H. Jing et al., "LSTM-Based Service Migration for Pervasive Cloud Computing," 2018 IEEE International Conference on Internet of Things (iThings) and IEEE Green Computing and Communications (GreenCom) and IEEE Cyber, Physical and Social Computing (CPSCom) and IEEE Smart Data (SmartData), Halifax, NS, Canada, 2018, pp. 1835-1840. doi: 10.1109/Cybermatics_2018.2018.00305
LSTM-based service migration for pervasive cloud computing
|Author:||Jing, Haifeng1; Zhang, Yafei2; Zhou, Jiehan3;|
1School of Computer and Communication Engineering, China University of Petroleum Qingdao, China
2Department of Software Engineering, China University of Petroleum Qingdao, China
3University of Oulu Finland
4Engineering Technology Research Institute, Huabei Oilfield Company, PetroChina Renqiu, China
|Online Access:||PDF Full Text (PDF, 0.6 MB)|
|Persistent link:|| http://urn.fi/urn:nbn:fi-fe202003238887
Institute of Electrical and Electronics Engineers,
|Publish Date:|| 2020-03-23
Service migration in pervasive cloud computing is important for leveraging cloud resources to execute mobile applications effectively and efficiently. This paper proposes a LSTM (long and short-term memory model) based service migration approach for pervasive cloud computing, i.e., LSTM4PCC, which supports an accurate prediction of cloud resources. LSTM4PCC makes a prediction for cloud resource availability with a LSTM network and establishes a service migration mechanism in order to optimize service executions. We evaluate LSTM4PCC and compare it with the ARIMA (AutoRegressive Integrated Moving Average) approach in terms of prediction accuracy. The results show that LSTM4PCC performs better than ARIMA.
|Pages:||1835 - 1840|
Proceedings IEEE 2018 International Congress on Cybermatics - 2018 IEEE International Conference on Internet of Things (iThings) and IEEE Green Computing and Communications (GreenCom) and IEEE Cyber, Physical and Social Computing (CPSCom) and IEEE Smart Data (SmartData)
IEEE International Conference on Computer and Information Technology
|Type of Publication:||
A4 Article in conference proceedings
|Field of Science:||
213 Electronic, automation and communications engineering, electronics
This research is supported by National Natural Science Foundation of China (No. 61309024), the Program on Innovation Method Fund of China (Grant No. 2015010300), the Key Research Program of Shandong Province (No. 2017GGX10140) and also supported by Fundamental Research Funds for the Central Universities.
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