Data Placement and Query for Cloud Computing Based on MyHeawood Network

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Abstract:

The massive data in Data centers network will be frequently accessed massive datasets for cloud services, which will lead to some new requirements and becomes an important issue for interconnection topology and data management in cloud computing. According to the cost-effective, the paper proposes a new interconnection network MyHeawood for cloud computing. MyHeawood is constructed by small switches and servers with dual-port NIC according to recursive method. The data placement strategy in MyHeawood is a hashing algorithm based on the family of hash functions. MyHeawood uses three replicas strategy base on master copy, which is allocated in different sub layer to improve the reliability of data.

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3100-3104

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March 2014

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© 2014 Trans Tech Publications Ltd. All Rights Reserved

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[1] E. Deelman, A. Chervenak, Data Management Challenges of Data-Intensive Scientific Workflows, CCGRID'08, 8th IEEE International Symposium on Clouster Computing and the Grid, (2008).

DOI: 10.1109/ccgrid.2008.24

Google Scholar

[2] D. Yuan,Y. Yang, X. Liu & Jinjun Chen, A data placement strategy in scientific cloud workflows, in Future Generation Computer Systems, Volume 26, Issue 8, October (2010).

DOI: 10.1016/j.future.2010.02.004

Google Scholar

[3] Chervenak et al, Data placement for scientific applications in distributed environments, in 8th IEEE/ACM International Conference on Grid Computing, 19-21 Sept. (2007).

DOI: 10.1109/grid.2007.4354142

Google Scholar

[4] D. Joyner, Minh Van Nguyen, Nathann Cohen, in Algorithmic Graph Theory. March 17, (2012).

Google Scholar

[5] Geneeujan et al., Novel Hierarchical Interconnection Networks for High-Performance Multicomputer Systems, (2004).

Google Scholar

[6] Chuanxiong Guo et al., DCell: A Scalable and Fault-tolerant Network Structure for Data Centers, in SIGCOMM'08, August 17-22, 2008, Scattle, Washington, USA.

Google Scholar

[7] Dan Li et al., FiConn: Using Backup Port for Server Interconnection in Data Centers, in IEEE InFocom (2009).

DOI: 10.1109/infcom.2009.5062153

Google Scholar

[8] C.X. Guo, G. Lu, D. Li, H. Wu, X. Zhang, Y. Shi, C. Tian, Y. Zhang, and S. Lu. Bcube: a high performance, server-centric network architecture for modular data centers. In SIGCOMM '09.

DOI: 10.1145/1592568.1592577

Google Scholar

[9] A. Greenberg J.R. Hamilton,N. Jain. VL2: A Scalable and Flexible Data center. SIGCOMM'09, August 17-21, (2009).

Google Scholar

[10] J. Schanffner, D. Jacobs, T. Kraska, and H. Plattner, The Multi-Tenant Data Placement Problem, DBKDA (2012).

Google Scholar

[11] S. Ghemawat,H. Gobioff, and S.T. Leung, The Goolge File System, SOSP'03.

Google Scholar

[12] G. DeCandia, et al. Vogels, Dynamo: amazon's highly available key-value store, in Proceedings of the 21st ACM Symposium on Operating Systems Principles, SOSP (2007).

DOI: 10.1145/1294261.1294281

Google Scholar