Multivariate workload and resource prediction in cloud computing using CNN and GRU by attention mechanism
Top Cited Papers
- 4 September 2022
- journal article
- research article
- Published by Springer Nature in The Journal of Supercomputing
- Vol. 79 (3) , 3437-3470
Abstract
No abstract availableKeywords
This publication has 58 references indexed in Scilit:
- A sequential pattern mining model for application workload prediction in cloud environmentJournal of Network and Computer Applications, 2018
- Cloud computing for genomic data analysis and collaborationNature Reviews Genetics, 2018
- Energy efficient temporal load aware resource allocation in cloud computing datacentersJournal of Cloud Computing, 2018
- How strong is the causal relationship between globalization and energy consumption in developed economies? A country-specific time-series and panel analysisApplied Economics, 2017
- A hybrid heuristic-based tuned support vector regression model for cloud load predictionThe Journal of Supercomputing, 2015
- Workload Prediction Using ARIMA Model and Its Impact on Cloud Applications’ QoSIEEE Transactions on Cloud Computing, 2014
- From Correlation to Granger CausalitySSRN Electronic Journal, 2011
- Causality detection based on information-theoretic approaches in time series analysisPhysics Reports, 2007
- A comparative study of neural network and Box-Jenkins ARIMA modeling in time series predictionComputers & Industrial Engineering, 2002
- Spatio-temporal prediction of snow water equivalent using the Kalman filterComputational Statistics & Data Analysis, 1996