保证响应时间百分比下的云中心资源优化配置

doi:10.11959/j.issn.1000-0801.2015197

Abstract

Abstract:

In order to minimize resource provisioning cost of commercial cloud center，while guarantee percentile response time SLA，a cloud center model based on queuing theory was proposed.Resource provisioning cost was analyzed from an economic point of view，and the mathematical expressions of cloud center percentile response time were deduced.Meanwhile the minimum provisioning cost algorithm（MPCA）was developed to calculate the minimum cost of cloud center，the affect on cloud center cost by load flow，percentile response time and based response time was analyzed via a large number of experiments.The results show that with MPCA to optimized server number and speed of cloud center，it can achieve cost linear increase with increasing traffic load.

Key words: percentile response time, cloud center, resource provision, SLA

Huaiwen He. Optimal Resource Provision of Cloud Center with Guarantee Percentile Response Time[J]. Telecommunications Science, 2015, 31(8): 91-98.

Figures/Tables 6

符号	意义
λ	负载到达速率
r	完成请求所需的计算量
x	完成请求所需的时间
n	云中心服务器数量
ρ	服务器利用率，等于λ/（nμ）
s	服务器运行速率
μ	服务速率
$\hat{T}$	基准响应时间
ψ	单位能耗价格
k	能耗比例系数
γ%	响应时间百分比
$\bar{r}$	请求所需的平均计算量
$\bar{x}$	完成请求所需的平均时间
π_k	队长为k的概率
P*	服务器基本能耗
C	云中心配置总成本
C_r	能耗成本
C_e	服务器租用成本
ω	单位时间服务器租用价格
η	能耗比例因子

参数	数值
能耗比例系数k	1
能耗比例因子η	3
服务器租用价格ω/（〓·s^-1）	0.5
能耗价格ψ/（＄·kW·h ^-1）	0.06
服务器基本能耗P^*/W	2
基准响应时间 $\hat{T} / s$	0.8
响应时间百分比γ%	0.98
请求所需的平均计算量 $\bar{r} /$ 十亿级指令	1

References 20

1	Armbrust M ， Fox A ， Griffith R ，et al. A view of cloud computing. Communications of the ACM， 2010，53（4）： 50～58
2	Bruneo D . A stochastic model to investigate data center performance and QoS in IaaS cloud computing systems. IEEE Transactions on Parallel and Distributed Systems， 2014，25（3）： 560～569
3	Wang S ， Munawar W ， Liu J ，et al. Power-saving design for server farms with response time percentile guarantees. Proceedings of the 18th Real-Time and Embedded Technology and Applications Symposium（RTAS）， Beijing，China， 2012
4	Xiong K Q ， Perros H . QRP01-6：resource optimization subject to a percentile response time SLA for enterprise computing. Proceedings of Global Telecommunications Conference， San Francisco，CA，USA， 2006
5	Decandia G ， Hastorun D ， Jampani M ，et al. Dynamo：amazon’s highly available key-value store. SIGOPS Oper Syst Rev， 2007，41（6）： 205～220
6	Khazaei H . Performance modeling of cloud computing centers （doctor dissertation）. The University of Manitoba， 2012
7	Zhuravlev S ， Saez J C ， Blagodurov S ，et al. Survey of energy-cognizant scheduling techniques. IEEE Transactions on Parallel and Distributed Systems， 2013，24（7）： 1447～1464
8	Deng W ， Liu F ， Jin H ，et al. Reliability-aware server consolidation for balancing energy-lifetime tradeoff in virtualized cloud datacenters. International Journal of Communication Systems， 2014，27（4）： 623～642
9	Berl A ， Gelenbe E ， Di Girolamo M ，et al. Energy-efficient cloud computing. The Computer Journal， 2010，53（7）： 1045～1051
10	Bilal K ， Malik S U R ， Khalid O ，et al. A taxonomy and survey on green data center networks. Future Generation Computer Systems， 2014，36（7）： 189～208
11	Cao J ， Li K ， Stojmenovic I . Optimal power allocation and load distribution for multiple heterogeneous multicore server processors across clouds and data centers. IEEE Transactions on Computers， 2014，63（1）： 45～58
12	Cao J W ， Kai H ， Li K Q ，et al. Optimal multiserver configuration for profit maximization in cloud computing. IEEE Transactions on Parallel and Distributed Systems， 2013，24（6）： 1087～1096
13	Xiong K Q ， Perros H . Service performance and analysis in cloud computing. Proceedings of 2009 World Conference on Services-I， Los Angeles，CA，USA， 2009： 693～700
14	Xiong K Q ， Suh S . Resource Provisioning in SLA-Based Cluster Computing Job Scheduling Strategies for Parallel Processing. Berlin： Springer Berlin Heidelberg, 2010： 1～15
15	陆传赉 . 排队论. 北京：北京邮电学院出版社， 1994 Lu C L . Queuing Theory. Beijing： Beijing University of Posts and Telecommunications Press， 1994
16	唐应辉，唐小我 . 排队论：基础与分析技术. 北京：科学出版社， 2006 Tang Y H ， Tang X W . Queuing Theory：Basic and Analysis. Beijing： Science Press， 2006
17	Gross D ， Shortle J F ， Thompson J M ，et al. Fundamentals of Queueing Theory. Hoboken： John Wiley ＆ Sons, 2013
18	Zhai B ， Blaauw D ， Sylvester D ，et al. Theoretical and practical limits of dynamic voltage scaling. Proceedings of the 41st Design Automation Conference， San Diego，USA， 2004
19	Mazzucco M ， Dyachuk D . Balancing electricity bill and performance in server farms with setup costs. Future Generation Computer Systems-The International Journal of Grid Computing and Escience， 2012，28（2）： 415～426
20	Altiok T ， Melamed B . Simulation modeling and analysis with Arena. New York： Academic Press, 2010

