论文标题
实施基于ML的故障探测器
Towards Implementing ML-Based Failure Detectors
论文作者
论文摘要
大多数现有的故障检测算法都取决于统计方法，很少使用机器学习（ML）。本文探讨了ML在失败检测领域中的生存能力：是否可以实现基于ML的检测器来实现令人满意的服务质量？我们实施了使用基本的长期短期内存神经网络算法的原型，并使用真实痕迹研究其行为。尽管ML模型的计算时间相对较长，但我们的原型在准确性和检测时间方面表现良好。
Most existing failure detection algorithms rely on statistical methods, and very few use machine learning (ML). This paper explores the viability of ML in the field of failure detection: is it possible to implement an ML-based detector that achieves a satisfactory quality of service? We implement a prototype that uses a basic long short-term memory neural network algorithm, and study its behavior with real traces. Although ML model has comparatively longer computing time, our prototype performs well in terms of accuracy and detection time.
