Dai Hai Ton That
Skip Abstract Section
Abstract
Due to several important features, such as high performance, low power consumption, and shock resistance, NAND flash has become a very popular stable storage medium for embedded mobile devices, personal computers, and even enterprise servers. However, the peculiar characteristics of flash memory require redesigning the existing data storage and indexing techniques that were devised for magnetic hard disks.
In this article, we propose TRIFL, an efficient and generic TRajectory Index for FLash. TRIFL is designed around the key requirements of trajectory indexing and flash storage. TRIFL is generic in the sense that it is efficient for both simple flash storage devices such as SD cards and more powerful devices such as solid state drives. In addition, TRIFL is supplied with an online self-tuning algorithm that allows adapting the index structure to the workload and the technical specifications of the flash storage device to maximize the index performance. Moreover, TRIFL achieves good performance with relatively low memory requirements, which makes the index appropriate for many application scenarios. The experimental evaluation shows that TRIFL outperforms the representative indexing methods on magnetic disks and flash disks.
- Devesh Agrawal, Deepak Ganesan, Ramesh Sitaraman, Yanlei Diao, and Shashi Singh. 2009. Lazy-adaptive tree: An optimized index structure for flash devices. PVLDB 2, 1 (2009), 361--372. Google Scholar
Digital Library
- Victor T. D. Almeida and Ralf H. Guting. 2005. Indexing the trajectories of moving objects in networks. GeoInformatica 9, 1 (2005), 33--60. Google ScholarDigital Library
- Nicolas Anciaux, Luc Bouganim, Philippe Pucheral, Yanli Guo, Lionel L. Folgoc, and Shaoyi Yin. 2014. MILo-DB: A personal, secure and portable database machine. Distributed and Parallel Databases 32, 1 (2014), 37--63. Google ScholarDigital Library
- Viorica Botea, Daniel Mallett, Mario A. Nascimento, and Jorg Sander. 2008. PIST: An efficient and practical indexing technique for historical spatio-temporal point data. GeoInformatica 12, 2 (2008), 143--168. Google ScholarDigital Library
- Thomas Brinkhoff. 2002. A framework for generating network-based moving objects. GeoInformatica 6, 2 (2002), 153--180. Google ScholarDigital Library
- V. P. Chakka, Adam Everspaugh, and Jignesh M. Patel. 2003. Indexing large trajectory data sets with SETI. In CIDR 2003.Google Scholar
- Xihui Chen and Jun Pang. 2013. Protecting query privacy in location-based services. Geoinformatica 18, 1 (2013), 95--133. Google ScholarDigital Library
- Delphine Christin, Andreas Reinhardt, Salil S. Kanhere, and Matthias Hollick, 2011. A survey on privacy in mobile participatory sensing applications. Journal of Systems and Software 84, 11 (2011), 1928--1946. Google ScholarDigital Library
- Philippe Cudré-Mauroux, Eugene Wu, and Samuel Madden. 2010. TrajStore: An adaptive storage system for very large trajectory data sets. In ICDE 2010, 109--120.Google ScholarCross Ref
- Raghu K. Ganti, Fan Ye, and Hui Lei. 2011. Mobile crowdsensing: Current state and future challenges. IEEE Communications Magazine 49, 11 (2011), 32--39.Google ScholarCross Ref
- Glaros.dtc.umn.edu. 2014. METIS—Family of Multilevel Partitioning Algorithms. Retrieved May 7, 2014 from http://glaros.dtc.umn.edu/gkhome/views/metis.Google Scholar
- Ralf H. Güting and Markus Schneider. 2005. Moving Objects Databases. Morgan Kaufmann.Google Scholar
- Salil S. Kanhere. 2013. Participatory sensing: Crowdsourcing data from mobile smartphones in urban spaces. Distributed Computing and Internet Technology. 7753 (2013), 19--26.Google ScholarCross Ref
- Marcel Kornacker and Douglas Banks. 1995. High-concurrency locking in R-trees. In VLDB 1995, 134--145. Google ScholarDigital Library
- George Karypis and Vipin Kumar. 1999. A fast and highly quality multilevel scheme for partitioning irregular graphs. SIAM Journal on Scientific Computing 20, 1 (1999), 359--392. Google ScholarDigital Library
