Virtual machine placement with (m, n)-fault tolerance in cloud data center

被引:25
作者
Zhou, Ao [1 ]
Wang, Shangguang [1 ]
Hsu, Ching-Hsien [2 ]
Kim, Myung Ho [3 ]
Wong, Kok-seng [3 ]
机构
[1] Beijing Univ Posts & Telecommun, State Key Lab Networking & Switching Technol, Beijing, Peoples R China
[2] Chung Hua Univ, Dept Comp Sci & Informat Engn, Hsinchu, Taiwan
[3] Soongsil Univ, Sch Software, Seoul, South Korea
来源
CLUSTER COMPUTING-THE JOURNAL OF NETWORKS SOFTWARE TOOLS AND APPLICATIONS | 2019年 / 22卷 / Suppl 5期
关键词
Cloud computing; Fault tolerance; Virtual machine placement; Data center network; PERFORMANCE; ALGORITHMS;
D O I
10.1007/s10586-017-1426-y
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Scalable computing resources are provided via the Internet in the cloud computing environment. A growing number of application providers begin to deploy their applications in cloud to save the infrastructure maintaince cost. The probability of node failures cannot be nontrivial due to a great quantity of nodes in the cloud data center. To address the problem, the virtual machine replication technique is extensively adopted in the cloud system to enhance the application/service reliability. K-fault tolerance is a typical replication strategy employed in cloud. However, currently proposed K-fault tolerance replication strategies cannot achieve the best effect due to the ignorance of switch failure. In this paper, we study to design a (m, n)-fault tolerance virtual machine placement algorithm to solve the problem. Firstly, we formulate the problem as an integer linear programming problem, and prove that the problem is NP-hard. Secondly, we extensively employ differential evolution (DE) algorithm to solve the integer linear programming problem. Finally, experiments are conducted to study the effectiveness of our algorithm, and the simulation results demonstrate that our algorithm outperforms other algorithms in reliability enhancement.
引用
收藏
页码:11619 / 11631
页数:13
相关论文
共 28 条
[1]   A scalable, commodity data center network architecture [J].
Al-Fares, Mohammad ;
Loukissas, Alexander ;
Vahdat, Amin .
ACM SIGCOMM COMPUTER COMMUNICATION REVIEW, 2008, 38 (04) :63-74
[2]   A View of Cloud Computing [J].
Armbrust, Michael ;
Fox, Armando ;
Griffith, Rean ;
Joseph, Anthony D. ;
Katz, Randy ;
Konwinski, Andy ;
Lee, Gunho ;
Patterson, David ;
Rabkin, Ariel ;
Stoica, Ion ;
Zaharia, Matei .
COMMUNICATIONS OF THE ACM, 2010, 53 (04) :50-58
[3]  
Bansal N, 2006, ANN IEEE SYMP FOUND, P697
[4]  
Bauer E., 2012, RELIABILITY AVAILABI
[5]   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
[6]   Energy-aware resource allocation heuristics for efficient management of data centers for Cloud computing [J].
Beloglazov, Anton ;
Abawajy, Jemal ;
Buyya, Rajkumar .
FUTURE GENERATION COMPUTER SYSTEMS-THE INTERNATIONAL JOURNAL OF ESCIENCE, 2012, 28 (05) :755-768
[7]   Cloud computing and emerging IT platforms: Vision, hype, and reality for delivering computing as the 5th utility [J].
Buyya, Rajkumar ;
Yeo, Chee Shin ;
Venugopal, Srikumar ;
Broberg, James ;
Brandic, Ivona .
FUTURE GENERATION COMPUTER SYSTEMS-THE INTERNATIONAL JOURNAL OF ESCIENCE, 2009, 25 (06) :599-616
[8]   On multidimensional packing problems [J].
Chekuri, C ;
Khanna, S .
SIAM JOURNAL ON COMPUTING, 2004, 33 (04) :837-851
[9]  
Dai Y.-S., 15 IEEE PAC RIM INT, P1
[10]  
Dong MX, 2014, IEEE CONF COMPUT, P529, DOI 10.1109/INFCOMW.2014.6849287