Metrics

Recommended 0

No Suggested Reading articles found!

λ	s	n	C	C_e	C_r	ρ
45	4.914 27	14.264 89	74.049 40	66.916 95	7.132 44	0.641 92
55	4.912 12	16.761 26	90.017 52	81.636 87	8.380 63	0.668 02
65	4.910 46	19.218 55	105.954 93	96.345 65	9.609 27	0.688 76
75	4.909 13	21.645 46	121.868 51	111.045 78	10.822 72	0.705 81

[1]	Huahua CHEN, Zhe CHEN. Research on anomaly detection algorithm based on sparse variational autoencoder using spike and slab prior [J]. Telecommunications Science, 2022, 38(12): 65-77.
[2]	Ziyu XIAO, Hongwei LV, Cun ZHAO, Yan HAN, Jian SU. Methodology of 5G network planning and design for vertical industry with product solutions [J]. Telecommunications Science, 2021, 37(6): 143-149.
[3]	Lijun ZU,Hang YUAN. Research and application of SRv6 Policy for financial backbone network [J]. Telecommunications Science, 2020, 36(8): 53-65.
[4]	Yiliang LIU,Xin LI,Kaitao BO. End-to-end network collaboration in 5G networks [J]. Telecommunications Science, 2020, 36(3): 144-155.
[5]	Hui Xiao,Jinchao Lin,Weihua Cao,Wenyun Li. Researcb on Private IP Address Mutiplexing in Mobile PS Domain [J]. Telecommunications Science, 2014, 30(7): 139-142.
[6]	Jianwu Zhang,Jie Yuan. Energy-Efficient Approach Based on 3G Background Traffic Shaping [J]. Telecommunications Science, 2014, 30(12): 1-86.
[7]	Panpan Li,Hongli Zhang,Huimin Deng,Zhigang Zhou. SLA Audit Mechanism of Virtual Machine Memory on Cloud [J]. Telecommunications Science, 2013, 29(6): 72-81.
[8]	Yan Hu,Zihao Zhang,Dan Ma. Wind-Solar Hybrid Power Technology for Communication Base Station [J]. Telecommunications Science, 2013, 29(4): 151-154.
[9]	Yan Li,Zhizhong Zhang. Research and Implementation of SlAP Monitor in LTE Network [J]. Telecommunications Science, 2013, 29(1): 31-38.
[10]	Qiongfen Qian,Chunlin Li,Jiajun Xiong,Qiang Li. Towards SLA Management in Cloud Computing [J]. Telecommunications Science, 2012, 28(10): 38-45.
[11]	Gansen Zhao,Hai Yu,Tongkai Ji,Hong Song. Adaptive Resource Provisioning for Cloud Computing [J]. Telecommunications Science, 2012, 28(1): 35-41.
[12]	Cuie Wang,Yonggen Gu,Xiaohong Wu,Jie Tao. Mechanism Design for Optimizing Response Time of SLA in Cloud Computing [J]. Telecommunications Science, 2012, 28(1): 46-50.
[13]	Zhao Gansen,Yu Hai,Ji Tongkai and Song Hong. Adaptive Resource Provisioning for Cloud Computing [J]. Telecommunications Science, 2012, 28(1): 31-37.
[14]	Wang Cuie,Gu Yonggen,Wu Xiaohong and Tao Jie. Mechanism Design for Optimizing Response Time of SLA in Cloud Computing [J]. Telecommunications Science, 2012, 28(1): 42-46.
[15]	Ling Gai. Research Based on Security Services of Cloud Computing [J]. Telecommunications Science, 2011, 27(6): 97-100.

Optimal Resource Provision of Cloud Center with Guarantee Percentile Response Time

RichHTML

PDF下载

Knowledge

Abstract

Cite this article

share this article

Figures/Tables 6

References 20

Related Articles 15

Metrics

Recommended 0