PRogrammable AI-Enabled DeterminIstiC neTworking for 6G

6G旨在加快5G开始的道路，以满足各种垂直使用案例的需求，无论是当前的还是新兴的。这将需要对当前的5G能力进行重大增强，特别是在带宽、延迟、可靠性、安全性和能源方面。因此，Forecast-6G的使命是开发端到端的6G(E2E)解决方案，包括架构和协议，这些架构和协议可以保证为需要极其严格的时间和可靠性约束的垂直用例无缝提供服务。为了取得成功，该解决方案将面向整个确定性网络基础设施，包括有线和无线网段及其互连。Forecast-6G将开发一种新的多技术多域数据平面(MDP)，彻底改变当前有线和无线标准中存在的可靠性和时间敏感性设计特征。我们的目标是让MDP的设计本质上是确定性的。为了实现这一目标，Forecast-6G将开发一个人工智能驱动的多利益相关者域间控制平面(AICP)，用于提供确定性网络路径，以支持最终客户要求的、具有不同扩展野心的时间敏感型服务，例如，从单一车辆中的网络到地理上分散的大型网络。这需要及时监测和预测整个网络的行为，包括识别潜在的质量违规来源和分析交通流量的各种路线。这些功能将通过Forecast-6G AI-Powered Digital Twin(DT)框架提供，允许预测端到端网络基础设施的行为，并能够对网络供应进行预期控制和验证，以满足实际运行服务的时间敏感度和可靠性要求

6G is envisioned to accelerate the path started in 5G for catering to the needs of a wide variety of vertical use cases, both current and emerging. This will require major enhancements of the current 5G capabilities especially in terms of bandwidth, latency, reliability, security, and energy. PREDICT-6G’s mission is therefore set towards the development of an end-to-end 6G (E2E) solution including architecture and protocols that can guarantee seamless provisioning of services for vertical use cases requiring extremely tight timing and reliability constraints. To succeed, the solution will target determinism network infrastructures at large, including wired and wireless segments and their interconnections. PREDICT-6G will develop a novel Multi-technology Multi-domain Data-Plane (MDP) overhauling the reliability and time sensitiveness design features existing in current wired and wireless standards. The ambition is for the MDP design to be inherently deterministic. To achieve this, PREDICT-6G will develop an AI-driven Multi-stakeholder Inter-domain Control-Plane (AICP) for the provisioning of deterministic network paths to support time sensitive services as requested by end-customers and with different scaling ambitions, e.g., from the network in a single vehicle to a large, geographically dispersed network. This requires timely monitoring and prediction of the behavior of the complete network, including identifying potential sources of quality violations and analyzing various routes of the traffic flows. These capabilities will be delivered through the PREDICT-6G AI-powered Digital Twin (DT) framework, allowing the prediction of the behavior of the end-to-end network infrastructure, and enabling anticipative control and validation of the network provisions to meet the real-world time-sensitive and reliability requirements of the running services