The Community for Technology Leaders
RSS Icon
Subscribe
Issue No.01 - {} (2013 vol.1)
pp: 101-115
Jenn-Wei Lin , Dept. of Comput. Sci. & Inf. Eng., Fu Jen Catholic Univ., New Taipei, Taiwan
Chien-Hung Chen , Dept. of Electr. Eng., Nat. Taiwan Univ., Taipei, Taiwan
J. Morris Chang , Dept. of Electr. & Comput. Eng., Iowa State Univ., Ames, IA, USA
ABSTRACT
Cloud computing provides scalable computing and storage resources. More and more data-intensive applications are developed in this computing environment. Different applications have different quality-of-service (QoS) requirements. To continuously support the QoS requirement of an application after data corruption, we propose two QoS-aware data replication (QADR) algorithms in cloud computing systems. The first algorithm adopts the intuitive idea of high-QoS first-replication (HQFR) to perform data replication. However, this greedy algorithm cannot minimize the data replication cost and the number of QoS-violated data replicas. To achieve these two minimum objectives, the second algorithm transforms the QADR problem into the well-known minimum-cost maximum-flow (MCMF) problem. By applying the existing MCMF algorithm to solve the QADR problem, the second algorithm can produce the optimal solution to the QADR problem in polynomial time, but it takes more computational time than the first algorithm. Moreover, it is known that a cloud computing system usually has a large number of nodes. We also propose node combination techniques to reduce the possibly large data replication time. Finally, simulation experiments are performed to demonstrate the effectiveness of the proposed algorithms in the data replication and recovery.
INDEX TERMS
Quality of service, Cloud computing, Servers, Switches, Radio frequency, Algorithm design and analysis, Heuristic algorithms, Cloud computing,network flow problem, Cloud computing, data-intensive application, quality of service, data replication
CITATION
Jenn-Wei Lin, Chien-Hung Chen, J. Morris Chang, "QoS-Aware Data Replication for Data-Intensive Applications in Cloud Computing Systems", IEEE Transactions on Cloud Computing, vol.1, no. 1, pp. 101-115, {} 2013, doi:10.1109/TCC.2013.1
REFERENCES
[1] M. Armbrust, A. Fox, R. Griffith, A.D. Joseph, R.H. Katz, A. Konwinski, G. Lee, D.A. Patterson, A. Rabkin, I. Stoica, and M. Zaharia, "Above the Clouds: A Berkeley View of Cloud Computing," Technical Report UCB/EECS-2009-28, Dept. of EECS, California Univ., Berkeley, Feb. 2009.
[2] M. Creeger, "Cloud Computing: An Overview," Queue, vol. 7, no. 5, pp. 2:3-2:4, June 2009.
[3] M.D. Dikaiakos, D. Katsaros, P. Mehra, G. Pallis, and A. Vakali, "Cloud Computing: Distributed Internet Computing for IT and Scientific Research," IEEE Internet Computing, vol. 13, no. 5, pp. 10-13, Sept. 2009.
[4] R. Buyya, C.S. Yeo, S. Venugopal, J. Broberg, and I. Brandic, "Cloud Computing and Emerging IT Platforms: Vision, Hype, and Reality for Delivering Computing as the fifth Utility," Future Generation Computer Systems, vol. 25, no. 6, pp. 599-616, June 2009.
[5] Apache Hadoop Project, http:/hadoop.apache.org, 2013.
[6] K.V. Vishwanath and N. Nagappan, "Characterizing Cloud Computing Hardware Reliability," Proc. ACM Symp. Cloud Computing, pp. 193-204, June 2010.
[7] E. Pinheiro, W.-D. Weber, and L.A. Barroso, "Failure Trends in a Large Disk Drive Population," Proc. Fifth USENIX Conf. File and Storage Technologies, pp. 17-28, Feb. 2007.
[8] B. Schroeder and G.A. Gibson, "Disk Failures in the Real World: What Does an MTTF of 1,000,000 Hours Mean to You?" Proc. Fifth USENIX Conf. File and Storage Technologies, pp. 1-16, Feb. 2007.
[9] F. Wang, J. Qiu, J. Yang, B. Dong, X. Li, and Y. Li, "Hadoop High Availability through Metadata Replication," Proc. First Int'l Workshop Cloud Data Manage, pp. 37-44, 2009.
[10] K. Shvachko, H. Kuang, S. Radia, and R. Chansler, "The Hadoop Distributed File System," Proc. IEEE 26th Symp. Mass Storage Systems and Technologies (MSST), pp. 1-10, June 2010.
[11] A. Gao and L. Diao, "Lazy Update Propagation for Data Replication in Cloud Computing," Proc. Fifth Int'l Conf. Pervasive Computing and Applications (ICPCA), pp. 250-254, Dec. 2010.
[12] W. Li, Y. Yang, J. Chen, and D. Yuan, "A Cost-Effective Mechanism for Cloud Data Reliability Management Based on Proactive Replica Checking," Proc. IEEE/ACM 12th Int'l Symp. Cluster, Cloud and Grid Computing (CCGrid), pp. 564-571, May 2012.
