Journal of Information Systems Engineering and Management

A Comparative Study on the Performance of the IB+ Tree and the I2B+ Tree
Edgar Carneiro 1 2, Alexandre Valle de Carvalho 1 2 * , Marco Amaro Oliveira 1
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1 INESCTEC, Campus da FEUP, R. Dr. Roberto Frias, 4200-465 Porto, PORTUGAL
2 FEUP, R. Dr. Roberto Frias, 4200-465 Porto, PORTUGAL
* Corresponding Author
Research Article

Journal of Information Systems Engineering and Management, 2021 - Volume 6 Issue 3, Article No: em0142
https://doi.org/10.21601/jisem/11007

Published Online: 23 Jun 2021

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How to cite this article
APA 6th edition
In-text citation: (Carneiro et al., 2021)
Reference: Carneiro, E., de Carvalho, A. V., & Oliveira, M. A. (2021). A Comparative Study on the Performance of the IB+ Tree and the I2B+ Tree. Journal of Information Systems Engineering and Management, 6(3), em0142. https://doi.org/10.21601/jisem/11007
Vancouver
In-text citation: (1), (2), (3), etc.
Reference: Carneiro E, de Carvalho AV, Oliveira MA. A Comparative Study on the Performance of the IB+ Tree and the I2B+ Tree. J INFORM SYSTEMS ENG. 2021;6(3):em0142. https://doi.org/10.21601/jisem/11007
AMA 10th edition
In-text citation: (1), (2), (3), etc.
Reference: Carneiro E, de Carvalho AV, Oliveira MA. A Comparative Study on the Performance of the IB+ Tree and the I2B+ Tree. J INFORM SYSTEMS ENG. 2021;6(3), em0142. https://doi.org/10.21601/jisem/11007
Chicago
In-text citation: (Carneiro et al., 2021)
Reference: Carneiro, Edgar, Alexandre Valle de Carvalho, and Marco Amaro Oliveira. "A Comparative Study on the Performance of the IB+ Tree and the I2B+ Tree". Journal of Information Systems Engineering and Management 2021 6 no. 3 (2021): em0142. https://doi.org/10.21601/jisem/11007
Harvard
In-text citation: (Carneiro et al., 2021)
Reference: Carneiro, E., de Carvalho, A. V., and Oliveira, M. A. (2021). A Comparative Study on the Performance of the IB+ Tree and the I2B+ Tree. Journal of Information Systems Engineering and Management, 6(3), em0142. https://doi.org/10.21601/jisem/11007
MLA
In-text citation: (Carneiro et al., 2021)
Reference: Carneiro, Edgar et al. "A Comparative Study on the Performance of the IB+ Tree and the I2B+ Tree". Journal of Information Systems Engineering and Management, vol. 6, no. 3, 2021, em0142. https://doi.org/10.21601/jisem/11007
ABSTRACT
Index structures were often used to optimise fetch operations to external storage devices (secondary memory). Nowadays, this also holds for increasingly large amounts of data residing in main-memory (primary memory). Within this scope, this work focuses on index structures that efficiently insert, query and delete valid-time data from very large datasets. This work performs a comparative study on the performance of the Interval B+ tree (IB+ tree) and the Improved Interval B+ tree (I2B+ tree): a variant that improves the time-efficiency of the deletion operation by reducing the number of traversed nodes to access siblings. We performed an extensive analysis of the performance of two operations: insertions and deletions, on both index structures, using multiple datasets with growing volumes of data, distinct temporal distributions and tree parameters (time-split alpha and node order). Results confirm that the I2B+ tree globally outperforms the IB+ tree, since, on average, deletion operations are 7% faster, despite insertions requiring 2% more time. Furthermore, results also allowed to determine the key factors that augment the performance difference on deletions between both trees.
KEYWORDS
REFERENCES
  • Bozkaya, T. and Ozsoyoglu, Z. M. (1998). Indexing valid time intervals. In G. Quirchmayr, E. Schweighofer, & T. J. Bench-Capon (Eds.), Database and expert system applications (pp. 541-550). DEXA 1998. Lecture Notes in Computer Science, vol 1460. Springer, Berlin, Heidelberg. https://doi.org/10.1007/BFb0054512