- George Kollios, Vassilis J. Tsotras, Dimitrios Gunopulos, Alex Delis, and Marios Hadjieleftheriou. 2000. Indexing animated objects using spatiotemporal access methods. IEEE Transactions on Knowledge and Data Engineering (TKDE 2000) 13, 5 (2000), 758--777. Google ScholarDigital Library
- Nicholas D. Lane, Emiliano Miluzzo, Hong Lu, Daniel Peebles, Tanzeem Choudhury, and Andrew T. Campbell. 2010. A survey of mobile phone sensing. IEEE Communications Magazine 48, 9 (2010), 140--150. Google ScholarDigital Library
- Sang-W. Lee and Bongki Moon. 2007. Design of flash-based DBMS: An in-page logging approach. In ACM SIGMOD 2007, 55--66. Google ScholarDigital Library
- Philip L. Lehman and S. B. Yao. 1981. Efficient locking for concurrent operations on B-trees. ACM Transactions on Database Systems (TODS) 6, 4 (1981), 650--670. Google ScholarDigital Library
- Yinan Li, Bingsheng He, Robin J. Yang, Qiong Luo, and Ke Yi. 2010. Tree indexing on solid state drives. VLDB J (2010) 3, 1 (2010), 1195--1206. Google ScholarDigital Library
- Yinan Li, Bingsheng He, Robin J. Yang, Qiong Luo, and Ke Yi. 2014. FD-Tree: A Tree Index on Solid State Drives. Retrieved May 7, 2014 from http://pages.cs.wisc.edu/∼yinan/fdtree.html.Google Scholar
- Dan Lin, Christian S. Jensen, Beng C. Ooi, and Simonas Saltenis. 2005. Efficient indexing of the historical, present, and future positions of moving objects. In Proceedings of the 6th International Conference on Mobile Data Management (MDM’05). 59--66. Google ScholarDigital Library
- Song Lin, Demetrios Zeinalipour-Yazti, Vana Kalogeraki, Dimitrios Gunopulos, and Walid A. Najjar. 2006. Efficient indexing data structures for flash-based sensor devices. ACM Transactions on Storage 2, 4 (2006), 468--503. Google ScholarDigital Library
- Mohamed F. Mokbel and Walid G. Aref. 2007. Location-aware query processing and optimization. In Proceedings of the International Conference on Mobile Data Management (MDM’07). 229. Google ScholarDigital Library
- Mohamed F. Mokbel, Thanaa M. Ghanem, and Walid G. Aref. 2003. Spatio-temporal access methods. IEEE Data Engineering Bulletin 26, 2 (2003), 40--49.Google Scholar
- Mohamed F. Mokbel, Louai Alarabi, Jie Bao, Ahmed Eldawy, Amr Magdy, Mohamed Sarwat, Ethan Waytas, and Steven Yackel. 2013. MNTG: An extensible web-based traffic generator. In Proceedings of the 13th International Conference on Advances in Spatial and Temporal Databases (SSTD’13), 38--55. Google ScholarDigital Library
- L-V. Nguyen-Dinh, Walid G. Aref, and Mohamed. F. Mokbel. 2010. Spatio-temporal access methods: Part 2 (2003--2010). IEEE Data Engineering Bulletin 33, 2 (2010), 46--55.Google Scholar
- Ocz.com. 2014. OCZ, SSD OCZ Vertex 4 SATA 3, Specifications. Retrieved May 7, 2014 from http://ocz.com/consumer/vertex-4-sata-3-ssd/specifications.Google Scholar
- Patrick O’Neil, Edward Cheng, Dieter Gawlick, and Elizabeth O’Neil. 1996. The log-structured merge-tree (LSM-tree). Acta Informatica 33, 4 (1996), 351--385. Google ScholarDigital Library
- Balaji Palanisamy and Ling Liu. 2011. MobiMix: Protecting location privacy with mix-zones over road networks. In 2011 IEEE 27th International Conference on Data Engineering (ICDE’11). Google ScholarDigital Library
- Jignesh M. Patel, Yun Chen, and V. P. Chakka. 2004. STRIPES: An efficient index for predicted trajectories. In SIGMOD 2004, 635--646. Google ScholarDigital Library
- Mindaugas Pelanis, Simonas Saltenis, and Christian S. Jensen. 2006. Indexing the past, present, and anticipated future positions of moving objects. ACM Transactions on Database Systems (TODS) 31, 1 (2006), 255--298. Google ScholarDigital Library
- Hongchan Roh, Sanghyun Park, Sungho Kim, Mincheol Shin, and Sang-W. Lee. 2011. B+-tree index optimization by exploiting internal parallelism of flash-based solid state drives. PVLDB 5, 4 (2011), 286--297. Google ScholarDigital Library
