Virtual machine scheduling strategy based on dual-speed and work vacation mode and its parameter optimization

Shun-fu JIN; Shan-shan HAO; Bao-shuai WANG

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

您当前的位置：

首页 >

文章列表页 >

Virtual machine scheduling strategy based on dual-speed and work vacation mode and its parameter optimization

Papers | 更新时间：2024-06-05

- Virtual machine scheduling strategy based on dual-speed and work vacation mode and its parameter optimization
- Journal on Communications Vol. 38, Issue 12, Pages: 10-20(2017)
- 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：
- 基金信息：
  
  TheNationalNaturalScienceFoundationofChina(61472342);The Natural Science Foundation of Hebei Province(F2017203141)
- DOI：10.11959/j.issn.1000-436x.2017298
  CLC： TP393
- Online First：2017-12，
  
  Published：25 December 2017
- 稿件说明：
移动端阅览
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：

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).

关键词

Keywords

references

JIN X , ZHANG F , VASILAKOS A V , et al . Green data centers:a survey,perspectives,and future directions [J ] . arXiv:1608 .00687.

DUAN L , ZHAN D , HOHNERLEIN J . Optimizing cloud data center energy efficiency via dynamic prediction of CPU idle intervals [C ] // IEEE International Conference on Cloud Computing . 2015 : 985 - 988 .

LI K . Improving multicore server performance and reducing energy consumption by workload dependent dynamic power management [J ] . IEEE Transactions on Cloud Computing , 2016 , 4 ( 2 ): 122 - 137 .

WANG Y , XIE Q , AMMARI A , et al . Deriving a near-optimal power management policy using model-free reinforcement learning and Bayesian classification [C ] // IEEE Design Automation Conference . 2011 : 41 - 46 .

GAO Y , GUAN H , QI Z , et al . Quality of service aware power management for virtualized data centers [J ] . Journal of Systems Architecture , 2013 , 59 ( 5 ): 245 - 259 .

LIAO D , LI K , SUN G , et al . Energy and performance management in large data centers:a queuing theory perspective [C ] // International Conference on Computing,Networking and Communications . 2015 : 287 - 291 .

SHEN D , LUO J , DONG F , et al . Stochastic modeling of dynamic right-sizing for energy-efficiency in cloud data centers [J ] . Future Generation Computer System , 2015 , 48 ( C ): 82 - 95 .

马晓彤 , 金顺福 , 刘建平 , 等 . 认识无线电网络中的基站节能策略及纳什均衡研究 [J ] . 通信学报 , 2017 , 37 ( 7 ): 172 - 181 .

MA X T , JIN S F , LIU J P , et al . Study on energy saving strategy and Nash equilibrium of base station in cognitive radio network [J ] . Journal on Communications , 2017 , 37 ( 7 ): 172 - 181 .

CHOU C H , WONG D , BHUYAN L N . DynSleep:fine-grained power management for a latency-critical data center application [C ] // The 2016 International Symposium on Low Power Electronics and Design . 2016 : 212 - 217 .

CHEN Y L , CHANG M F , LIANG W Y , et al . Performance and energy efficient dynamic voltage and frequency scaling scheme for multicore embedded system [C ] // IEEE International Conference on Consumer Electronics . 2016 : 58 - 59 .

TIAN N , ZHANG Z G , Vacation queueing models theory and applications [M ] . Springer US , 2006 .

LATOUCHE G , RAMASWAMI V . Introduction to matrix analytic methods in stochastic modeling [M ] // Society for Industrial and Applied Mathematics . 2001 .

GREENBAUM A , . Iterative methods for solving linear systems [M ] // Society for Industrial and Applied Mathematics . 2001 .

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 .

GANDOMI A H , YANG X S , ALAVI A H . Mixed variable structural optimization using firefly algorithm [J ] . Computers＆Structures , 2011 , 89 ( 24 ): 2325 - 2336 .

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

Views

2248

下载量

CSCD

Alert me when the article has been cited

提交

Tools

Publicity Resources

Handover algorithm for space-air-ground integrated network based on location prediction model

Joint intelligent optimization of task offloading and service caching for vehicular edge computing

Website defense strategy selection method based on attack-defense game and Monte Carlo simulation

Dynamic bandwidth allocation algorithm based on transmission rate adaptation

Multi-values discrete particle swarm optimization for cross layer resource allocation in cooperative OFDMA systems

Related Author

LI Cuiran

ZHANG Zepeng

CHEN Long

XIE Jianli

Zhibin DOU

Ci HE

Qingqi PEI

Jie FENG

Related Institution

School of Electronic and Information Engineering, Lanzhou Jiaotong University

State Key Laboratory of Integrated Services Networks, Xidian University

The 54th Research Institute of China Electronics Technology Group Corporation

School of Communication and Information Engineering, Xi’an University of Posts and Telecommunications

Information Centre,Xi’an University of Posts and Telecommunications

AI问答

⁰