TRACK-Plus: Optimizing Artificial Neural Networks for Hybrid Anomaly Detection in Data Streaming Systems

TRACK-Plus: Optimizing Artificial Neural Networks for Hybrid Anomaly Detection in Data Streaming Systems

Software applications can feature intrinsic variability in their execution time due to interference from other applications or software contention from other users, which may lead to unexpectedly long running times and anomalous performance. There is thus a need for effective automated performance a...

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Bibliographic Details
Main Authors: Ahmad Alnafessah, Giuliano Casale
Format: Article
Language:English
Published: IEEE 2020-01-01
Series:IEEE Access
Subjects:
Apache Spark
artificial intelligence
big data
machine learning
neural networks
performance anomalies
Online Access:https://ieeexplore.ieee.org/document/9163089/

Internet

https://ieeexplore.ieee.org/document/9163089/

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