- Simonas Saltenis, Christian S. Jensen, Scott T. Leutenegger, and Mario A. Lopez. 2000. Indexing the positions of continuously moving objects. ACM SIGMOD Record 29, 2 (2000), 331--342. Google ScholarDigital Library
- Iulian Sandu Popa, Karine Zeitouni, Vincent Oria, Dominique Barth, and SandrineVial. 2010. PARINET: A tunable access method for in-network trajectories. In ICDE 2010, 177--188.Google Scholar
- Iulian Sandu Popa, Karine Zeitouni, Vincent Oria, Dominique Barth, and Sandrine Vial. 2011. Indexing in-network trajectory flows. VLDB Journal 20, 5 (2011), 643--669. Google ScholarDigital Library
- Mohamed Sarwat, Mohamed F. Mokbel, Xun Zhou, and Suman Nath. 2011. FAST: A generic framework for flash-aware spatial trees. In SSTD 2011, 149--167. Google ScholarDigital Library
- Mohamed Sarwat, Mohamed F. Mokbel, Xun Zhou, and Suman Nath. 2013. Generic and efficient framework for search trees on flash memory storage systems. GeoInformatica 17, 3 (2013), 417--448. Google ScholarDigital Library
- Patrick Schmid and Achim Roos. 2014. SDXC/SDHC Memory Cards, Rounded Up and Benchmarked. Retrieved May 7, 2014 from http://tinyurl.com/tom-sdxc.Google Scholar
- Russell Sears and Raghu Ramakrishnan. 2012. bLSM: A general purpose log structured merge tree. In Proceedings of the SIGMOD Conference. 217--228. Google ScholarDigital Library
- Yufei Tao and Dimitris Papadias. 2001. MV3R-Tree: A spatio-temporal access method for timestamp and interval queries. In VLDB 2001, 431--440. Google ScholarDigital Library
- Yufei Tao, Dimitris Papadias, and Jimeng Sun. 2003. The TPR*-tree: An optimized spatio-temporal access method for predictive queries. In VLDB (2003), 790--801. Google ScholarDigital Library
- Arvind Thiagarajan, James Biagioni, Tomas Gerlich, and Jakob Eriksson. 2010. Cooperative transit tracking using smartphone. In Sensys. 85--98. Google ScholarDigital Library
- Nicolas Tsiftes and Adam Dunkels. 2011. A database in every sensor. In SenSys. 316--332. Google ScholarDigital Library
- Baobing Wang and John S. Baras. 2013. Hybridstore: An efficient data management system for hybrid flash-based sensor devices. In Proceedings of the 10th European Conference on Wireless Sensor Networks (EWSN’13), 50--66. Google ScholarDigital Library
- Chin-H. Wu, Tei-W. Kuo, and Li P. Chang. 2007. An efficient B-tree layer implementation for flash-memory storage systems. ACM Transactions on Embedded Computing Systems 6, 3 (2007). Google ScholarDigital Library
- Shaoyi Yin, Philippe Pucheral, and Xiaofeng Meng. 2009. A sequential indexing scheme for flash-based embedded systems. In EDBT 2009. 588--599. Google ScholarDigital Library
- Yu Zheng, Lizhu Zhang, Xing Xie, and Wei-Y. Ma. 2009. Mining interesting locations and travel sequences from GPS trajectories. In Proceedings of the International Conference on World Wide Web (WWW’09). 791--800. Google ScholarDigital Library
Index Terms
- TRIFL: A Generic Trajectory Index for Flash Storage
Recommendations
GCOTraj: A storage approach for historical trajectory data sets using grid cells ordering
AbstractVast amounts of trajectory data have been collected due to the popularity of GPS devices. Analyzing this wealth of data is important, thus highlighting the need to efficiently index and store this large amount of data on secondary ...
Editorial: An efficient index buffer management scheme for implementing a B-tree on NAND flash memory
Recently, NAND flash memory has been one of the best storage mediums for various embedded systems such as MP3 players, mobile phones and laptops because of its shock-resistant, low-power consumption, and none-volatile properties. However, since it has ...
PFFS: a scalable flash memory file system for the hybrid architecture of phase-change RAM and NAND flash
SAC '08: Proceedings of the 2008 ACM symposium on Applied computingIn this paper, we present the scalable and efficient flash file system using the combination of NAND and Phase-change RAM (PRAM). Until now, several flash file systems have been developed considering the physical characteristics of NAND flash. However, ...
Comments