Distributed digital infrastructures for computation and analytics are now evolving towards an interconnected ecosystem allowing complex applications to be executed from IoT Edge devices to the HPC Cloud (aka the Computing Continuum, the Digital Continuum, or the Transcontinuum). Understanding end-to-end performance in such a complex continuum is challenging. This breaks down to reconciling many, typically contradicting application requirements and constraints with low-level infrastructure design choices. One important challenge is to accurately reproduce relevant behaviors of a given application workflow and representative settings of the physical infrastructure underlying this complex continuum. We introduce a rigorous methodology for such a process and validate it through E2Clab. It is the first platform to support the complete experimental cycle across the Computing Continuum: deployment, analysis, optimization. Preliminary results with real-life use cases show that E2Clab allows one to understand and improve performance, by correlating it to the parameter settings, the resource usage and the specifics of the underlying infrastructure.

中文翻译：

---

在边缘到云连续体上实现复杂工作流的可重现分析

用于计算和分析的分布式数字基础设施现在正朝着互连的生态系统发展，允许从物联网边缘设备到 HPC 云（又名计算连续体、数字连续体或跨连续体）执行复杂的应用程序。在如此复杂的连续体中理解端到端性能具有挑战性。这分解为协调许多通常与应用程序要求和约束相矛盾的低级基础设施设计选择。一个重要的挑战是准确地重现给定应用程序工作流的相关行为以及作为这个复杂连续体基础的物理基础设施的代表性设置。我们为这样的过程引入了严格的方法论，并通过 E2Clab 对其进行了验证。它是第一个支持跨计算连续体的完整实验周期的平台：部署、分析、优化。实际用例的初步结果表明，E2Clab 通过将性能与参数设置、资源使用情况和底层基础设施的细节相关联，可以让人们了解和提高性能。