Autonomic Workload Performance Modeling for Large-Scale Databases and Data Warehouses Through Deep Belief Network With Data Augmentation Using Conditional Generative Adversarial Networks

Autonomic Workload Performance Modeling for Large-Scale Databases and Data Warehouses Through Deep Belief Network With Data Augmentation Using Conditional Generative Adversarial Networks

Databases and warehouses are experiencing workload of different types such as Decision Support System (DSS), Online Transaction Processing (OLTP) and Mixed workloads. Handling variety of workload in autonomic systems is a critical task. After self-configuring the workload, the next challenge is work...

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Bibliographic Details
Main Authors: Nusrat Shaheen, Basit Raza, Ahmad Raza Shahid, Ahmad Kamran Malik
Format: Article
Language:English
Published: IEEE 2021-01-01
Series:IEEE Access
Subjects:
Autonomic computing
generative adversarial networks
stacked genetic algorithm
deep belief network
large-scale data repositories
Online Access:https://ieeexplore.ieee.org/document/9478861/

Internet

https://ieeexplore.ieee.org/document/9478861/

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