Edge Orchestration Framework for AI-assisted Link Failure Forecasting and Recovery

A comprehensive orchestration framework designed for edge computing scenarios is presented. The framework includes (i) a telemetry collector gathering data from both computing and programmable packet-optical network elements; (ii) a Service Level Agreement (SLA) broker processing telemetry data and enforcing configurations at the network, computing and/or application level; (iii) a lightweight Software Defined Networking (SDN) controller designed for low-latency operations over wired-wireless networks including Flying Ad Hoc Networks (FANETs); (iv) a Kubernetes scheduler for pod relocation; and (v) an Application API module to trigger adaptations at the application level. In this paper, first implementations of an AI-empowered SLA Broker and of a lightweight SDN Controller are presented, showing the capability to dynamically forecast critical link degradations and successfully recover adequate network conditions without affecting the service level.