Pattern-based Interactive Configuration Derivation for Cyber-physical System Product Lines

IF 2 Q3 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS
Hong Lu, T. Yue, Shaukat Ali
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引用次数: 2

Abstract

Deriving a Cyber-Physical System (CPS) product from a product line requires configuring hundreds to thousands of configurable parameters of components and devices from multiple domains, e.g., computing, control, and communication. A fully automated configuration process for a CPS product line is seldom possible in practice, and a dynamic and interactive process is expected. Therefore, some configurable parameters are to be configured manually, and the rest can be configured either automatically or manually, depending on pre-defined constraints, the order of configuration steps, and previous configuration data in such a dynamic and interactive configuration process. In this article, we propose a pattern-based, interactive configuration derivation methodology (named as Pi-CD) to maximize opportunities of automatically deriving correct configurations of CPSs by benefiting from pre-defined constraints and configuration data of previous configuration steps. Pi-CD requires architectures of CPS product lines modeled with Unified Modeling Language extended with four types of variabilities, along with constraints specified in Object Constraint Language (OCL). Pi-CD is equipped with 324 configuration derivation patterns that we defined by systematically analyzing the OCL constructs and semantics. We evaluated Pi-CD by configuring 20 CPS products of varying complexity from two real-world CPS product lines. Results show that Pi-CD can achieve up to 72% automation degree with a negligible time cost. Moreover, its time performance remains stable with the increase in the number of configuration parameters as well as constraints.
基于模式的信息物理系统产品线交互配置派生
从产品线衍生网络物理系统(CPS)产品需要从多个领域配置数百到数千个组件和设备的可配置参数,例如计算、控制和通信。CPS产品线的完全自动化配置过程在实践中是不可能的,并且需要一个动态和交互式的过程。因此,在这种动态和交互式配置过程中,根据预定义的约束、配置步骤的顺序和先前的配置数据,一些可配置参数将手动配置,其余参数可以自动或手动配置。在本文中,我们提出了一种基于模式的交互式配置推导方法(称为Pi-CD),通过受益于先前配置步骤的预定义约束和配置数据,最大限度地提高自动推导CPSs正确配置的机会。Pi-CD需要使用统一建模语言建模的CPS产品线架构,该语言扩展了四种类型的变量,以及对象约束语言(OCL)中指定的约束。Pi-CD配备了324个配置派生模式,我们通过系统分析OCL结构和语义来定义这些模式。我们通过从两条真实世界的CPS产品线中配置20种不同复杂性的CPS产品来评估Pi-CD。结果表明,Pi-CD可以在可忽略的时间成本下实现高达72%的自动化程度。此外,随着配置参数和约束数量的增加,其时间性能保持稳定。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
ACM Transactions on Cyber-Physical Systems
ACM Transactions on Cyber-Physical Systems COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS-
CiteScore
5.70
自引率
4.30%
发文量
40
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