摘要：RFID middleware collects and filters RFID streaming data gathered continuously by numerous readers to process requests from applications. These requests are called continuous queries. The problem when using any of the existing query indexes on these continuous queries is that it takes a long time to build the index because it is necessary to insert a large number of segments into the index. KDB-tree is an index which can dispose multidimensional data. It is also a dynamic balance tree that has a good query performance and high spatial usage. This paper propose an aggregate transformation algorithm for querydata filtering, and applies KDB-tree into RFID event filtering to improve the performance of query. Comparing to other indexes, the result of simulation shows that KDB-tree index outperforms others in synthesized consideration of storage cost, insertion time cost and query time cost. In particular the query time cost of KDB-tree is distinctly lower than others because it provides single path traverse in the query process.
