基于灰色模型的海洋大数据迁移算法设计

陈作聪

doi:10.12052/gdutxb.180013

欢迎来到能源电力期刊网！

English Version 期刊登录

您当前的位置：

首页 >

文章列表页 >

基于灰色模型的海洋大数据迁移算法设计

综合研究 | 更新时间：2026-05-27

- 基于灰色模型的海洋大数据迁移算法设计
- Design for Migration Algorithm Based on Gray Model for Ocean Big Data
- 广东工业大学学报 2018年35卷第3期页码：95-99
- 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：
  
  陈作聪(1975–)，男，教授，主要研究方向为无线网络技术、大数据等
- 基金信息：
  
  海南省重大科技计划项目(ZDKJ2016021)
- DOI：10.12052/gdutxb.180013
  中图分类号： TP391
- 纸质出版：2018
- 稿件说明：
移动端阅览
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.

关键词

Keywords

references

ARMBRUST M, FOX A, GRIFFITH R, et al. Above the clouds: a Berkeley view of cloud computing, UCB/EECS-2009-28[R]. Springfield, USA: University of California, Berkely. Electrical Engineering and Computing Science Department, 2009.

LI P W, GE W Y. Research on dynamic deployment for virtual machine in cloud computing [J]. Computer Measurement Control, 2013, 21(5): 1374-1376.

HUANG H J, CUI Z M. Heuricstic method of independent virtual machine migration based on load fluctuaion forecasting [J]. Computer Application and Software, 2014, 8(31): 20-24.

WU H S, WANG C J, XIE J Y. TeraPELB-an algorithm of prediction-based elastic load balancing in cloud computing [J]. Journal of System Simulantion, 2013, 8(25): 1751-1765.

ZHOU W Y, CHEN H P, YANG S, et al . Resource scheduling in virtual machine cluster based on live migration of virtual machine [J ] . Journal of Huazhong University of Science Technology(Natural Science Edition), 2011, 39(1): 130-133.

GONG S W, AI H J, YUAN Y M. Research of cloud resource dynamic scheduling strategy on migration technology [J]. Computer Engineering and Applications, 2014, 50(5): 51-54.

SUN D D, LIU Q, WU Y N. Load balancing-oriented autonomous live migration framework for virtual machine [J]. Computer Science, 2014, 4(41): 80-85.

HUANG D M, DU Y L, HE Q. Migration algorithm for big marine data in hybrid cloud storage [J]. Journal of Computer Research and Development, 2014, 51(1): 199-205.

ZHANG J L, SONG J Y, YAO M. Determination of calibration interval for ATS test instruments based on the improved grey model [J]. Computer Engineering and Science, 2016, 38(3): 603-608.

PUDDU P E, AMADUZZI P L, RICCI B. Coronary heart disease incidence and competing risks: an important issue [J]. Journal of Geriatric Cardiology, 2017, 14(7): 425.

MENOTTI A, PUDDU P E, MAIANI G, et al . Age at death as a useful indicator of healthy aging at population level: a 50-year follow-up of the Italian rural areas of the seven countries study [J ] . Aging Clinical and Experimental Research, 2017, 1: 1-11.

YANG J, WANG H, LYU Z, et al . Multimedia recommendation and transmission system based on cloud platform [J ] . Future Generation Computer Systems, 2017, 70: 94-103.

LIU C, GUO Z, FENG Y, et al . CPCA: The cloud platform of complex virtual instruments system architecture [J ] . IEEE Access, 2017, 5: 4350-4360.

RANJAN S, JHA V K, PAL P. Application of emerging technologies in ERP implementation in Indian manufacturing enterprises: an exploratory analysis of strategic benefits [J]. The International Journal of Advanced Manufacturing Technology, 2017, 88(1-4): 369-380.

ZHANG K, LIU B P, HUANG D. Study on nonlinear residual grey Verhulst metering combination forecasting model of small sample based on EGA algorithm [J]. Systems Engineering Theory Practice, 2017, 37(10): 2630-2639.

浏览量

下载量

CSCD

文章被引用时，请邮件提醒。

提交

工具集

关联资源

改进的贝叶斯分类方法在电信客户流失中的研究与应用

基于路况参数的混合动力机车能量管理策略研究

多尺度对比嵌入增强的自适应入侵检测模型

基于高效时序建模的RGB-T跟踪

多套餐共享储能模式下考虑功率互济的社区联盟优化运行策略