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。这种复杂性大大增加了群体系统，这是高度动态和异构的，需要分散的解决方案，以适应高度动态的系统条件。TaRDIS项目的重点是支持正确和有效地开发应用程序的集群和分散的分布式系统，通过结合一个新的编程范式与工具箱，以支持应用程序的开发和执行。TaRDIS提出了一种独立于语言的事件驱动编程范式，通过基于事件的接口，暴露了分布抽象和强大的分散式机器学习原语。程序设计环境将协助建立正确的系统，利用行为类型自动分析各组成部分的相互作用，以确保其应用程序的设计正确，同时考虑到应用程序的不变量和目标执行环境的特性。TaRDIS底层分布式中间件将提供基本服务，包括数据管理和分散的机器学习组件。该中间件将通过以自主和智能的方式编排和适应跨设备的不同应用组件的执行来隐藏异构性并解决分布式执行环境的动态性。TaRDIS的结果将被集成到一个开发环境中，也可以作为独立的工具，这两者都可以用于开发群系统的应用程序。项目结果将在高影响力工业合作伙伴提供的四个不同用例的背景下进行验证，这些用例包括卫星群、去中心化动态市场、用于个人助理应用的去中心化机器学习解决方案以及分布式控制过程。智能工厂。

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.