Title :
Filtering Redundant RFID Data Based on Sliding Windows
Author :
Wu Rui ; Liao Guoqiong ; Di Guoqiang
Author_Institution :
Sch. of Inf. Technol., Jiangxi Univ. of Finance & Econ., Nanchang, China
Abstract :
Filtering redundancy data is an important task of radio frequency identification (RFID) middleware. In order to ensure RFID middleware can effectively filter the time redundant data and identify tagged object location change timely, this paper proposed a Temporal-Spatial bloom filter based on the sliding window model. The filter extends the one-dimension array in the standard bloom filter to a two-dimension array. Meanwhile, in order to guarantee the false positive rate doesn´t increase due to the reason that the storage unit of the filter becomes full, we proposed a random decay strategy for deleting the expiration elements. The experimental results show that TSBF algorithm can filter time redundant data effectively and had a good performance to deal with location movement.
Keywords :
data structures; information filtering; middleware; radiofrequency identification; redundancy; spatial filters; TSBF algorithm; filtering redundant RFID data; radiofrequency identification middleware; sliding window model; tagged object location identification; temporal-spatial Bloom filter; time redundant data; two-dimension array; Algorithm design and analysis; Data models; Filtering algorithms; Information filters; Radiofrequency identification; Bloom Filter; Data Filtering; Data Stream; RFID;
Conference_Titel :
Management of e-Commerce and e-Government (ICMeCG), 2014 International Conference on
DOI :
10.1109/ICMeCG.2014.46