Journal of Jilin University(Engineering and Technology Edition) ›› 2018, Vol. 48 ›› Issue (6): 1859-1866.doi: 10.13229/j.cnki.jdxbgxb20170674

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Synchronous sleeping based energy saving strategy of reservation virtual machines in cloud data centers and its performance research

JIN Shun-fu1,2,3(),WANG Bao-shuai1,HAO Shan-shan1,JIA Xiao-guang1,HUO Zhan-qiang2()   

  1. 1. School of Information Science and Engineering, Yanshan University, Qinhuangdao 066004,China
    2. School of Computer Science and Technology, Henan Polytechnic University, Jiaozuo 454000,China
    3. Science and Technology on Communication Networks Laboratory,Shijiazhuang 050081,China
  • Received:2017-06-27 Online:2018-11-20 Published:2018-12-11

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Abstract:

With the rapid development of cloud computing, more and more people shift their workload to the cloud data centers, the energy consumption of the cloud data centers is non-negligible. In order to reduce energy consumption and achieve green cloud service, an energy saving strategy in the cloud data centers based on synchronous sleeping of the reservation virtual machines is proposed. All the Virtual Machines (VMs) are divided into two groups: the main group and the reservation group. The main group is always activated. According to the traffic load of the cloud data centers, the reservation group may be asleep or activated. Considering the cloud data centers served for the user requests with multiple tasks, a batch arrival queuing model with part servers synchronization multiple vacation is established. By using Gauss Seidel method, the steady-state distribution of the system model is derived, and the performance measures, such as the energy saving rate of system are evaluated. Numerical experiments with analysis and simulation are provided to study the system performance of the energy saving strategy in the cloud data centers based on synchronous sleeping of the reservation VMs and verify the effectiveness of the proposed strategy.

Key words: computer application, cloud data centers, partial sleep, batch arrival, Gauss Seidel method

CLC Number: 

  • TP393

Fig.1

State transition of reservation group"

Fig.2

State transition of the system"

Table 1

System parameters"

参 数 数值
主模块虚拟机的数量n/个 20
备用模块虚拟机的数量m/个 20
缓冲区容量r/个 70
用户请求规模参数θ 0.2
虚拟机服务率μ/s-1 1.0

Fig.3

Change trend for blocking probability of tasks"

Fig.4

Change trend for average response time of tasks"

Fig.5

Change trend for the energy saving rate of system"

