things (IoT). Indeed, due to the open and dynamic nature of the IoT, on the one hand, at design-time, most often the SoS architects do not know which will be the concrete IoT systems that will become constituents of an SoS, these being predominantly identified at run-time; on the other hand, the correct architecture depends not only on the constituent IoT systems but also, largely, on the operational environment where the SoS will be positioned on the IoT. The consequent research question is thereby how to design and describe the SoS architecture in a way that is flexible enough to cope with these different uncertainties. To address this challenge, this paper investigates the notion of uncertainty in SoS and presents how SosADL, a formal SoS Architecture Description Language (ADL), enables to cope with uncertainty in the architecture modeling of SoSs. It presents the concepts and constructs that makes possible to describe SoS architectures which will operate in unpredictable environments on the IoT based on the SosADL support for dealing with partial knowledge, grounded on concurrent constraints.
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