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P2 When Performance Failure Occurs in Low-Latency Storage Systems: Observation, Prediction, and Solutions

当低延迟存储系统发生性能故障:观察、预测与解决方案
ISSTA Proceedings of the 34th ACM SIGSOFT International Symposium on Software Testing and Analysis2025匹配度 1/10 · 该论文关注低延迟存储系统中的硬件故障性能退化预测与缓解,属于系统/存储领域,与用户核心方向(静态分析、Agentic 程序、LLM 与程序分析/形式化验证、浮点程序分析、贝叶斯程序分析)没有直接关联。其预测技术也未涉及 LLM/Agent 或程序分析理论。引用 0 inbox
Linxiao Bai
crossref: 2026-09-12

AI 速览

一句话:研究低延迟存储系统中硬件故障引发的性能退化,提出预测与缓解方法,在95/99分位显著提升。

硬件技术快速发展使软件成为 I/O 性能瓶颈。在低延迟存储系统中,即使采用最先进硬件,性能故障仍不可避免。本文研究此类性能故障对低延迟硬件环境下软件栈的影响,提出一种利用预测技术预判并缓解硬件故障所致性能退化的方法。通过细致观察与分析,作者给出理论洞见与实用方案,旨在提升低延迟存储系统软件性能的鲁棒性与可靠性。实验表明该方法在 95 分位和 99 分位等指标上取得显著改进,显示出现实应用中的优化潜力。

问题
低延迟存储系统中即使硬件先进,性能故障仍不可避免,并会显著影响软件栈;如何预判并缓解其导致的性能退化是核心问题。
方法
通过观察与分析性能故障行为,采用预测技术提前预判硬件故障引发的性能退化,并据此采取缓解措施。
评估
实验显示所提方法在 95th 和 99th 百分位性能指标上取得显著改进,表明其对真实应用具有优化潜力。
原文摘要(Abstract)

The rapid advancement of hardware technology has resulted in software becoming the new bottleneck in I/O performance. In low-latency storage systems, performance failures are inevitable, even with state-of-the-art hardware. This paper investigates the impact of such performance failures on the software stack within low-latency hardware environments. We propose a novel approach that leverages predictive techniques to anticipate and mitigate the performance degradation caused by hardware failures. Our method demonstrates significant improvements, particularly at the 95th and 99th percentile, showing the potential for substantial optimization in real-world applications. Through detailed observation and analysis, we aim to provide both theoretical insights and practical solutions to enhance the robustness and reliability of system software performance in low-latency storage systems.

链接与引用

DOI 原文 ·

BibTeX
@inproceedings{paperbot9611,
  title = {When Performance Failure Occurs in Low-Latency Storage Systems: Observation, Prediction, and Solutions},
  author = {Linxiao Bai},
  booktitle = {ISSTA},
  year = {2025},
  doi = {10.1145/3713081.3731744}
}