Future AI applications require performance, reliability and privacy that the existing, cloud-dependant system architectures cannot provide. In this article, we study orchestration in the device-edge-cloud continuum, and focus on edge AI for resource orchestration. We claim that to support the constantly growing requirements of intelligent applications in the device-edge-cloud computing continuum, resource orchestration needs to embrace edge AI and emphasize local autonomy and intelligence. To justify the claim, we provide a general definition for continuum orchestration, and look at how current and emerging orchestration paradigms are suitable for the computing continuum. We describe certain major emerging research themes that may affect future orchestration, and provide an early vision of an orchestration paradigm that embraces those research themes. Finally, we survey current key edge AI methods and look at how they may contribute into fulfilling the vision of future continuum orchestration.

翻译：未来的人工智能应用对性能、可靠性和隐私提出了更高要求，而现有依赖云的系统架构无法满足这些需求。本文研究设备-边缘-云连续体中的编排问题，重点关注用于资源编排的边缘人工智能。我们主张，为支持设备-边缘-云计算连续体中智能应用不断增长的需求，资源编排需要采纳边缘人工智能，并强化局部自主性与智能。为论证这一主张，我们给出了连续体编排的通用定义，并审视了当前及新兴编排范式对算力连续体的适用性。我们描述了若干可能影响未来编排的重大新兴研究主题，并提出了一个融合这些研究主题的编排范式初步愿景。最后，我们调研了当前关键的边缘人工智能方法，并探讨了它们如何助力实现未来连续体编排的愿景。