Trustworthy and Resilient Decentralised Intelligence for Edge Systems

开发和管理分布式系统是一项复杂的任务，需要跨多个领域的专业知识。这种复杂性在集群系统中大大增加，因为集群系统是高度动态和异质的，需要适应高度动态系统条件的分散解决方案。Tardis项目通过将新的编程范例与支持应用程序开发和执行的工具箱相结合，专注于支持集群和分散分布式系统的正确和高效的应用程序开发。Tardis提出了一种独立于语言的事件驱动编程范例，它通过基于事件的接口公开了分布抽象和强大的分散式机器学习原语。编程环境将通过利用行为类型自动分析组件的交互来帮助构建正确的系统，以确保其应用程序的设计正确性，同时考虑到应用程序不变量和目标执行环境的属性。TARDIS底层分布式中间件将提供基本的服务，包括数据管理和分散的机器学习组件。中间件将通过以自主和智能的方式编排和调整跨设备的不同应用程序组件的执行来隐藏异构性并解决分布式执行环境的动态化。Tardis结果将集成在一个开发环境中，也可以作为独立的工具，这两个工具都可以用于为Sarm系统开发应用程序。项目结果将在高影响力的工业合作伙伴提供的四个不同用例的背景下得到验证，这些用例包括成群的卫星、分散的动态市场、用于个人助理应用的分散的机器学习解决方案，以及智能工厂的分布式控制流程。

Developing and managing distributed systems is a complex task requiring expertise across multiple domains. This complexity considerably increases in swarm systems, which are highly dynamic and heterogeneous and require decentralised solutions that adapt to highly dynamic system conditions. The project TaRDIS focuses on supporting the correct and efficient development of applications for swarms and decentralised distributed systems, by combining a novel programming paradigm with a toolbox for supporting the development and executing of applications. TaRDIS proposes a language-independent event-driven programming paradigm that exposes, through an event-based interface, distribution abstractions and powerful decentralised machine learning primitives. The programming environment will assist in building correct systems by taking advantage of behavioural types to automatically analyse the component's interactions to ensure correctness-by-design of their applications, taking into account application invariants and the properties of the target execution environment. TaRDIS underlying distributed middleware will provide essentialservices, including data management and decentralised machine learning components. The middleware will hide the heterogeneity and address the dynamicity of the distributed execution environment by orchestrating and adapting the execution of different application components across devices in an autonomic and intelligent way. TaRDIS results will be integrated in a development environment, and also as standalone tools, both of which can be used for developing applications for swarm systems. The project results will be validated in the context of four different use cases provided by high impact industrial partners that range from swarms of satellites, decentralised dynamic marketplaces, decentralised machine learning solutions for personal-assistant applications, and the distributed control process of a smart factory.