Efficient Transformation Scheme for Indexing Continuous Queries on RFID Streaming Data

Abstract

RFID data are usually regarded as streaming data that are huge and change frequently because they are gathered continuously by numerous readers. RFID middleware filters the data acquired from the readers to process queries from applications. To enhance the performance of the middleware, an index must be built to process the queries efficiently. Several approaches to building an index on queries rather than data records, called query index, have been proposed and are widely used to evaluate continuous queries over streaming data. EPCglobal proposed an event cycle specification (ECSpec) model, which is a standard query interface for RFID applications. The problem with using any of the query indexes in the ECSpec model is that it takes a long time to build the index and to process queries because each data consist of a large number of segments. To solve this problem, we propose an aggregate transformation that converts a group of segments into compressed data. Then, we measure the performance improvement of the index by the proposed technique using experimental evaluation.