Auto-Scaling Web Application in Docker Based on Gray Prediction

DOI

10.2991/ncce-18.2018.29How to use a DOI?

Keywords

Docker, web application, dynamic weighted average method, gray prediction.

Abstract

The on-demand use and the elastic scaling feature of cloud computing make more and more companies deploy web applications on cloud platforms. True elasticity and cost-effectiveness in the pay-per-use cloud business model, however, have not yet been achieved. To address this challenge, we propose an algorithm which can auto-scaling web application in docker. We use docker container technology to deploy web applications and add or delete docker containers to adjust web applications resources. The use of dynamic weighted average method to calculate the weight of web application indicators combined with the gray prediction algorithm to predict container scale up and down. Experimental results show that the algorithm in this paper can achieve better results.

Copyright

© 2018, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Shuangyan Wu
AU  - Dong Zhang
AU  - Bingheng Yan
AU  - Feng Guo
AU  - Dongpu Sheng
PY  - 2018/05
DA  - 2018/05
TI  - Auto-Scaling Web Application in Docker Based on Gray Prediction
BT  - Proceedings of the 2018 International Conference on Network, Communication, Computer Engineering (NCCE 2018)
PB  - Atlantis Press
SP  - 169
EP  - 174
SN  - 1951-6851
UR  - https://doi.org/10.2991/ncce-18.2018.29
DO  - 10.2991/ncce-18.2018.29
ID  - Wu2018/05
ER  -