RCAD: Real-time Collaborative Anomaly Detection System for Mobile Broadband Networks-Reference-Cited by-同舟云学术

RCAD: Real-time Collaborative Anomaly Detection System for Mobile Broadband Networks

Published:2022-08-14 Issue: Volume: Page:
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Container-title:Proceedings of the 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining
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Author:

Ahmed Azza H.¹,Riegler Michael A.²,Hicks Steven A.¹,Elmokashfi Ahmed³

Affiliation:

1. Simula Metropolitan Center for Digital Engineering & Oslo Metropolitan University, Oslo, Norway

2. Simula Metropolitan Center for Digital Engineering & University of Tromsø, Oslo, Norway

3. Simula Metropolitan Center for Digital Engineering, Oslo, Norway

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3534678.3539097

Reference40 articles.

1. Federated Learning in Edge Computing: A Systematic Survey

2. Unsupervised real-time anomaly detection for streaming data

3. Predicting High Delays in Mobile Broadband Networks

4. USAD

5. Anthony Bagnall , Jason Lines , Aaron Bostrom, James Large, and Eamonn Keogh. 2017 . The great time series classification bake off: a review and experimental evaluation of recent algorithmic advances. Data mining and knowledge discovery 31, 3 (2017), 606--660. Anthony Bagnall, Jason Lines, Aaron Bostrom, James Large, and Eamonn Keogh. 2017. The great time series classification bake off: a review and experimental evaluation of recent algorithmic advances. Data mining and knowledge discovery 31, 3 (2017), 606--660.

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