Continuous Query Processing on Combined Data Stream: Sensor, Location and Identification

RFID has become one of the emerging technologies for a wide area of applications such as cold chain system and blood transportation. To support a safe transaction of tagged items in those systems, it is necessary to provide the history of item's status and location by using other devices, including a RFID sensor tag, GPS, and RTLS. Because of high communication cost to RFID middleware on the move, status and location of tagged items are simultaneously gathered by the RFID reader after they are stored in the tag memory. This information has characteristics of not only streaming data but bulk data. To prevent data loss by large amount of input data, therefore, RFID middleware should manage dynamically the size of queues for collecting data from readers. In this paper, we propose a queue resizing technique of RFID middleware in order to process combined data stream efficiently. Queue resizing adjusts queue size of each data source based on the size of collected data. Since proposed technique prevent data overflow by small queue size and memory loss by excessive static queue size, RFID middleware can process continuous queries for combined data stream in real-time.