A Review on Bloom Filter Based Approaches for RFID Data Cleaning
This paper provides comprehensive review about data cleaning for RFID data streams. It serves the purpose to understand the current undertakings to ensure data quality in RFID. It focused on three major RFID data issues which are noise readings, duplicate readings and missed readings. It includes in-depth analysis on existing approaches specifying on Bloom filter based approaches. This literature can be used by researcher to understand the background of RFID data filtering, the challenges and expectation in the future.
KeywordsRFID Data filtering Noise reading Missed reading Duplicate reading Bloom filter
Unable to display preview. Download preview PDF.
This work is sponsored by Ministry of Education Malaysia and Universiti Tun Hussein Onn Malaysia.
- 1.Chawla, V., Ha, D.S.: An overview of passive RFID. IEEE Communications Magazine, vol. 45, pp.11-17 (2007) Google Scholar
- 2.Clampitt, H.G.: RFID Certification Textbook. 3rd edition, American RFID Solution, LLC, (2007)Google Scholar
- 3.Darcy, P., Stantic, B., Sattar, A.: A fusion of data analysis and non-monotonic reasoning to restore missed RFID readings. In Proceedings of the 5th International Conference on Intelligent Sensors, Sensor Networks and Information Processing, pp.313-318, Melbourne, Victoria, (2009)Google Scholar
- 4.Nogee, A.: RFID tags and chips: Opportunities in the second generation. In-Stat/MDR Reports (2005)Google Scholar
- 5.Derakhshan, R., Orlowska, M., Li, X.: RFID data management: challenges and opportunities. In Proceedings of the IEEE International Conference on RFID, pp. 175-182, Grapevine, Texas (2007)Google Scholar
- 6.Jeffery, S. R., Alonso, G., Franklin, M.J., Hong, W., Widom, J.: A pipelined framework for online cleaning of sensor data streams. In Proceedings of the 22nd International Conference on Data Engineering, p. 140, Atlanta, Georgia, (2006)Google Scholar
- 7.Leong, K. S., Ng, M. L., Grasso, A. R., Cole, P. H.: Synchronization of RFID readers for dense RFID reader environments. In Proceedings of the International Symposium on Applications and the Internet Workshops, pp. 48-51, Phoenix, Arizona (2006)Google Scholar
- 8.Azambuja, M.C.d., Jung, C.F., Caten, C.S., Hessel, F.P.: RFID-Env: Methods and software simulation for RFID environments. Business Process Management Journal, 16, 1014 – 1038 (2010)Google Scholar
- 9.Bai, Y., Wang, F., Liu, P.: Efficiently filtering RFID data streams. In Proceedings of the CleanDB Workshop, pp. 50-57, Seoul, South Korea (2006)Google Scholar
- 10.Bloom, B.: Space/Time tradeoffs in hash coding with allowable errors. Commun. ACM, 13, 422–426 (1970)Google Scholar
- 11.DdddGoogle Scholar
- 12.Wang, X., Zhang, Q., Jia, Y.: Efficiently filtering duplicates over distributed data streams. In Proceedings of the International Conference on Computer Science and Software Engineering, Wuhan, Hubei, 12-14 Dec. 2008; pp. 631 – 634.Google Scholar
- 13.Mahdin, H., Abawajy, J.: An Approach for Removing Redundant Data from RFID Data Streams. Sensors, 11, 9863-9877 (2011).Google Scholar
- 14.Shen H., Zhang Y.: Improved approximate detection of duplicates for data streams over sliding windows. Journal of Computer Science and Technology, 23, 973–987 (2008).Google Scholar
- 15.Fan L., Cao P., Almeida J., Broder A.Z.: Summary cache: A Scalable Wide-Area Web Cache Sharing Protocol. IEEE/ACM Trans. Networking, 8, 281-293 (2000)Google Scholar