融合双速率和工作休眠的虚拟机调度策略及参数优化

金顺福; 郝闪闪; 王宝帅

doi:10.11959/j.issn.1000-436x.2017298

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融合双速率和工作休眠的虚拟机调度策略及参数优化

学术论文 | 更新时间：2024-06-05

- 融合双速率和工作休眠的虚拟机调度策略及参数优化
- Virtual machine scheduling strategy based on dual-speed and work vacation mode and its parameter optimization
- 通信学报 2017年38卷第12期页码：10-20
- 作者机构：
  
  1. 燕山大学信息科学与工程学院，河北秦皇岛 066004
  2. 河北省计算机虚拟技术与系统集成重点实验室，河北秦皇岛 066004
  3. 河北省软件工程重点实验室,河北秦皇岛 066004
- 作者简介：
  
  [ "金顺福（1966-），女，朝鲜族，内蒙古满洲里人，燕山大学教授、博士生导师，主要研究方向为网络资源分配与优化、排队论研究与应用等。" ]
  [ "郝闪闪（1993-），女，河北邢台人，燕山大学硕士生，主要研究方向为云数据中心的节能策略与性能优化。" ]
  [ "王宝帅（1993-），男，河北保定人，燕山大学硕士生，主要研究方向为网络资源分配与优化。" ]
- 基金信息：
  
  国家自然科学基金资助项目(61472342);河北省自然科学基金资助项目(F2017203141)
- DOI：10.11959/j.issn.1000-436x.2017298
  中图分类号： TP393
- 网络出版日期：2017-12，
  
  纸质出版日期：2017-12-25
- 稿件说明：
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金顺福, 郝闪闪, 王宝帅. 融合双速率和工作休眠的虚拟机调度策略及参数优化[J]. 通信学报, 2017,38(12):10-20.

Shun-fu JIN, Shan-shan HAO, Bao-shuai WANG. Virtual machine scheduling strategy based on dual-speed and work vacation mode and its parameter optimization[J]. Journal on communications, 2017, 38(12): 10-20.
金顺福, 郝闪闪, 王宝帅. 融合双速率和工作休眠的虚拟机调度策略及参数优化[J]. 通信学报, 2017,38(12):10-20. DOI： 10.11959/j.issn.1000-436x.2017298.

Shun-fu JIN, Shan-shan HAO, Bao-shuai WANG. Virtual machine scheduling strategy based on dual-speed and work vacation mode and its parameter optimization[J]. Journal on communications, 2017, 38(12): 10-20. DOI： 10.11959/j.issn.1000-436x.2017298.

摘要

受日趋严格的环境标准的影响，高能耗和高污染成为制约云数据中心发展的重要因素。在保证云数据中心服务质量的前提下，应用动态电压调整技术，引入同步多重工作休眠模式，提出一种新型的虚拟机调度策略。通过构建具有自适应服务率和多重工作休假的二维连续时间马尔可夫（Markov）随机模型，运用矩阵几何解方法，从系统节能水平和用户请求平均延迟等方面评估虚拟机调度策略的性能。综合理论分析结果和仿真统计结果，验证虚拟机调度策略的有效性。从经济学角度出发，建立系统效用函数，改进萤火虫智能优化算法，给出工作休眠参数的优化方案，实现系统响应性能和节能效果之间的合理平衡。

Abstract

Due to the increasingly strict environmental standards

high pollution and high energy consumption have become the significant factors restricting the development of cloud data centers (CDC).Under the premise of guaranteeing the quality of service (QoS) of CDC

dynamic power management (DPM) technology was applied

synchronous multiple working sleep mode was introduced

and a novel virtual machine (VM) scheduling strategy was proposed.By establishing a two-dimensional continuous-time Markov stochastic model with adaptive service rate and synchronous multiple work vacations

and using the method of a matrix geometric solution

the performance of the VM scheduling strategy was evaluated in terms of energy saving level and average delay of requests.Numerical results with analysis and simulation verify the energy saving effectiveness of the VM scheduling strategy.In order to achieve a reasonable balance between the response performance and the energy-saving effect

a system utility function was constructed from the perspective of economics and design a researching algorithm of the sleep parameter based on the firefly algorithm(FA).

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Keywords

references

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陈赓 , 夏玮玮 , 沈连丰 . 基于传输速率自适应的动态带宽分配算法 [J ] . 通信学报 , 2014 , 35 ( 5 ): 25 - 32 .

CHEN G , XIA W W , SHEN L F . Dynamic bandwidth allocation algorithm based on transmission rate adaptation [J ] . Journal on Communications , 2014 , 35 ( 5 ): 25 - 32 .

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YU S , ZHU S , MA Y , et al . Enhancing firefly algorithm using generalized opposition-based learning [J ] . Computing , 2015 , 97 ( 7 ): 741 - 754 .

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