Filtering Redundant RFID Data Based on Sliding Windows

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.