A generative framework for IoT migration of legacy systems

物联网(IoT)应用为公司提供有关其产品和服务的见解，以改进其决策流程，这解释了人们对采用IoT技术的兴趣日益浓厚。然而，公司在将其传统应用迁移到物联网时面临着几个挑战。假设一家五金店想要将其库存管理系统迁移到物联网。通过使用传感器，商店希望实时定位其产品。为了实现迁移，我们必须将遗留系统从调用返回体系结构(CRA)演变为事件驱动体系结构(EDA)。在CRA中，组件通过同步调用进行通信，并通过用户输入提供新数据。在EDA中，事件使分离的设备和组件之间能够进行异步通信，并且通过各种来源的事件(例如，通知产品属性变化的传感器)提供新数据。当有大量的异类设备，并且可能有多个云平台时，这种CRA到IoT EDA的迁移并不是微不足道的。现有的物联网EDA平台可以帮助实现迁移。然而，选择合适的平台并向该平台迁移并非易事，因为它们在事件流和管理、性能、可靠性和安全性方面提供了不同的功能。此研究计划的目标是构建一种由方法和工具组成的方法，以帮助将传统CRA系统迁移到IoT EDA。实现这一目标的拟议方法依赖于经验工程和模型驱动工程。特别是，我们将开展经验性研究，以确定物联网EDA平台的共同和不同功能，并构建传统系统在CRA到IoT EDA迁移过程中必须经历的反复更改的目录-称为物联网迁移模式。我们将利用模型驱动的技术：(1)抽象常见的物联网EDA平台并自动派生给定平台的平台描述模型；(2)以可操作的形式对确定的物联网迁移模式进行编码；(3)将遗留系统的组件映射到适当的物联网迁移模式；以及(4)使用这些映射半自动支持物联网迁移中体现的重构。该计划的结果将对寻求从物联网技术中获益的加拿大企业具有重要价值。这将有助于更好地了解物联网平台，并改进物联网迁移流程并降低其成本。这项研究计划也有可能对研究产生重大影响。它将通过物联网技术解决方案增强当前的架构知识，定义物联网迁移模式，并通过半自动重构为其提供支持。参与该计划的HQP将接受模型驱动技术、物联网技术和物联网迁移模式方面的培训。软件公司对它们的需求将会很高。

Internet of things (IoT) applications provide insights to companies about their products and services to improve their decision-making processes, which explains the growing interest in adopting IoT technologies. Yet, companies face several challenges when migrating their legacy applications to the IoT. Consider a hardware store that wants to migrate their inventory management system towards the IoT. Using sensors, the store wants to locate its products in real-time. To achieve the migration, we must evolve the legacy system from a call-and-return architecture (CRA) to an event-driven architecture (EDA). In the CRA, components communicate through synchronous calls and new data is provided through user inputs. In the EDA, events enable asynchronous communication between decoupled devices and components, and new data is provided via events of various sources (e.g., sensors that signal product attribute changes). This CRA to IoT EDA migration is not trivial when there is a high number of heterogeneous devices and, possibly, multiple Cloud platforms. Existing IoT EDA platforms can help in the migration. Yet, choosing the appropriate platform and performing the migration towards this platform is not straightforward because they provide different capabilities in terms of event streaming and management, performance, reliability and security. The goal of this research program is to build an approach composed of a methodology and tools to help with the migration of legacy CRA systems towards IoT EDA. The proposed methodology to achieve this goal relies on empirical engineering and model-driven engineering. In particular, we will carry out empirical studies to identify common and dissimilar features of IoT EDA platforms, and to build a catalog of recurring changes-called IoT migration patterns- that a legacy system must undergo in a CRA to IoT EDA migration. We will leverage model-driven technologies: (1) to abstract common IoT EDA platforms and automatically derive a platform description model for a given platform, (2) to codify the identified IoT migration patterns in an operationalizable form, (3) to map components of the legacy system to the appropriate IoT migration patterns and (4) use these mappings to semi-automatically support the refactorings embodied in the IoT migration. The outcome of this program will be of great value to Canadian enterprises seeking to benefit from the IoT technologies. It will contribute to a better understanding of IoT platforms and to improve the IoT migration process and reduce its cost. This research program has also potential for a significant impact on research. It will augment current architectural knowledge with IoT technology solutions, define IoT migration patterns and support them through semi-automatic refactorings. The HQP involved in this program will be trained in model-driven technologies, IoT technologies and IoT migration patterns. They will be in high demand by software companies.