Design for Migration Algorithm Based on Gray Model for Ocean Big Data

Chen Zuo-cong

doi:10.12052/gdutxb.180013

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Design for Migration Algorithm Based on Gray Model for Ocean Big Data

更新时间：2026-05-27

- Design for Migration Algorithm Based on Gray Model for Ocean Big Data
- Vol. 35, Issue 3, Pages: 95-99(2018)
- 作者机构：
  
  海南热带海洋学院　海洋信息工程学院,海南,三亚,572022
- 作者简介：
- 基金信息：
- DOI：10.12052/gdutxb.180013
  CLC： TP391
- Published：2018
- 稿件说明：
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陈作聪. 基于灰色模型的海洋大数据迁移算法设计[J]. 广东工业大学学报, 2018, 35(3): 95-99.

Chen Zuo-cong. Design for Migration Algorithm Based on Gray Model for Ocean Big Data[J]. 2018, 35(3): 95-99.
陈作聪. 基于灰色模型的海洋大数据迁移算法设计[J]. 广东工业大学学报, 2018, 35(3): 95-99. DOI： 10.12052/gdutxb.180013.

Chen Zuo-cong. Design for Migration Algorithm Based on Gray Model for Ocean Big Data[J]. 2018, 35(3): 95-99. DOI： 10.12052/gdutxb.180013.

摘要

针对海洋大数据环境的数据量大和实时动态变化的特点，提出了一种基于云存储的海洋大数据迁移算法。首先，对海洋大数据进行了表示；设计了一种灰色模型的服务器负载预测算法，该算法能根据服务器历史负载信息来预测下一个时刻的负载。基于服务器的负载预测信息，提出了一种对服务器的负载进行实时迁移的数据迁移算法，通过设定最大负载阈值和最小负载阈值来实现服务器负载的均衡分配。在CloudSim环境下进行实验，实验结果表明文中方法能有效地实现海洋大数据环境的云环境的负载均衡，具有负载均衡高和负载均衡效率高的优点，与其他方法相比，具有更好的负载均衡能力。

Abstract

Aiming at the big amount of data in the big data environment and the dynamical change in time

a migration algorithm for data based on cloud memory is proposed. Firstly

the big data in ocean environment is represented; the load prediction algorithm based on the prediction of the gray model

where the algorithm can predict the load for the next time based on the historical load information. The data migration algorithm for migrating the load among the servers is proposed on the condition of the setting the smallest and biggest load threshold. In the environment of the Cloudsim

the simulated result shows this method can balance the load in the ocean big data

with the high load balance and load balance efficiency. Compared with the other methods

it has a better load balance ability.

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references

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