5 papers
InfraBench: Evaluating Infrastructure Agents Across Layers, Lifecycle, and Risk
Yuan Gao, Zeren Yang, Junnan Li +6
Managing modern computing infrastructure has become a steadily harder problem due to the ever-increasing complexity. Recent advances in AI agents create a timely opportunity to aut…
Don't Let AI Agents YOLO Your Files: Information and Control in Agent-Native Filesystems
Shawn Wanxiang Zhong, Junxuan Liao, Jing Liu +3
AI coding agents regularly misuse their filesystem access, causing data corruption, loss, and leakage. We conduct the first systematic study of this problem through an analysis of…
StorageXTuner: An LLM Agent-Driven Automatic Tuning Framework for Heterogeneous Storage Systems
Qi Lin, Zhenyu Zhang, Viraj Thakkar +3
Automatically configuring storage systems is hard: parameter spaces are large and conditions vary across workloads, deployments, and versions. Heuristic and ML tuners are often sys…
On Fault Tolerance of Data Storage Systems: A Holistic Perspective
Mai Zheng, Duo Zhang, Ahmed Dajani
Data storage systems serve as the foundation of digital society. The enormous data generated by people on a daily basis make the fault tolerance of data storage systems increasingl…
Revisiting Computational Storage for Data Integrity and Security
Chao Shi, Anthony Manschula, Tabassum Mahmud +6
The idea of computational storage device (CSD) has come a long way since at least 1990s [1], [2]. By embedding computing resources within storage devices, CSDs could potentially of…