计算连续体中的自主性和智能：挑战、推动因素和未来的发展方向
Autonomy and Intelligence in the Computing Continuum: Challenges, Enablers, and Future Directions for Orchestration
摘要：
未来的人工智能应用程序需要现有的依赖云的系统架构无法提供的性能，可靠性和隐私。在本文中，我们研究设备-边缘-云连续体中的编排，并重点关注用于资源编排的边缘人工智能。我们声称，为了支持设备-边缘-云计算连续体中智能应用不断增长的需求，资源编排需要拥抱边缘AI，并强调本地自治和智能。为了证明这一说法，我们提供了一个统一体编排的一般定义，并研究了当前和新兴的编排范式如何适用于计算连续体。我们描述了某些主要的新兴研究主题，可能会影响未来的编排，并提供了一个编排范式，拥抱这些研究主题的早期愿景。最后，我们调查了当前的关键AI方法，并研究了它们如何有助于实现未来连续体编排的愿景。
英文摘要：
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.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
