Resource Scheduling for Cloud Data Center Based on Data Mining in Smart Grid

Songtao Peng

doi:10.11959/j.issn.1000-0801.2015084

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Resource Scheduling for Cloud Data Center Based on Data Mining in Smart Grid

Electric power information column | 更新时间：2024-06-05

- Resource Scheduling for Cloud Data Center Based on Data Mining in Smart Grid
- Telecommunications Science Vol. 31, Issue 3, Pages: 142-147(2015)
- 作者机构：
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- DOI：10.11959/j.issn.1000-0801.2015084
  CLC：
- Published Online：2015-03，
  
  Published：20 March 2015
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Songtao Peng. Resource Scheduling for Cloud Data Center Based on Data Mining in Smart Grid[J]. Telecommunications science, 2015, 31(3): 142-147.
DOI：

Songtao Peng. Resource Scheduling for Cloud Data Center Based on Data Mining in Smart Grid[J]. Telecommunications science, 2015, 31(3): 142-147. DOI： 10.11959/j.issn.1000-0801.2015084.

摘要

随着虚拟化技术的应用，数据中心的资源利用率已经得到一定程度的提高，但是云资源通常还是根据用户提出的需求预先分配，资源利用率仍然有待提高。为了进一步改进资源利用率，云中心的实际资源需求可分为“周期资源”及“峰期资源”。“周期资源”可以通过历史规律，利用递阶成分负载模型进行分析，预测出数据中心大部分时间的资源需求；“峰期资源”主要是满足短时间内的各种高峰资源需求，这种需求应用了排队论及随机均衡算法模型并根据实际应用的需要动态启用、分配和收回资源。通过使用资源收集与分配守护进程对云中心资源需求进行规划调度实验，效果明显，从而为云中心资源利用率的提升及节能减排提供了一种有效途径。

Abstract

Since the wide use of virtual technology

the resource use rate in cloud data center has been improved effectively than ever before.However

there is still a large space for improvement due to the resources usually are pre-started and pre-allocated by the user demand rather than the actual needs.In order to allocate available resource more accurately

two algorithms were proposed to meet the needs of the daily use in most of time.The available virtual resources would be arranged according the forecast using the algorithms of hierarchical composition of loading and the peek resources needs would be dynamic allocated using the algorithms of stochastic equilibrium and queuing theory.The results of experiment via the system based upon above theories show that the solution provides a kind of very effective advanced means for the optimal use of resources and energy saves.

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references

张大华，丁辉，吴向阳等 . 面向智能电网的电力云计算架构 . 电力通信管理暨智能电网通信技术论坛论文集，北京，中国 , 2011

Zhang D H , Ding H , Wu X Y et al . Cloud computing architecture for smart grid . Proceedings of Electric Power Communication Management and Smart Grid Communications Technology Forum , Beijing,China , 2011

王利赛，杨明玉，孙月琴等 . 电力云研究综述 . 电力信息化， 2011 （ 5 ）

Wang L S , Yang M Y , Sun Y Q et al . Summary research on electric power cloud computing . Electric Power Information Technology , 2011 （ 5 ）

王鹏 . 云计算的关键技术与应用实例 . 北京：人民邮电出版社， 2010

Wang P . Examples of key techniques and application on cloud computing . Beijing : Posts and Telecom Press , 2010

徐国祥 . 统计预测和决策 . 上海：上海财经大学出版社， 2011

Xu G X . Statistical forecast and decision making . Shanghai : Shanghai University of Finance and Economics Press , 2011

陆传赉 . 排队论 . 北京：北京邮电大学出版社， 2009

Lu C L . Queuing Theory . Beijing : Beijing University of Posts and Telecommunications Press , 2009

Kalekar S P . Time series forecasting using holt-winters exponential smoothing . Kanwal Rekhi School of Information Technology Tech Rep , 2004

Dostal Z . Optimal Quadratic Programming Algorithms:With Application to Variations to Variational Inequalities . New York:Springer , 2009

Jiang Y , Perng S C , Li T , et al . ASAP:a self-adaptive prediction system for instant cloud resource demand provisioning . Proceedings of ICDM , Vancouver,Canada , 2011

杨巨龙 . 大数据技术全解 . 北京：电子工业出版社， 2014

Yang J L . Big Data Technology Entire Solution . Beijing : Publishing House of Electronics Industry , 2014

苏跃进，韩英杰 . 基于分布式电站群的智能数据分析中心建设与实践 . 电信科学， 2013 （ 11 ）: 122 ～ 126

Su Y J , Han Y J . Construction and practice of intelligent data analysis center based on distributed power plant . Telecommunications Science , 2013 （ 11 ）: 122 ～ 126

耿亮，吴燕，孟宪楠 . 电力数据挖掘在电网内部及各领域间的应用 . 电信科学， 2013 （ 11 ）: 127 ～ 130

Geng L , Wu Y , Meng X N . Application of power data mining within and between grid fields . Telecommunications Science , 2013 （ 11 ）: 127 ～ 130

赵云山，刘焕焕 . 大数据技术在电力行业的应用研究 . 电信科学， 2014 （ 1 ）: 57 ～ 62

Zhao Y S , Liu H H . Research on application of big data technique in electricity power industry . Telecommunications Science , 2014 （ 1 ）: 57 ～ 62

黄章树，刘晴晴 . 基于云计算服务模式的数据挖掘应用平台的构建 . 电信科学， 2012 （ 1 ）: 53 ～ 57

Huang Z S , Liu Q Q . Construction of data mining application platform based on the service models of cloud computing . Telecommunications Science , 2012 （ 1 ）: 53 ～ 57

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