[1] Fard S, Ahmadi M, Adabi S . A dynamic VM consolidation technique for QoS and energy consumption in cloud environment[J/OL]. Journal of Supercomputing.[ 2017- 06- 01]. .
[2] Hamee A, Khoshkbarforoushha A, Ranjan R , et al. A survey and taxonomy on energy efficient resource allocation techniques for cloud computing systems[J]. Computing, 2016,98(7):751-774.
doi: 10.1007/s00607-014-0407-8
[3] Dabbagh M, Hamdaoui B, Guizani M , et al. Toward energy-efficient cloud computing: prediction, consolidation and overcommitment[J]. IEEE Network, 2015,29(2):56-61.
doi: 10.1109/MNET.2015.7064904
[4] Li H, Zhu G, Cui C , et al. Energy-efficient migration and consolidation algorithm of virtual machines in data centers for cloud computing[J]. Computing, 2016,98(3):303-317.
doi: 10.1007/s00607-015-0467-4
[5] 张沪寅, 汪思思, 钱龙 , 等. 面向SDN数据中心网络的路径资源管理节能机制研究[J]. 小型微型计算机系统, 2017,38(4):755-760.
[6] 杨静, 周超, 彭海英 , 等. 自适应QoS感知的以太网无源光网络节能机制[J]. 重庆邮电大学学报:自然科学版, 2017,29(2):216-222.
doi: 10.3979/j.issn.1673-825X.2017.02.012
Yang Jing, Zhou Chao, Peng Hai-ying , et al. Adaptive energy saving mechanism with QoS aware in ethernet passive optical network[J]. Journal of Chongqing University of Posts and Telecommunications(Natural Science Edition), 2017,29(2):216-222.
doi: 10.3979/j.issn.1673-825X.2017.02.012
7 Zhang Hu-yin, Wang Si-si, Qian Long , et al. SDN data center networks oriented energy saving mechanism research based on the path resource management[J]. Journal of Chinese Computer Systems, 2017,38(4):755-760.
[7] Liao D, Li K, Sun G, et al. Energy and performance management in large data centers: a queuing theory perspective [C]//Proceedings of the International Conference on Computing, Networking and Communications, Garden Grove,America, 2015: 287-291.
[8] Cao J, Li K, Stojmenovic I . Optimal power allocation and load distribution for multiple heterogeneous multicore server processors across clouds and data centers[J]. IEEE Transactions on Computers, 2014,63(1):45-58.
doi: 10.1109/TC.2013.122
[9] Kuehn P J, Mashaly M . Automatic energy efficiency management of data center resources by load-dependent server activation and sleep modes[J]. Ad Hoc Networks, 2015,25(B):497-504.
doi: 10.1016/j.adhoc.2014.11.013
[10] Di S, Kondo D, Cappello F. Characterizing cloud applications on a Google date center [C]//Proceedings of the International Conference on Parallel Processing, Lyon, France, 2013: 468-473.
[11] Benson T, Akella A, Maltz D. Network traffic characteristics of data centers in the wild [C]//Proceedings of the 10th ACM SIGCOMM Conference on Internet Measurement, Melbourne, Australia, 2010: 267-280.
[12] Chen G, He W, Liu J, et al. Energy-aware server provisioning and load dispatching for connection-intensive Internet services [C]//Proceedings of the 5th USENIX Symposium on Networked Systems Design and Implementation, San Francisco, America, 2008: 337-350.
[13] 何怀文, 傅瑜 . 批量到达下的IaaS云计算中心服务性能评价[J]. 电子科技大学报, 2015,44(3):445-450.
doi: 10.3969/j.issn.1001-0548.2015.03.022
He Huai-wen, Fu Yu . Service performance evaluation of IaaS cloud computing center under batch arrivals[J]. Journal of University of Electronic Science and Technology of China, 2015,44(3):445-450.
doi: 10.3969/j.issn.1001-0548.2015.03.022
[14] Nashid Anjum M D, Wang Hong-gang . Dynamic scheduling and analysis of real time systems with multiprocessors[J]. Digital Communications and Networks, 2016(3):130-138.
doi: 10.1016/j.dcan.2016.06.004
[15] 金顺福, 姚兴华, 霍占强 . 非理想感知下动态信道绑定策略性能[J]. 吉林大学学报:工学版, 2016,46(5):1667-1674.
Jin Shun-fu, Yao Xing-hua, Huo Zhan-qiang . Performance of the dynamic channel bonding strategy with imperfect channel sensing[J]. Journal of Jilin University(Engineering and Technology Edition), 2016,46(5):1667-1674.
[16] 马子骥, 彭强, 周冰航 , 等. 基于分数时延信道模型的低复杂度信道估计方法[J]. 重庆邮电大学学报:自然科学版, 2017,29(5):611-617.
Ma Zi-ji, Peng Qiang, Zhou Bing-hang , et al. Low complexity channel estimation method based on fractional delay channel model[J]. Journal of Chongqing University of Posts and Telecommunications(Natural Science Edition), 2017,29(5):611-617.
[17] Li Rui-dong, Asaeda Hitoshi, Li Jie , et al. A distributed authentication and authorization scheme for in-network big data sharing[J]. Digital Communications and Networks, 2017(4):226-235.
[18] 戈立军, 程以泰, 张华 , 等. 基于压缩感知的非线性 OFDM 系统迭代信道估计算法[J]. 重庆邮电大学学报:自然科学版, 2016,28(5):680-685.
Ge Li-jun, Cheng Yi-tai, Zhang Hua , et al. Iterative channel estimation based on compressed sensing for nonlinearly distorted OFDM systemsl[J]. Journal of Chongqing University of Posts and Telecommunications(Natural Science Edition), 2016,28(5):680-685.
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