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MHB-Tree: A Distributed Spatial Index Method for Document Based NoSQL Database System

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Ubiquitous Information Technologies and Applications

Part of the book series: Lecture Notes in Electrical Engineering ((LNEE,volume 214))

Abstract

As the development of telecommunication technology and mobile device technology, geo-location data happened everywhere and every time from humans’ real life. Because all of the smart device’s applications are include spatial components now. When the traditional relational database cannot support the continuously flooded data, researchers developed key-value based NoSQL database system to meet this problem. But spatial data processes are rarely considered until now. In this case client user must have their own spatial data processing component to process the spatial data from NoSQL database. In this paper, we proposed a spatial index based on document based NoSQL which can distribute the spatial data by using the geo-hash method and can satisfy the high insert rate by using the b-tree based index method. At last we developed our method on OrientDB which is document based NoSQL.

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References

  1. Jing, J., Helal, A.S., Elamagarmid, A.: Client-server computing in mobile environments. ACM Comp. Surv. 31(4), 117–157 (2012)

    Google Scholar 

  2. Schrom-Feiertag, H.: A mobile LBS for geo-content generation facilitating users to share, rate and access information in a novel manner. Adv. Location-Based Serv. Sect. I, 55–75 (2012)

    Article  Google Scholar 

  3. Kang, C.: Ph. D Cloud computing and its applications in GIS, Clark University, p. 93 (2012)

    Google Scholar 

  4. Han, J., Haihong, E.: Survey on NoSQL database. In: Pervasive computing and applications (ICPCA), 2011 6th international conference on, pp. 363–366, (2011)

    Google Scholar 

  5. Shetty, K.S., Singh, S.: Cloud based application development for accessing restaurant information on mobile device using LBS. Int. J. UbiComp (IJU) 2(4), 37–49 (2011)

    Google Scholar 

  6. du Mouza, C., Litwin, W., Rigaux, P.: Large-scale indexing of spatial data in distributed repositories: the SD-Rtree. VLDB J. Int. J. Very Large Data Bases Arch. 18 (4), 933–958 (2009)

    Google Scholar 

  7. Jagadish, H.V., Ooi, B.C, Vu, Q.H.: BATON: a balanced tree structure for peer-to-peer networks. In: Proceedings International Conferences on Very Large Data Bases (VLDB), pp. 661–672. (2005)

    Google Scholar 

  8. Apache Cassandra: http://cassandra.apache.org/

  9. The graph-document based NoSQLdatabase:OrientDB: http://www.orientechnologies.com/

  10. Amazon Web Services Made Simple: Learn how Amazon EC2, S3, SimpleDB and SQS Web Services

    Google Scholar 

  11. Sun, Y., Aggarwal, C. C., Han, J.: Relation strength-aware clustering of heterogeneous information networks with incomplete attributes. Proceedings of the VLDB Endowment, 5(5), 394−405 (2012)

    Google Scholar 

  12. Li, K., Yao, F.: An online clustering algorithm. In: 2011 Eighth international conference, Vol. 2, pp. 1104–1108. (2011)

    Google Scholar 

  13. Sadoghi, M., Jacobsen, H.-A.: BE-tree: an index structure to efficiently match Boolean expressions over high-dimensional discrete space. In: SIGMOD ‘11: Proceedings of the 2011 international conference on Management of data, (2011)

    Google Scholar 

  14. Dekel, O., Gilad-Bachrach, R.: Optimal distributed online prediction using mini-batches, J. Mach. Learn. Res. 13, 165−202 (2012)

    Google Scholar 

  15. Rigaux, P.: Spatial databases: with application to GIS. Morgan Kaufmann Publishers, Burlington (2001)

    Google Scholar 

  16. Jianliang, X., Baihua, Z., Wang-Chien, L., DikLun L.: The d-tree: an index structure for planar point queries in location based wireless services. IEEE Trans. Knowl. Data Eng. 16(12), 1526–1542 (2004)

    Google Scholar 

  17. Aizawa, K., Tanaka, S.: A constant-time algorithm for finding neighbors in quadtrees. IEEE Trans. Pattern Anal. Mach. 31(7), 1178–1183 (2009)

    Google Scholar 

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Author information

Authors and Affiliations

  1. Department of Computer and Information Engineering, Inha University, Incheon, Korea

    Yan Li & HaeYoung Bae

  2. Department of Computer Education, Seowon University, Chongju, Korea

    GyoungBae Kim

  3. Department of Information Science, Soongsil University, Seoul, Korea

    LongRi Wen

Authors
  1. Yan Li
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  2. GyoungBae Kim
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  3. LongRi Wen
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  4. HaeYoung Bae
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Corresponding author

Correspondence to Yan Li .

Editor information

Editors and Affiliations

  1. and Education, Computer Science and Engineering, Korea University of Technology, Chungjeolno, Byeongchun 1600, CheonAn, 330-861, Korea, Republic of (South Korea)

    Youn-Hee Han

  2. , Division of Computer Science and Enginee, SoonChunHyang University, Sinchang, Chungnam, 336-745, Korea, Republic of (South Korea)

    Doo-Soon Park

  3. , Dept of Computer Science, City University of Hong Kong, Tat Chee Avenue, Kowloon, 83, Hong Kong SAR

    Weijia Jia

  4. , Division of Computer Engineering, Mokwon University, Do-An-Buk-Ro 88, Daejeon, 302-729, Korea, Republic of (South Korea)

    Sang-Soo Yeo

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Li, Y., Kim, G., Wen, L., Bae, H. (2013). MHB-Tree: A Distributed Spatial Index Method for Document Based NoSQL Database System. In: Han, YH., Park, DS., Jia, W., Yeo, SS. (eds) Ubiquitous Information Technologies and Applications. Lecture Notes in Electrical Engineering, vol 214. Springer, Dordrecht. https://doi.org/10.1007/978-94-007-5857-5_53

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  • DOI: https://doi.org/10.1007/978-94-007-5857-5_53

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  • Publisher Name: Springer, Dordrecht

  • Print ISBN: 978-94-007-5856-8

  • Online ISBN: 978-94-007-5857-5

  • eBook Packages: EngineeringEngineering (R0)

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