可编程网络中基于意图的元调度：一项研究议程
Intent-based Meta-Scheduling in Programmable Networks: A Research Agenda
AI总结：
本文针对5G及超5G可编程网络提出基于意图的动态元调度研究议程，利用主动推断实现调度器自主性与元调度器全局协调，并给出试探性架构及关键研究问题。
摘要：
5G及超5G（B5G）网络的兴起与发展催生了所谓的“可编程”网络，即其操作要求极为严苛，只能以自动化、极少或无需人工干预的方式才能满足的网络。此类网络上的任何需求都需要通过意图进行形式化规范，意图能以形式化且易于理解的方式表示用户需求。通过意图满足用户需求将需要在网络中快速实现资源分配与调度。此外，鉴于可编程网络的预期规模与地理分布，需要同时实现多个资源调度方案。这将需要使用一个元调度器来协调各个调度器，并动态确保整个网络内的最优资源调度。为此，在这篇立场性论文中，我们提出了一项研究议程，旨在为可编程网络中基于意图的动态元调度的建模、实现与纳入进行研究。我们的研究议程将建立在主动推断（一种因果推断）的基础之上。主动推断为每个调度器提供一定程度的自主性，而元调度器则负责整体的意图实现。我们的研究议程将包含一个用于元调度的试探性架构，以及一系列为使基于意图的动态元调度成为现实而需要解决的研究问题。
英文摘要：
The emergence and growth of 5G and beyond 5G (B5G) networks has brought about the rise of so-called ''programmable'' networks, i.e., networks whose operational requirements are so stringent that they can only be met in an automated manner, with minimal/no human involvement. Any requirements on such a network would need to be formally specified via intents, which can represent user requirements in a formal yet understandable manner. Meeting the user requirements via intents would necessitate the rapid implementation of resource allocation and scheduling in the network. Also, given the expected size and geographical distribution of programmable networks, multiple resource scheduling implementations would need to be implemented at the same time. This would necessitate the use of a meta-scheduler that can coordinate the various schedulers and dynamically ensure optimal resource scheduling across the network. To that end, in this position paper, we propose a research agenda for modeling, implementation, and inclusion of intent-based dynamic meta-scheduling in programmable networks. Our research agenda will be built on active inference, a type of causal inference. Active inference provides some level of autonomy to each scheduler while the meta-scheduler takes care of overall intent fulfillment. Our research agenda will comprise a strawman architecture for meta-scheduling and a set of research questions that need to be addressed to make intent-based dynamic meta-scheduling a reality.
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。
