A Peak Prediction Method for Subflow in Hybrid Data Flow
Joint Authors
Wang, Pengwei
Zhang, Zhaohui
Liu, Qiuwen
Chen, Ligong
Source
Issue
Vol. 2020, Issue 2020 (31 Dec. 2020), pp.1-13, 13 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2020-02-14
Country of Publication
Egypt
No. of Pages
13
Main Subjects
Abstract EN
Subflow prediction is required in resource active elastic scaling, but the existing single flow prediction methods cannot accurately predict the peak variation of subflow in hybrid data flow.
These do not consider the correlation between subflows.
The difficulty is that it is hard to calculate the correlation between different data flows in hybrid data flow.
In order to solve this problem, this paper proposes a new method DCCSPP (subflow peak prediction of hybrid data flow based on delay correlation coefficients) to predict the peak value of hybrid data flow.
Firstly, we establish a delay correlation coefficient model based on the sliding time window to determine the delay time and delay correlation coefficient.
Next, based on the model, a hybrid data flow subflow peak prediction model and algorithm are established to achieve accurate peak prediction of subflow.
Experiments show that our prediction model has achieved better results.
Compared with LSTM, our method has decreased the MAE about 18.36% and RMSE 13.50%.
Compared with linear regression, MAE and RMSE are decreased by 27.12% and 25.58%, respectively.
American Psychological Association (APA)
Zhang, Zhaohui& Liu, Qiuwen& Chen, Ligong& Wang, Pengwei. 2020. A Peak Prediction Method for Subflow in Hybrid Data Flow. Scientific Programming،Vol. 2020, no. 2020, pp.1-13.
https://search.emarefa.net/detail/BIM-1208991
Modern Language Association (MLA)
Zhang, Zhaohui…[et al.]. A Peak Prediction Method for Subflow in Hybrid Data Flow. Scientific Programming No. 2020 (2020), pp.1-13.
https://search.emarefa.net/detail/BIM-1208991
American Medical Association (AMA)
Zhang, Zhaohui& Liu, Qiuwen& Chen, Ligong& Wang, Pengwei. A Peak Prediction Method for Subflow in Hybrid Data Flow. Scientific Programming. 2020. Vol. 2020, no. 2020, pp.1-13.
https://search.emarefa.net/detail/BIM-1208991
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1208991