智能IoT服务模型驱动工程的数据分析和机器学习方法、技术和工具
Data Analytics and Machine Learning Methods, Techniques and Tool for Model-Driven Engineering of Smart IoT Services
摘要：
本博士论文提出了一种新的方法来加强物联网（IoT）和智能网络物理系统（CPS）的智能服务的发展。所提出的方法提供了抽象和自动化的软件工程过程，以及数据分析（DA）和机器学习（ML）的做法。这是以集成和无缝的方式实现的。我们通过扩展一个名为ThingML的开源建模工具来实现和验证所提出的方法。ThingML是一种特定于领域的语言和建模工具，可为IoT/CPS领域生成代码生成。ThingML和任何其他IoT/CPS建模工具都不支持建模级别的DA/ML。因此，作为博士论文的主要贡献，我们将有关DA/ML方法和技术的必要语法和语义添加到ThingML的建模语言中。此外，我们支持多个ML库和框架的API，用于自动生成Python和Java中目标软件的源代码。我们的方法支持独立于平台的模型以及特定于平台的模型。此外，我们通过在后台（专家模式）提供自动化ML（AutoML），并通过在设计时进行模型检查约束和提示，来帮助执行半自动化DA/ML任务。最后，我们考虑了来自网络安全、智能能源系统和能源交易市场领域的三个用例场景。
英文摘要：
This doctoral dissertation proposes a novel approach to enhance the development of smart services for the Internet of Things (IoT) and smart Cyber-Physical Systems (CPS). The proposed approach offers abstraction and automation to the software engineering processes, as well as the Data Analytics (DA) and Machine Learning (ML) practices. This is realized in an integrated and seamless manner. We implement and validate the proposed approach by extending an open source modeling tool, called ThingML. ThingML is a domain-specific language and modeling tool with code generation for the IoT/CPS domain. Neither ThingML nor any other IoT/CPS modeling tool supports DA/ML at the modeling level. Therefore, as the primary contribution of the doctoral dissertation, we add the necessary syntax and semantics concerning DA/ML methods and techniques to the modeling language of ThingML. Moreover, we support the APIs of several ML libraries and frameworks for the automated generation of the source code of the target software in Python and Java. Our approach enables platform-independent, as well as platform-specific models. Further, we assist in carrying out semiautomated DA/ML tasks by offering Automated ML (AutoML), in the background (in expert mode), and through model-checking constraints and hints at design-time. Finally, we consider three use case scenarios from the domains of network security, smart energy systems and energy exchange markets.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
