A Diffusion-Based Framework for Configurable and Realistic Multi-Storage Trace Generation
Seohyun Kim, Junyoung Lee, Jongho Park, Jinhyung Koo, Sungjin Lee, Yeseong Kim
Published: 2025/9/2
Abstract
We propose DiTTO, a novel diffusion-based framework for generating realistic, precisely configurable, and diverse multi-device storage traces. Leveraging advanced diffusion tech- niques, DiTTO enables the synthesis of high-fidelity continuous traces that capture temporal dynamics and inter-device dependencies with user-defined configurations. Our experimental results demonstrate that DiTTO can generate traces with high fidelity and diversity while aligning closely with guided configurations with only 8% errors.