电信科学 ›› 2015, Vol. 31 ›› Issue (3): 89-97.doi: 10.11959/j.issn.1000-0801.2015073

• 研究与开发 • 上一篇    下一篇

大数据网络服务器群智能伸缩机制与架构研究

鞠洪尧   

  1. 浙江纺织服装职业技术学院 宁波 315211
  • 出版日期:2015-03-15 发布日期:2017-02-23
  • 基金资助:
    科技部创新基金资助项目;宁波市智团创业基金资助项目

Research on Smart Scaling Mechanism and Structure for Big Data Network Server Groups

Hongyao Ju   

  1. Zhejiang Textile&Fashion College,Ningbo 315211,China
  • Online:2015-03-15 Published:2017-02-23
  • Supported by:
    The Innovation Fund for Technology Based Firms of the Chinese Ministry of Science and Technology;Ningbo Intelligence Group Entrepreneurship Project

摘要:

阐述了大数据网络服务器群智能伸缩原理及架构的构建过程,对大数据网络服务器群智能伸缩涉及的关键技术做了深入的探讨。围绕服务器群工作负载监测、服务器数量智能增减控制以及访问负载调度等关键技术展开研究,给出了大数据网络服务器群智能伸缩机制和实现方法,为大数据网络智能伸缩及有效节能提供了技术支持。依据所提的构建方法和关键技术,给出了大数据网络服务器群智能伸缩模型。

关键词: 大数据网络, 服务器群, 智能伸缩, 负载调度

Abstract:

The principle and construction of the structure of smart telescopic on big data network server groups were elaborated.The key technologies involved in the smart scaling of big data network server groups were discussed.After investigating key technologies,including the monitoring of the workload of the server group,the smart control of the number of servers,and the scheduling of access loads,the principle and realization method for the smart scaling of big data network server groups were proposed and technical supports were provided for the smart scaling and effective energy conservation of big data network server groups.According to the proposed construction method and key technologies,a smart scaling model for big data network server groups was provided as well.

Key words: big data network, server group, smart scaling, load scheduling

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