Browse > Article
http://dx.doi.org/10.7236/IJIBC.2022.14.1.95

A New Flash TPR-tree for Indexing Moving Objects with Frequent Updates  

Lim, Seong-Chae (Dept. of Computer Science, Dongduk Women's University)
Publication Information
International Journal of Internet, Broadcasting and Communication / v.14, no.1, 2022 , pp. 95-104 More about this Journal
Abstract
A TPR-tree is a well-known indexing structure that is developed to answer queries about the current or future time locations of moving objects. For the purpose of space efficiency, the TPR-tree employs the notion of VBR (velocity bounding rectangle)so that a regionalrectangle presents varying positions of a group of moving objects. Since the rectangle computed from a VBR always encloses the possible maximum range of an indexed object group, a search process only has to follow VBR-based rectangles overlapped with a given query range, while searching toward candidate leaf nodes. Although the TPR-tree index shows up its space efficiency, it easily suffers from the problem of dead space that results from fast and constant expansions of VBR-based rectangles. Against this, the TPR-tree index is enforced to update leaf nodes for reducing dead spaces within them. Such an update-prone feature of the TPR-tree becomes more problematic when the tree is saved in flash storage. This is because flash storage has very expensive update costs. To solve this problem, we propose a new Bloom filter based caching scheme that is useful for reducing updates in a flash TPR-tree. Since the proposed scheme can efficiently control the frequency of updates on a leaf node, it can offer good performance for indexing moving objects in modern flash storage.
Keywords
Flash memory; TPR-tress; Moving object databases; Indexing scheme;
Citations & Related Records
Times Cited By KSCI : 1  (Citation Analysis)
연도 인용수 순위
1 Jianzhong Qi, Rui Zhang, Christian S. Jensen, Kotagiri Ramamohanarao, and Jiayuan HE, "Continuous Spatial Query Processing: A survey of Safe Region based Techniques," ACM Computer Surveys, Vol. 51, No. 3, pp. 1-39, May 2019. DOI : doi.org/10.1145/3193835   DOI
2 Laura M. Grupp, John D. Davis, and Steven Swanson, "The Bleak Future of NAND Flash Memory," in Proc. of the USENIX Conference on File and Storage, Feb. 2012.
3 John Colgrove, et at., "Purity: Building Fast, Highly-Available Enterprise Flash Storage from Commodity Components," in Proc. of SIGMOD, pp. 1683-1694, May 2015. DOI : doi.org/10.1145/2723372.2742798   DOI
4 B. H. Bloom, "Space/time Trade-offs in Hash Coding with Allowable Errors," Communications of the ACM, Vol. 13, No. 7, pp. 422-426, 1970.   DOI
5 B. Donnet, P. Raoult, T. Friedman, and M. Crovella, "Efficient Algorithms for Large-scale Topology Discovery," in Proc. of ACM SIGMETRICS, pp. 327-338, June. 2005. DOI: doi.org/10.1145/1071690.1064256   DOI
6 Hendawi A.M., Bao J., Mokbel M.F., and Ali M., "Predictive Tree: An Efficient Index for Predictive Queries on Road Networks," in Proc. of ACM ICDE, pp. 1215-1226, 2015. DOI: 10.1109/ICDE.2015.7113369   DOI
7 Benoit Donnet, Bruno Baynat, and Timur Friedman , "Retouched Bloom filters: Allowing Networked Applications to Trade off Selected False Positives against False Negatives," in Proc. of ACM CoNEXT, pp. 1-12, December 2006. DOI : doi.org/10.1145/1368436.1368454   DOI
8 Deke Guo, Jie Wu, Honghui Chen, Ye Yuan, and Xueshan Luo, "The Dynamic Bloom Filters," IEEE Trans. on Knowledge and Data Engineering, Vol. 22, No. 3, pp. 120-133. January 2010. DOI : 10.1109/TKDE.2009.57   DOI
9 Sungchae Lim , "F2B+-tree: A Flash-aware B+-tree Using the Bloom Filter," Asia-pacific Journal of Convergent Research Interchange, Vol.6, No.7, pp. 21-28, July 2020. DOI : 10.47116/apjcri.2020.07.03   DOI
10 Yongkun Wang, Kazuo Goda, and Masaru Kitsuregawa, "Evaluating Non-In-Place Update Techniques for Flash-Based Transaction Processing Systems," in Proc. of DEXA, pp. 777-791, 2009.
11 Seong-Chae Lim, "An Indexing Scheme for Predicting Future-time Positions of Moving Objects with Frequently Varying Velocities," Journal of the Korea Society of Computer and Information, Vol.15 No. 5, pp. 23 - 31, 2012. DOI : doi.org/10.9708/jksci.2010.15.5.023   DOI
12 Thi Nguyen, Zhen He, Rui Zhang, and Phillip Ward, "Boosting Moving Object Indexing through Velocity Partitioning," in Proc. of the VLDB Endowment, pp. 860-871, May 2012. DOI : doi.org/10.14778/2311906.2311913   DOI
13 Rslan E., Hameed H.A., and Ezzat E., "Spatial R-tree Index based on Grid Division for Query Processing," International Journal of Database Management Systems, Vol. 9, No. 6, pp. 25-36, 2017. DOI : 10.5121/ijdms.2017.9602   DOI
14 Koide S., Tadokoro Y., Yoshimura T., and Xiao C., "Enhanced Indexing and Querying of Trajectories in Road Networks via String Algorithms," ACM Trans. Spatial Algorithms Systems, Vol. 4, No. 1, pp. 1-41, 2018. DOI : doi.org/10.1145/3200200   DOI
15 Stephan Baumann, Giel de Nijs, Michael Strobel, and Kai-Uwe Sattler, "Flashing Databases: Expectations and Limitations," in Proc. of ACM DaMon, pp. 9-18, June, 2010.
16 Sungchae Lim, "A New Flash-based B+-tree with Very Cheap Update Operations on Leaf Nodes," in Proc. of International Conference on Engineering Technologies and Big Data Analytics, pp. 45-49, January 2016. DOI : dx.doi.org/10.15242/IIE.E0116022   DOI
17 Tseng-Yi Chen, Yuan-Hao Chang, Yuan-Hung Kuan, Ming-Chang Yang, Yu-Ming Chang, and Pi-Cheng Hsiu, "Enhancing Flash Memory Reliability by Jointly Considering Write-back Pattern and Block Endurance," ACM Transactions on Design Automation of Electronic Systems, Vol. 23, No. 5, pp 1-24, September 2018. DOI : doi.org/10.1145/3229192   DOI
18 Woon-Hak Kang, Sang-Won Lee, and Bongki Moon, "Flash-based Extended Cache for Higher Throughput and Faster Recovery," Journal of the VLDB Endowment, Vol. 5, No. 11, pp. 1615-1626, 2012.   DOI