[13] C.N. Reddy, "A CIM (Common Information Model) Based Management Model for Clouds," Proc. IEEE Int'l Conf. Cloud Computing in Emerging Markets (CCEM), pp. 1-5, Oct. 2012.
[14] Amazon EC2. http://aws.amazon.comec2/, 2013.
[15] X. Tang and J. Xu, "QoS-Aware Replica Placement for Content Distribution," IEEE Trans. Parallel and Distributed Systems, vol. 16, no. 10, pp. 921-932, Oct. 2005.
[16] S. Ghemawat, H. Gobioff, and S.-T. Leung, "The Google File System," Proc. 19th ACM Symp. Operating Systems Principles, vol. 37, no. 5, pp. 29-43, Dec. 2003.
[17] IEEE Standard for Local and Metropolitan Area Networks: Media Access Control (MAC) Bridges, IEEE 802.1D Std., 2004.
[18] M. Shorfuzzaman, P. Graham, and R. Eskicioglu, "QoS-Aware Distributed Replica Placement in Hierarchical Data Grids," Proc. IEEE Int'l Conf. Advanced Information Networking and Applications, pp. 291-299, Mar. 2011.
[19] H. Wang, P. Liu, and J.-J. Wu, "A QoS-Aware Heuristic Algorithm for Replica Placement," Proc. IEEE/ACM Seventh Int'l Conf. Grid Computing, pp. 96-103, Sept. 2006.
[20] X. Fu, R. Wang, Y. Wang, and S. Deng, "A Replica Placement Algorithm in Mobile Grid Environments," Proc. Int'l Conf. Embedded Software and Systems (ICESS '09), pp. 601-606, May 2009.
[21] A.M. Soosai, A. Abdullah, M. Othman, R. Latip, M.N. Sulaiman, and H. Ibrahim, "Dynamic Replica Replacement Strategy in Data Grid," Proc. Eighth Int'l Conf. Computing Technology and Information Management (ICCM), pp. 578-584, Apr. 2012.
[22] D. Gross and C.M. Harris, Fundamentals of Queueing Theory, third ed. John Wiley & Sons, 1998.
[23] H. Khazaei and J.M.V.B. Mii, "Performance Analysis of Cloud Computing Centers Using M/G/m/m+r Queuing Systems," IEEE Trans. Parallel and Distributed Systems, vol. 23, no. 5, pp. 936-943, May 2012.
[24] S. Bradley, A. Hax, and T. Magnanti, Applied Mathematical Programming. Addison-Wesley, 1977.
[25] S. Dasgupta, C.H. Papadimitriou, and U.V. Vazirani, Algorithms. McGraw-Hill, 2008.
[26] R.K. Ahuja, T.L. Magnanti, and J.B. Orlin, Network Flows: Theory, Algorithms, and Applications, first ed. Prentice Hall, Feb. 1993.
[27] P.T. Sokkalingam, R.K. Ahuja, and J.B. Orlin, "New Polynomial-Time Cycle-Canceling Algorithms for Minimum-Cost Flows," Networks, vol. 36, no. 1, pp. 53-63, June 2000.
[28] C.-X. Xu, "A Simple Solution to Maximum Flow at Minimum Cost," Proc. Second Int'l Conf. Information Eng. and Computer Science (ICIECS '10), pp. 1-4, Dec. 2010.
[29] W. Lin and D. Qi, "Research on Resource Self-Organizing Model for Cloud Computing," Proc. Int'l Conf. Internet Technology and Applications, pp. 1-5, Aug. 2010.
[30] A. Voulodimos, S. Gogouvitis, N. Mavrogeorgi, R. Talyansky, D. Kyriazis, S. Koutsoutos, V. Alexandrou, E. Kolodner, P. Brand, and T. Varvarigou, "A Unified Management Model for Data Intensive Storage Clouds," Proc. First Int'l Symp. Network Cloud Computing and Applications, pp. 69-72, Nov. 2011.
[31] L. Xu and J. Yang, "A Management Platform for Eucalyptus-Based IaaS," Proc. IEEE Int'l Conf. Cloud Computing and Intelligence Systems, pp. 193-197, Sept. 2011.
[32] MathWorks - MATLAB and Simulink for Technical Computing, http:/www.mathworks.com, 2013.
[33] Speed Considerations, http://www.seagate.com/www/en-us/support/ before_you_buyspeed_considerations, 2013.
[34] Hard Disk Performance, Quality and Reliability, http://www.pcguide.com/ref/hdd/perfindex.htm , 2013.
[35] Latency on a Switched Ethernet Network, http://www. ruggedcom.com/pdfs/application_notes latency_on_a_ switched_ethernet_network.pdf , 2013.
[36] T. Shanley, InfiniBand Network Architecture, first ed. Addison-Wesley, 2002.
8 ms
(Ver 2.0)

Marketing Automation Platform Marketing Automation Tool