NetEventCause: Event-Driven Root Cause Analysis for Large Network System Without Topology
Published in IEEE Transactions on Neural Networks and Learning Systems, 2025
This article introduces NetEventCause (NEC), an event-driven, unsupervised, and nonintrusive root cause analysis algorithm designed for large-scale private cloud network systems with unknown or incomplete topologies. Addressing the limitations of existing topology-free RCA approaches, NEC learns from historical alarm events to model the occurrence patterns of diverse alarm types using a multivariate neural temporal point process. Leveraging conditional intensity predictions and attribution methods, the algorithm identifies root alarms and reconstructs anomaly transmission chains from cascading alarm events. Extensive evaluations on synthetic data and real-world datasets from the Huawei Shennong Intelligent Maintenance and Operation Center demonstrate NEC’s superior performance in alarm modeling and root cause identification.
Recommended citation: Zhaolin Yuan, Long Ma, Wenjia Wei, Xia Zhu, Mingjie Sun, Duxin Chen, Xiaojuan Ban, "NetEventCause: Event-Driven Root Cause Analysis for Large Network System Without Topology." IEEE Transactions on Neural Networks and Learning Systems, 2025.
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