Hybrid Orchestration of Edge AI and Microservices via Graph-based Self-Imitation Learning

ArXi:2603.06669v1 Announce Type: cross Modern edge AI applications increasingly rely on microservice architectures that integrate both AI services and conventional microservices into complex request chains with stringent latency requirements. Effectively orchestrating these heterogeneous services is crucial for ensuring low-latency performance, yet remains challenging due to their diverse resource demands and strong operational interdependencies under resource-constrained edge environments.