EVALUATION OF KNOWLEDGE-BASED QUERY TREE PROTOCOLS WITH DIFFERENT RFID TAG DISTRIBUTIONS

Abstract

Tag query in RFID systems is a key operation for identifying tags that appear in the reader’s interrogation zone. Many tag query protocols have been proposed; however, reducing the number of collision slots often comes at the cost of increasing the number of idle slots. In certain deployment scenarios, the number of tags, the tag ID space, and the tag distribution can be known in advance; this information constitutes knowledge and has been exploited in several knowledge-based query algorithms. This paper evaluates knowledge-based query tree protocols under different tag distributions: uniform and non-uniform. Implementation results show that knowledge-based query tree protocols consistently achieve better query efficiency than the traditional query tree protocol, with QTKS and QTKS_TE providing the best performance. The analytical and implementation results also indicate that the more knowledge is exploited in the protocols, the higher the achievable query efficiency.