High-Efficiency Cloud Data Center System Design for Business Workloads

HUANG Qing; LUO Zhi-min; LI Jie

doi:10.3969/j.issn.2096-6091.2023.15.007

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High-Efficiency Cloud Data Center System Design for Business Workloads

CORRESPONDENCE | 更新时间：2025-03-26

- High-Efficiency Cloud Data Center System Design for Business Workloads
- New Generation of Information Technology Vol. 6, Issue 15, Pages: 32-38(2023)
- 作者机构：
  
  1.广州市数字政府运营中心，广东广州 511348
  2.中国移动通信集团广东有限公司广州分公司，广东广州 510000
  3.暨南大学信息科学技术学院，广东广州 510632
- 作者简介：
- 基金信息：
- DOI：10.3969/j.issn.2096-6091.2023.15.007
  CLC： TP39
- Accepted：2023-09-21，
  
  Published：15 August 2023
- 稿件说明：
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黄庆, 罗志敏, 李杰. 面向业务负载的高效能云数据中心系统设计[J]. 新一代信息技术, 2023, 6(15): 32-38

HUANG Qing, LUO Zhi-min, LI Jie. High-Efficiency Cloud Data Center System Design for Business Workloads[J]. New Generation of Information Technology, 2023, 6(15): 32-38
黄庆, 罗志敏, 李杰. 面向业务负载的高效能云数据中心系统设计[J]. 新一代信息技术, 2023, 6(15): 32-38 DOI： 10.3969/j.issn.2096-6091.2023.15.007.

HUANG Qing, LUO Zhi-min, LI Jie. High-Efficiency Cloud Data Center System Design for Business Workloads[J]. New Generation of Information Technology, 2023, 6(15): 32-38 DOI： 10.3969/j.issn.2096-6091.2023.15.007.

摘要

云数据中心不合理的业务负载调度和资源分配不仅会导致硬件资源利用率低，而且会引起IT设备的局部热点，这会降低IT设备的可靠性，同时增加云数据中心制冷系统的能量消耗。本文设计了一种面向业务负载的高效能云数据中心系统。该系统统筹管理IT设备、制冷设备及供配电设备，构建云数据中心的能耗模型，通过合理的业务负载调度和资源管理，在有限的云数据中心资源下，提高IT设备的资源利用率并降低云数据中心的能量消耗。

Abstract

Unreasonable business workload scheduling and resource allocation in cloud data centers not only lead to low hardware resource utilization but also cause local hotspots in IT equipment

which can reduce the reliability of IT equipment and increase the energy consumption of the cooling system in cloud data centers. In this paper

we design a high-efficiency cloud data center system for business workload. The system integrates the management of IT equipment

cooling equipment

and power supply and distribution equipment

builds a power consumption model for cloud data centers

improves the resource utilization of IT equipment

and reduces the energy consumption of cloud data centers under the limited cloud data center resources through reasonable business workload scheduling and resource management.

关键词

Keywords

references

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