Application-level Swarm-based Orchestration Across the Cloud-to-Edge Continuum

在云到边缘计算连续体中收集和分析大量数据提出了新的挑战。在云中集中处理所有这些数据数据中心不再可行，将大量数据转移到云中既耗时又昂贵，还会降低性能，并可能引起安全问题。因此，出现了新的分布式计算范式，如边缘计算和雾计算，以支持更接近其起源的数据处理。然而，这种超分布式系统需要全新的方法。为了克服当前集中式应用程序管理方法的局限性，swarmhestrat将基于自组织相互依赖的swarm的概念，开发一种全新的去中心化应用程序级编排器。应用程序微服务由分散的编排代理在动态编排空间中管理，由分布式智能管理，该智能提供应用程序需求和资源之间的匹配，并支持集群的动态自组织。知识和信任对编排空间的运作至关重要，将通过基于区块链的可信解决方案，使用自主身份（SSI）和分布式标识符（DID）的方法进行管理。整个系统的端到端安全性将通过利用最先进的加密算法和保护隐私的数据分析来保证。由于分散系统迫在眉睫的复杂性，在开发的早期阶段，将开发新的模拟方法来测试和优化系统行为（例如，能源效率）。此外，模拟器将进一步扩展为与物理系统并行运行的数字双胞胎，并通过预测反馈改善其行为。Swarmchestrate概念将以四个现实生活中的演示为原型，分别来自防洪、停车位管理、视频分析和自然栖息地的数字孪生体。

Collecting and analysing large amounts of data in the Cloud-to-Edge computing continuum raises novel challenges. Processing all this data centrally in cloud data centresis not feasible anymore astransferring large amounts of data to the cloud istime-consuming, expensive, degrade performance and may raise security concerns. Therefore, novel distributed computing paradigms, such as edge and fog computing emerged to support processing data closer to its origin. However, such hyper-distributed systems require fundamentally new methods. To overcome the limitation of current centralised application management approaches, Swarmhestrate will develop a completely novel decentralised application-level orchestrator, based on the notion of self-organised interdependent Swarms. Application microservices are managed in a dynamic Orchestration Space by decentralised Orchestration Agents, governed by distributed intelligence that provides matchmaking between application requirements and resources, and supports the dynamic self-organisation of Swarms. Knowledge and trust, essential for the operation of the Orchestration Space, will be managed through blockchain-based trusted solutions using methods of Self-Sovereign Identities (SSI) and Distributed Identifiers (DID). End-to-end security of the overall system will be assured by utilising state-of-the-art cryptographic algorithms and privacy preserving data analytics. Due to the imminent complexity of the decentralised system, novel simulation approaches will be developed to test and optimise system behaviour (e.g., energy efficiency) in the early stages of development. Additionally, the simulator will be further extended into a digital twin running in parallel to the physical system and improving its behaviour with predictive feedback. The Swarmchestrate concept will be prototyped on four real-life demonstrators from the areas of flood prevention, parking space management, video analytics and a digital twin of natural habitat.