Proceedings of the 2nd International Conference on Electronic & Mechanical Engineering and Information Technology (EMEIT 2012)

Research on Load Balance Strategy Based on Grey Prediction Theory in Cloud Storage

Authors
Yu Mao, Jie Ling
Corresponding Author
Yu Mao
Available Online September 2012.
DOI
10.2991/emeit.2012.39How to use a DOI?
Keywords
cloud storage, replica strategy, load balance, grey prediction theory
Abstract

In the HDFS cloud storage environment, the existing replica strategy is not able to adopt the optimal replica according to the current system environment dynamically, which affects the performance of the Cloud Storage system. This paper aims at the replica selection strategies in the load balancing problem, proposes a Replica Strategy based on grey prediction theory in Cloud Storage and predicts the node load rate of different replicas at a moment, selecting the minimum load node dynamically, eventually to load balance.

Copyright
© 2012, 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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Volume Title
Proceedings of the 2nd International Conference on Electronic & Mechanical Engineering and Information Technology (EMEIT 2012)
Series
Advances in Intelligent Systems Research
Publication Date
September 2012
ISBN
978-90-78677-60-4
ISSN
1951-6851
DOI
10.2991/emeit.2012.39How to use a DOI?
Copyright
© 2012, 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/).

Cite this article

TY  - CONF
AU  - Yu Mao
AU  - Jie Ling
PY  - 2012/09
DA  - 2012/09
TI  - Research on Load Balance Strategy Based on Grey Prediction Theory in Cloud Storage
BT  - Proceedings of the 2nd International Conference on Electronic & Mechanical Engineering and Information Technology (EMEIT 2012)
PB  - Atlantis Press
SP  - 199
EP  - 203
SN  - 1951-6851
UR  - https://doi.org/10.2991/emeit.2012.39
DO  - 10.2991/emeit.2012.39
ID  - Mao2012/09
ER  -