Prediction-Based Elastic Load Balancing Mechanism in Cloud Environment

DOI

10.2991/iccia-16.2016.60How to use a DOI?

Keywords

Elastic load balancing; Cloud computing; Machine learning.

Abstract

An elastic load balancing mechanism in cloud computing environment is studied in this paper. The mechanism that uses kNN (k-Nearest Neighbors) and Naive Bayes classification algorithms in machine learning can effectively solve the problem of resource allocation lag by predicting the future load trend on the basis of analysis and study of historical data. And taking into account the cross regional nature of the cloud computing environment, applications will be deployed to the computing nodes closer to the user to reduce user access time. Finally, we verify the feasibility and effectiveness of the proposed mechanism through some experiments.

Copyright

© 2016, 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  - Xin Yang
AU  - Xiuquan Qiao
PY  - 2016/09
DA  - 2016/09
TI  - Prediction-Based Elastic Load Balancing Mechanism in Cloud Environment
BT  - Proceedings of the 2016 International Conference on Computer Engineering, Information Science & Application Technology (ICCIA 2016)
PB  - Atlantis Press
SP  - 324
EP  - 329
SN  - 2352-538X
UR  - https://doi.org/10.2991/iccia-16.2016.60
DO  - 10.2991/iccia-16.2016.60
ID  - Yang2016/09
ER  -