Skip to main content
SpringerLink
Log in
Book cover

International Conference on Algorithms and Architectures for Parallel Processing

ICA3PP 2015: Algorithms and Architectures for Parallel Processing pp 781–790Cite as

ABR-Tree: An Efficient Distributed Multidimensional Indexing Approach for Massive Data

  • Conference paper
  • First Online:

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 9532))

Abstract

In the big data era, there many application scenarios urgently need efficient distributed multidimensional indexing approach to accelerate the data analytics. To address this issue, in this paper, we propose ABR-Tree, a multidimensional distributed indexing approach. ABR-Tree consist of two components, the global append-efficient B + -Tree, and the local R*-Tree. Both of them are layered over the cloud database as the index and data store, which not only make ABR-Tree is easy to implement and inherently become a distributed cloud index, but also enable ABR-Tree can sustain high throughput workload and large data volumes, meanwhile, ensuring fault-tolerance, and high availability. We conducted extensive experiments over 1 TB real data set to evaluate its efficiency of processing multidimensional range queries, the results show that it is significantly fast than the existing representative distributed multidimensional cloud index method.

This is a preview of subscription content, log in via an institution.

Chapter
USD   29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD   84.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD   109.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Learn about institutional subscriptions

References

  1. Sanjay, G., Howard, G., Shun-Tak, L.: The Google file system. In: Proceedings of the SOSP 2003, pp. 29–43 (2003)

    Google Scholar 

  2. Hadoop Distributed File System. https://hadoop.apache.org/

  3. Shoji, N., Sudipto, D., Divyakant, A., Amr, A.: MD-HBase: design and implementation of an elastic data infrastructure for cloud-scale location services. Distrib. Parallel Databases 31(2), 289–319 (2013)

    Article  Google Scholar 

  4. Jinbao, W., Sai, W., Hong, G., Jianzhong, L., Beng, O.: Indexing multi-dimensional data in a cloud system. In: Proceedings of the SIGMOD 2010, pp. 591–602 (2010)

    Google Scholar 

  5. Xiangyu, Z., Jing, A., Zhongyuan, W., Jiaheng, L., Xiaofeng, M.: An efficient multi-dimensional index for cloud data management. In: CloudDB 2009, pp. 17–24 (2009)

    Google Scholar 

  6. Zhou, X., Zhang, X., Wang, Y., Li, R., Wang, S.: Efficient distributed multi-dimensional index for big data management. In: Wang, J., Xiong, H., Ishikawa, Y., Xu, J., Zhou, J. (eds.) WAIM 2013. LNCS, vol. 7923, pp. 130–141. Springer, Heidelberg (2013)

    Chapter  Google Scholar 

  7. Haojun, L., Jizhong, H., Jinyun, F.: Multi-dimensional Index on Hadoop Distributed File System. In: Proceedings of the NAS 2010, pp. 240–249 (2010)

    Google Scholar 

  8. Zou, Y., Liu, J., Wang, S., Zha, L., Xu, Z.: CCIndex: A complemental clustering index on distributed ordered tables for multi-dimensional range queries. In: Ding, C., Shao, Z., Zheng, R. (eds.) NPC 2010. LNCS, vol. 6289, pp. 247–261. Springer, Heidelberg (2010)

    Chapter  Google Scholar 

  9. George, T., Dimitris, S., Timos, S.: Index-based query processing on distributed multidimensional data. GeoInformatica 17(3), 489–519 (2013)

    Article  Google Scholar 

  10. Beomseok, N., Alan, S.: Analyzing design choices for distributed multidimensional indexing. J. Supercomputing 59(3), 1552–1576 (2012)

    Article  Google Scholar 

  11. Andreas, P., Dimitrios, K.: A-Tree: distributed indexing of multidimensional data for cloud computing environments. In: Proceedings of the CloudCom 2011, pp. 407–414 (2011)

    Google Scholar 

  12. Xinfa, W., Kaoru, S.: DHR-Trees: A distributed multidimensional indexing structure for P2P systems. SCPE 8(3), 291–300 (2007)

    Google Scholar 

  13. Apache HBase. http://hbase.apache.org/

  14. Amazon Elastic Compute Cloud (Amazon EC2). https://aws.amazon.com/ec2/

  15. Sylvia, R., Paul, F., Mark, Handley., Richard, K., Scott, S.: A scalable content-addressable network. In: Proceedings of the SIGCOMM 2001, pp.161–172 (2001)

    Google Scholar 

  16. Nokia Solutions and Networks. http://www.nsn.com

Download references

Acknowledgments

This work was supported by the China Ministry of Science and Technology under the State Key Development Program for Basic Research (2012CB821800), Fund of National Natural Science Foundation of China (No. 61462012, 61562010, U1531246), Scientific Research Fund for talents recruiting of Guizhou University (No. 700246003301), Science and Technology Fund of Guizhou Province (No. J [2013]2099), High Tech. Project Fund of Guizhou Development and Reform Commission (No. [2013]2069), Industrial Research Projects of the Science and Technology Plan of Guizhou Province (No. GY[2014]3018) and The Major Applied Basic Research Program of Guizhou Province (NO. JZ20142001, NO. JZ20142001-05).

Author information

Authors and Affiliations

  1. School of Infomation, Renmin University of China, Beijing, 100872, China

    Xin Zhou, Xiao Zhang & Shan Wang

  2. College of Computer Science and Technology, Guizhou University, Guiyang, 550025, China

    Hui Li

  3. Nokia Solutions and Networks, Beijing, 100016, China

    Yanyu Ma & Keyan Liu

  4. National Astronomical Observatories, Chinese Academy of Sciences, Beijing, 100012, China

    Ming Zhu & Menglin Huang

Authors
  1. Xin Zhou
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Hui Li
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Xiao Zhang
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Shan Wang
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Yanyu Ma
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Keyan Liu
    View author publications

    You can also search for this author in PubMed Google Scholar

  7. Ming Zhu
    View author publications

    You can also search for this author in PubMed Google Scholar

  8. Menglin Huang
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Hui Li .

Editor information

Editors and Affiliations

  1. Central South University, Changsha, China

    Guojin Wang

  2. Sch of Information Technologies, Sydney University, Sydney, New South Wales, Australia

    Albert Zomaya

  3. Department of Information and Commu, University of Murcia, Murcia, Murcia, Spain

    Gregorio Martinez

  4. Changsha, China

    Kenli Li

Rights and permissions

Reprints and permissions

Copyright information

© 2015 Springer International Publishing Switzerland

About this paper

Cite this paper

Zhou, X. et al. (2015). ABR-Tree: An Efficient Distributed Multidimensional Indexing Approach for Massive Data. In: Wang, G., Zomaya, A., Martinez, G., Li, K. (eds) Algorithms and Architectures for Parallel Processing. ICA3PP 2015. Lecture Notes in Computer Science(), vol 9532. Springer, Cham. https://doi.org/10.1007/978-3-319-27161-3_71

Download citation

  • DOI: https://doi.org/10.1007/978-3-319-27161-3_71

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-27160-6

  • Online ISBN: 978-3-319-27161-3

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics

Search

Navigation