.png){kind=icon}
.png){kind=icon}
Return
CNFP: Optimizing Cloud-Native Network Function placement with diffusion models on the cloud continuum
.png){kind=icon}
PRE
AI
DOI：10.1016/j.comnet.2026.112321.png)
.png){kind=icon}
Original request for help.png){kind=icon}
Share.png){kind=icon}
Save
Abstract
En 中文
• A diffusion model based solver is introduced for Cloud-Native Network Function (CNF) placement across the Cloud-Continuum. • CNF placement is modeled as a conditional generative process driven by topology, resources, and service demands. • Results show competitive placement quality with substantially lower inference time than exact optimization on many instances.
Keywords:
CNF placement
diffusion models
cloud continuum
network functions
optimization