A Diffusion-Based Framework for Configurable and Realistic Multi-Storage Trace Generation
This work addresses the need for synthetic storage traces in system testing and simulation, offering a configurable solution for researchers and engineers, though it appears incremental as it applies diffusion techniques to a specific domain.
The paper tackled the problem of generating realistic and configurable multi-device storage traces, proposing DiTTO, a diffusion-based framework that achieved high fidelity and diversity with only 8% errors in alignment with user-defined configurations.
We propose DiTTO, a novel diffusion-based framework for generating realistic, precisely configurable, and diverse multi-device storage traces. Leveraging advanced diffusion techniques, 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.