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Agentic Cross-Layer Mobility Management for Reliable 6G IoT Networks

Fulltext:


Authors:

Hossein Fotouhi, Maryam Vahabi

Research group:

Data Communication

Publication Type:

Conference/Workshop Paper

Venue:

International Conference on Collaborative Technologies and Data Science for Smart City Applications

Abstract

Future 6G IoT smart environments will comprise large populations of mobile cyber-physical entities operating under stringent reliability and latency requirements. Unlike traditional static IoT deployments, mobility becomes an intrinsic system property that continuously alters network topology, communication quality, and resource availability. Consequently, maintaining reliable and deterministic communication requires the coordinated adaptation of localization, routing, handover, and scheduling mechanisms. However, existing mobility-management approaches remain largely reactive and typically optimize these functions independently, limiting their ability to support mobility-intensive industrial environments. This paper presents an Agentic Mobility Management for 6G IoT networks (AMM-6GIoT), which is a hierarchical agentic cross-layer orchestration framework for deterministic IoT communication systems. The proposed architecture jointly coordinates mobility perception, cooperative localization, proactive handover, routing adaptation, and mobility-aware TSCH scheduling across mobile, edge, and cloud layers. Unlike conventional reactive solutions, AMM-6GIoT formulates mobility support as a coupled orchestration problem spanning multiple communication layers and temporal scales. A representative industrial smart-environment use case is further discussed to illustrate the orchestration challenges of future mobility-intensive IoT systems.

Bibtex

@inproceedings{Fotouhi7473,
author = {Hossein Fotouhi and Maryam Vahabi},
title = {Agentic Cross-Layer Mobility Management for Reliable 6G IoT Networks},
month = {November},
year = {2026},
booktitle = {International Conference on Collaborative Technologies and Data Science for Smart City Applications},
url = {http://www.es.mdu.se/publications/7473-}
}