Distributed Virtual Machine Placement based on Dependability in Data Centers

被引:0
作者
Yin, Luxiu [1 ]
He, Wenfeng [1 ]
Luo, Juan [1 ]
机构
[1] Hunan Univ, Coll Comp Sci & Elect Engn, Changsha, Hunan, Peoples R China
来源
2016 12TH INTERNATIONAL CONFERENCE ON NATURAL COMPUTATION, FUZZY SYSTEMS AND KNOWLEDGE DISCOVERY (ICNC-FSKD) | 2016年
关键词
clustering; data center; dependability; virtual machine placement;
D O I
暂无
中图分类号
TP301 [理论、方法];
学科分类号
081202 ;
摘要
One of primary and challenging difficulties in placing virtual machine (VM) onto physical machines in a cloud data center, is to balance the interests of both cloud service providers (CSPs) and cloud tenants, which are often expressed as minimizing the number of power-on servers and improving user experience respectively. However, the current research on VMP try to gathering the requested VMs on the fewest possible activated PMs for the purpose of reducing the number of power-on physical machines, without taking the experience of cloud tenants in to account. In this study, we define and formulate the VMP problem in cloud data center, and design a VMP strategy named Dependability based Distributed Virtual Machine Placement algorithm (D2VMP), with the placement goals of energy efficiency and dependability. To maintain the dependability of user requests D2VMP limits the number of virtual machines from the same request assigned on each physical machine. Furthermore, to ensure minimize the number of power-on physical machines, we propose to divide the data center into several clusters, and thus, different requests can reuse activated clusters. The experimental results demonstrate that proposed algorithm can effectively lower the power-on devices and maintain service-dependability.
引用
收藏
页码:2152 / 2158
页数:7
相关论文
共 16 条
[1]  
[Anonymous], 2010, P 8 INT WORKSH MIDDL
[2]  
[Anonymous], 2014, 23 INT C COMP COMM N
[3]  
[Anonymous], 2010, INFOCOM, 2010 Proceedings IEEE, DOI 10.1109/INFCOM.2010.5461930
[4]   Optimal online deterministic algorithms and adaptive heuristics for energy and performance efficient dynamic consolidation of virtual machines in Cloud data centers [J].
Beloglazov, Anton ;
Buyya, Rajkumar .
CONCURRENCY AND COMPUTATION-PRACTICE & EXPERIENCE, 2012, 24 (13) :1397-1420
[5]   CloudSim: a toolkit for modeling and simulation of cloud computing environments and evaluation of resource provisioning algorithms [J].
Calheiros, Rodrigo N. ;
Ranjan, Rajiv ;
Beloglazov, Anton ;
De Rose, Cesar A. F. ;
Buyya, Rajkumar .
SOFTWARE-PRACTICE & EXPERIENCE, 2011, 41 (01) :23-50
[6]  
Ferdaus M.H., 2014, CLOUD COMPUTING, P179, DOI DOI 10.1007/978-3-319-10530-7_8
[7]   The Cost of a Cloud: Research Problems in Data Center Networks [J].
Greenberg, Albert ;
Hamilton, James ;
Maltz, David A. ;
Patel, Parveen .
ACM SIGCOMM COMPUTER COMMUNICATION REVIEW, 2009, 39 (01) :68-73
[8]   Placing Virtual Machines to Optimize Cloud Gaming Experience [J].
Hong, Hua-Jun ;
Chen, De-Yu ;
Huang, Chun-Ying ;
Chen, Kuan-Ta ;
Hsu, Cheng-Hsin .
IEEE TRANSACTIONS ON CLOUD COMPUTING, 2015, 3 (01) :42-53
[9]   An Energy Efficient Virtual Machine Placement Algorithm with Balanced Resource Utilization [J].
Huang, Wei ;
Li, Xin ;
Qian, Zhuzhong .
2013 SEVENTH INTERNATIONAL CONFERENCE ON INNOVATIVE MOBILE AND INTERNET SERVICES IN UBIQUITOUS COMPUTING (IMIS 2013), 2013, :313-319
[10]  
Jiang JW, 2012, IEEE INFOCOM SER, P2876, DOI 10.1109/INFCOM.2012.6195719