基于利益相关视角的多维QoS云资源调度方法

苏命峰; 王国军; 李仁发

doi:10.11959/j.issn.1000-436x.2019113

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基于利益相关视角的多维QoS云资源调度方法

学术论文 | 更新时间：2024-06-05

- 基于利益相关视角的多维QoS云资源调度方法
- Multidimensional QoS cloud computing resource scheduling method based on stakeholder perspective
- 通信学报 2019年40卷第6期页码：102-115
- 作者机构：
  
  1. 中南大学计算机学院,湖南长沙 410083
  2. 广州大学计算机科学与网络工程学院，广东广州510006
  3. 湖南大学信息科学与工程学院，湖南长沙 410082
- 作者简介：
  
  [ "苏命峰（1980- ），男，湖南宁乡人，中南大学博士生，主要研究方向为云计算、边缘计算、云-端协同计算等。" ]
  [ "王国军（1970- ），男，湖南长沙人，博士，广州大学教授、博士生导师，主要研究方向为云计算、边缘计算、云-端协同计算等。" ]
  [ "李仁发（1957- ），男，湖南宜章人，博士，湖南大学教授、博士生导师，主要研究方向为云计算、嵌入式系统、无线传感网等。" ]
- 基金信息：
  
  国家自然科学基金资助项目(61632009);国家自然科学基金资助项目(61472451);国家自然科学基金资助项目(61672217);湖南省自然科学基金资助项目(2019JJ70057);广东省自然科学基金资助项目(2017A030308006);广东省高等教育高层次人才基金资助项目(2016ZJ01);中南大学中央高校基本科研业务费专项资金基金资助项目(2018zzts180)
- DOI：10.11959/j.issn.1000-436x.2019113
  中图分类号： TP393
- 网络出版日期：2019-06，
  
  纸质出版日期：2019-06-25
- 稿件说明：
移动端阅览
苏命峰, 王国军, 李仁发. 基于利益相关视角的多维QoS云资源调度方法[J]. 通信学报, 2019,40(6):102-115.

Mingfeng SU, Guojun WANG, Renfa LI. Multidimensional QoS cloud computing resource scheduling method based on stakeholder perspective[J]. Journal on communications, 2019, 40(6): 102-115.
苏命峰, 王国军, 李仁发. 基于利益相关视角的多维QoS云资源调度方法[J]. 通信学报, 2019,40(6):102-115. DOI： 10.11959/j.issn.1000-436x.2019113.

Mingfeng SU, Guojun WANG, Renfa LI. Multidimensional QoS cloud computing resource scheduling method based on stakeholder perspective[J]. Journal on communications, 2019, 40(6): 102-115. DOI： 10.11959/j.issn.1000-436x.2019113.

摘要

基于云用户和云服务提供商的利益相关视角，以低计算成本（如能耗、经济成本和系统可用性等）满足云用户高QoS需求（如任务执行时间和任务最终完成时间），设计多维QoS云计算体系结构，构建多维QoS云资源调度模型，面向二级云资源调度，提出采用多重Greedy算法思想的MQoS云资源调度算法。实验结果表明，在具有无后效性的4种云计算应用场景下，MQoS云资源调度算法相比FIFO云资源调度算法、M2EC多维能耗虚拟机调度算法，其多维QoS度总体提升206.42%~228.99%、34.26%~56.93%，其云数据中心负载均衡差平均总体降低0.48~0.49、0.20~0.27。

Abstract

A multidimensional cloud computing architecture is designed and a multidimensional cloud resource scheduling model is constructed based on the stakeholder perspective of cloud users and cloud service providers to meet the high QoS requirements of cloud users (such as task execution time and task completion time) with low computing costs (such as energy consumption

economic costs and system availability).For the second-level cloud resource scheduling

an MQoS cloud resource scheduling algorithm based on multiple Greedy algorithm is proposed.The experimental results show that under the four cloud computing application scenarios with no aftereffects

the MQoS cloud resource scheduling algorithm has an overall increase of 206.42%~228.99% and 34.26%~56.93 in terms of multidimensional QoS degree compared with FIFO and M2EC algorithms.It has an average overall reduction of 0.48~0.49 and 0.20~0.27 in terms of cloud data center load balance difference.

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references

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