The Computing Continuum (CC) integrates different layers of processing infrastructure, from Edge to Cloud, to optimize service quality through ubiquitous and reliable computation. Compared to central architectures, however, heterogeneous and dynamic infrastructure increases the complexity for service orchestration. To guide research, this article first summarizes structural problems of the CC, and then, envisions an ideal solution for autonomous service orchestration across the CC. As one instantiation, we show how Active Inference, a concept from neuroscience, can support self-organizing services in continuously interpreting their environment to optimize service quality. Still, we conclude that no existing solution achieves our vision, but that research on service orchestration faces several structural challenges. Most notably: provide standardized simulation and evaluation environments for comparing the performance of orchestration mechanisms. Together, the challenges outline a research roadmap toward resilient and scalable service orchestration in the CC.

翻译：计算连续体（CC）通过整合从边缘到云的不同处理基础设施层，借助无处不在且可靠的计算来优化服务质量。然而，与集中式架构相比，异构且动态的基础设施增加了服务编排的复杂性。为引导研究，本文首先总结了CC的结构性问题，进而展望了一种跨CC自主服务编排的理想解决方案。作为一个具体实例，我们展示了源自神经科学的主动推理（Active Inference）概念如何支持自组织服务持续解读其环境以优化服务质量。尽管如此，我们得出结论：现有解决方案均未实现我们的愿景，且服务编排研究面临若干结构性挑战。其中最突出的是：需提供标准化的仿真与评估环境以比较不同编排机制的性能。这些挑战共同勾勒出一条通往CC中弹性可扩展服务编排的研究路线图。