HotSpot: Anomaly Localization for Additive KPIs With Multi-Dimensional Attributes

HotSpot: Anomaly Localization for Additive KPIs With Multi-Dimensional Attributes

Additive key performance indicators (KPIs) (such as page view (PV), revenue, and error count) with multi-dimensional attributes (such as ISP, Province, and DataCenter) are common and important in monitoring metrics in Internet companies. When an anomaly happens to an overall KPI, it is critical but...

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Bibliographic Details
Main Authors: Yongqian Sun, Youjian Zhao, Ya Su, Dapeng Liu, Xiaohui Nie, Yuan Meng, Shiwen Cheng, Dan Pei, Shenglin Zhang, Xianping Qu, Xuanyou Guo
Format: Article
Language:English
Published: IEEE 2018-01-01
Series:IEEE Access
Subjects:
Anomaly localization
multi-dimensional attributes
huge search space
potential score
Monte Carlo Tree Search (MTCS)
hierarchical pruning
Online Access:https://ieeexplore.ieee.org/document/8288614/

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https://ieeexplore.ieee.org/document/8288614/

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