@inproceedings{2d80d4bee3c4438c95a7081ef95e264c,
title = "Predicting host CPU utilization in cloud computing using recurrent neural networks",
abstract = "One of the major challenges facing cloud computing is to accurately predict future resource usage for future demands. Cloud resource consumption is constantly changing, which makes it difficult for forecasting algorithms to produce accurate predictions. This motivates the research presented in this paper which aims to predict host machines CPU consumption for a single time-step and multiple time-steps into the future. This research implements a Recurrent Neural Network to predict CPU utilisation, due to their ability to retain information and accurately make predictions for time series problems, making it a promising candidate to predict CPU utilization with greater accuracy when compared to traditional approaches.",
keywords = "Cloud Computing, CPU Prediction, Neural Networks",
author = "Martin Duggan and Karl Mason and Jim Duggan and Enda Howley and Enda Barrett",
note = "Publisher Copyright: {\textcopyright} 2017 Infonomics Society.; 12th International Conference for Internet Technology and Secured Transactions, ICITST 2017 ; Conference date: 11-12-2017 Through 14-12-2017",
year = "2018",
month = may,
day = "8",
doi = "10.23919/ICITST.2017.8356348",
language = "English",
series = "2017 12th International Conference for Internet Technology and Secured Transactions, ICITST 2017",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "67--72",
booktitle = "2017 12th International Conference for Internet Technology and Secured Transactions, ICITST 2017",
}