An approximate duplicate elimination in RFID data streams

摘要

The RFID technology has been applied to a wide range of areas since it does not require contact in detecting RFID tags. However, due to the multiple readings in many cases in detecting an RFID tag and the deployment of multiple readers, RFID data contains many duplicates. Since RFID data is generated in a streaming fashion, it is difficult to remove duplicates in one pass with limited memory. We propose one pass approximate methods based on Bloom Filters using a small amount of memory. We first devise Time Bloom Filters as a simple extension to Bloom Filters. We then propose Time Interval Bloom Filters to reduce errors. Time Interval Bloom Filters need more space than Time Bloom Filters. We propose a method to reduce space for Time Interval Bloom Filters. Since Time Bloom Filters and Time Interval Bloom Filters are based on Bloom Filters, they do not produce false negative errors. Experimental results show that our approaches can effectively remove duplicates in RFID data streams in one pass with a small amount of memory.