  • Carneiro, E., Carvalho, A. V. d. and Oliveira, M. A. (2020). I2B+tree: Interval B+ tree variant towards fast indexing of time-dependent data. 2020 15th Iberian Conference on Information Systems and Technologies (CISTI), Sevilla, Spain, 2020, pp. 1-7. https://doi.org/10.23919/CISTI49556.2020.9140897
  • Carvalho, A. V. d., Oliveira, M. A. and Rocha, A. (2014). Improvements to efficient retrieval of very large temporal datasets with the TravelLight method. s.l., 9th Iberian Conference on Information Systems and Technologies (CISTI). https://doi.org/10.1109/CISTI.2014.6876986
  • Comer, D. E. (1979). Ubiquitous B-Tree. ACM Computing Surveys, 11(2), 121-137. https://doi.org/10.1145/356770.356776
  • Cudre-Mauroux, P., Wu, E. and Madden, S., 2010. Trajstore: An adaptive storage system for very large trajectory data sets. 2010 IEEE 26th International Conference on Data Engineering (ICDE 2010), March, pp. 109-120. https://doi.org/10.1109/ICDE.2010.5447829
  • de Berg, M., van Kreveld, M., Overmars, M. and Schwarzkopf, O. (2008). Computational Geometry: Algorithms and Applications. Springer-Verlag. https://doi.org/10.1007/978-3-540-77974-2
  • Elmasri, R., Wuu, G. T. J. and Kim, Y.-J. (1990). The time index: An access structure for temporal data. Brisbane, Queensland, Australia, 16th International Conference on Very Large Data Bases.
  • Gamma, E., Helm, R., Johnson, R. and Vlissides, J. (1994). Design patterns: Elements of reusable object-oriented software. s.l.: Addison-Wesley Professional Computing Series, Pearson Education.
  • Goyal, M. (2009). Numerical Methods and Statistical Techniques Using ‘C’. s.l., Laxmi Publications.
  • Guo, T., Papaioannou, T. G. and Aberer, K. (2014). Efficient indexing and query processing of model-view sensor data in the cloud. Big Data Research, 1, 52-65. https://doi.org/10.1016/j.bdr.2014.07.005
  • Guttman, A. (1984). R trees: A dynamic index structure for spatial searching. ACM SIGMOD Record, 14. https://doi.org/10.1145/971697.602266
  • He, Z., Kraak, M.-J., Huisman, O., Ma. and Xiao, J. (2013). Parallel indexing technique for spatio-temporal data. International Journal of Photogrammetry and Remote Sensing, 78, 116-128. https://doi.org/10.1016/j.isprsjprs.2013.01.014
  • Katti, S. K. and Rao, A. V. (1968). Handbook of the poisson distribution. Technometrics, 10(2), 412-412. https://doi.org/10.1080/00401706.1968.10490580
  • Liu, Q. and Yuan, H., 2019. A high performance memory key-value database based on redis. Journal of Computers, 14, 170-183. https://doi.org/10.17706/jcp.14.3.170-183
  • Lock, H. C. and Booss, D. (2010). Indexing stored data. US, Patent No. 7,761,474.
  • Mahmood, A. R., Aly, A. M., Kuznetsova, T., Basalamah, S. and Aref, W. G. (2018). Disk-Based Indexing of Recent Trajectories. ACM Transactions on Spatial Algorithms and Systems, 4(3), 7. https://doi.org/10.1145/3234941
  • Mahmood, A. R., Punni, S. and Aref, W. G. (2019). Spatio-temporal access methods: a survey (2010 - 2017). Geoinformatica, 23(1), 1-36. https://doi.org/10.1007/s10707-018-0329-2
  • Nascimento, M. A. and Dunham, M. (1999). Indexing valid time databases via B/sup +/-trees. IEEE Transactions on Knowledge and Data Engineering, 11(6), 929-947. https://doi.org/10.1109/69.824609
  • Reinsel, D., Gantz, J. and Rydning, J. (2018). The digitization of the World – From edge to core, s.l.: Seagate, IDC Information and Data.
  • Theodoridis, Y., Silva, J. R. and Nascimento, M. A. (1999). On the generation of spatiotemporal datasets. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and LectureNotes in Bioinformatics), 1651, 147-164. https://doi.org/10.1007/3-540-48482-5_11
  • Valdés, F. and Güting, R. (2017). Index-supported pattern matching on tuples of time-dependent values. GeoInformatica, 21. https://doi.org/10.1007/s10707-016-0286-6
  • Vutukuri, T. R. (2018). Q+ IB+ tree: Indexing technique for moving regions (PhD thesis), Southern Illinois University.
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