Interaction and Conflict Management in AI-assisted Operational Control Loops in 6G

TL;DR

This paper explores how autonomous control loops in 6G wireless networks can be managed for effective interaction and conflict resolution, proposing modules and implementation strategies to ensure coherence among AI-assisted network operations.

Contribution

It introduces ICM modules and categorizes ACLs to facilitate conflict management and interaction in AI-assisted 6G network control loops.

Findings

ICM modules improve conflict resolution among ACLs.

Categorization of ACLs aids in tailored conflict management.

Implementation with Kubernetes demonstrates practical conflict mitigation.

Abstract

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.