Hybrid Auto-Scaling for an Asynchronous Computationally Intensive Application
Cloud computing has developed rapidly in recent years. It enables users to access computing resources on an on-demand basis, acquiring resources when an application requires them and releasing them when they are no longer needed. This characteristic of cloud computing or elasticity as it is often re...
Main Author: | Jónsson, Arnþór Jóhann |
---|---|
Format: | Others |
Language: | English |
Published: |
KTH, Skolan för elektroteknik och datavetenskap (EECS)
2020
|
Subjects: | |
Online Access: | http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-280729 |
Similar Items
-
Scalable Hyperparameter Opimization: Combining Asynchronous Bayesian Optimization With Efficient Budget Allocation
by: Jeggle, Kai
Published: (2020) -
Robust Descriptor Learning Using Variational Auto-Encoders
by: Valavanis, Leonidas
Published: (2020) -
Hybrid Parallel Computation of OpenFOAM Solver on Multi-Core Cluster Systems
by: Liu, Yuan
Published: (2011) -
Vulnerability Assessment of Authentication Methods in a Large-Scale Computer System
by: Freimanis, Davis
Published: (2019) -
Unsupervised real-time anomaly detection on streaming data for large-scale application deployments
by: Jernbäcker, Carl
Published: (2019)