Interaction and Conflict Management in AI-assisted Operational Control Loops in 6G
This addresses coordination challenges in AI-assisted operational control for 6G networks, but it appears incremental as it builds on existing multi-agent and Kubernetes frameworks.
The paper tackles the problem of managing interactions and conflicts among autonomous and AI-assisted control loops in 6G networks by proposing ICM modules, and it demonstrates an implementation using Kubernetes to resolve scheduling conflicts for Pods.
This paper studies autonomous and AI-assisted control loops (ACLs) in the next generation of wireless networks in the lens of multi-agent environments. We will study the diverse interactions and conflict management among these loops. We propose "interaction and conflict management" (ICM) modules to achieve coherent, consistent and interactions among these ACLs. We introduce three categories of ACLs based on their sizes, their cooperative and competitive behaviors, and their sharing of datasets and models. These categories help to introduce conflict resolution and interaction management mechanisms for ICM. Using Kubernetes, we present an implementation of ICM to remove the conflicts in the scheduling and rescheduling of Pods for different ACLs in networks.