• Journal of KIISE:Databases
• /
• v.36 no.3
• /
• pp.198-214
• /
• 2009

Trajectories of RFID tags can be modeled as a line, denoted by tag interval, captured by an RFID reader and indexed in a three-dimensional domain, with the axes being the tag identifier (TID), the location identifier (LID), and the time (TIME). Distribution of tag intervals in the domain space is an important factor for efficient processing of a query for tracing tags and is changed according to arranging coordinates of each domain. Particularly, the arrangement of LIDs in the domain has an effect on the performance of queries retrieving the traces of tags as times goes by because it provides the location information of tags. Therefore, it is necessary to determine the optimal ordering of LIDs in order to perform queries efficiently for retrieving tag intervals from the index. To do this, we propose LID proximity for reordering previously assigned LIDs to new LIDs and define the LID proximity function for storing tag intervals accessed together closely in index nodes when a query is processed. To determine the sequence of LIDs in the domain, we also propose a reordering scheme of LIDs based on LID proximity. Our experiments show that the proposed reordering scheme considerably improves the performance of Queries for tracing tag locations comparing with the previous method of assigning LIDs.

• Journal of Internet Computing and Services
• /
• v.10 no.2
• /
• pp.133-141
• /
• 2009

A tag collision problem occurs when many tags are placed in a interrogation zone in RFID system. A tag collision problem is one of core issues and various protocols have been proposed to solve the collision problems. Generally tree-based protocols generate unique prefixes and identify tags with them as quick as possible. In this paper, we propose the QT-BCS protocol which decreases the identification time by reducing the number of query-response. The QT-BCS protocol makes a prefixes using time slot and bit change sensing unit. This protocol compares the current bit of tags until the current bit is differ from the previous one. When this occurs, all of the bits scanned so far are transferred to slot-0 and slot-1 depending on the first bit value in Reader. Consequently, this method can reduce the number of queries by tracing prefixes easily. Simulation result shows QT-BCS is more efficient in identifying tags than Query Tree and 4-ary Query Tree protocol.

• Journal of KIISE:Databases
• /
• v.35 no.5
• /
• pp.432-446
• /
• 2008

Queries for tracing tag locations are among the most challenging requirements in RFID based applications, including automated manufacturing, inventory tracking and supply chain management. For efficient query processing, a previous study proposed the index scheme for storing tag objects, based on the moving object index, in 3-dimensional domain with the axes being the tag identifier, the reader identifier, and the time. In a different way of a moving object index, the ranges of coordinates for each domain are quite different so that the distribution of query regions is skewed to the reader identifier domain. Previous indexes for tags, however, do not consider the skewed distribution for query regions. This results in producing many overlaps between index nodes and query regions and then causes the problem of traversing many index nodes. To solve this problem, we propose a new disproportional insertion and split policy of the index for RFID tags which is based on the R*-tree. For efficient insertion of tag data, our method derives the weighted margin for each node by using weights of each axis and margin of nodes. Based the weighted margin, we can choose the subtree and the split method in order to insert tag data with the minimum cost. Proposed insertion method also reduces the cost of region query by reducing overlapped area of query region and MBRs. Our experiments show that the index based on the proposed insertion and split method considerably improves the performance of queries than the index based on the previous methods.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
• /
• 2007.10a
• /
• pp.578-581
• /
• 2007

For tracing tag locations, a trajectories should be modeled and indexed in radio frequency identification (RFID) systems. The trajectory of a tag can be represented as a line that connects two spatiotemporal locations captured when the tag enters and leaves the vicinity of a reader. If a tag enters but does not leave a reader, its trajectory is represented only as a point captured at entry. Because the information that the tag stays in the reader is missing from the trajectory represented only as a point, we should extend the region of a query to find the tag that remains in a reader. In this paper, we propose an interval data model of tag's trajectory in order to solve the problem. Trajectories of tags are represented as two kinds of intervals; dynamic intervals which are time-dependent lines and static intervals which are fixed lines. We also show that the interval data model has better performance than others with a cost model

• Journal of Korea Spatial Information System Society
• /
• v.7 no.2 s.14
• /
• pp.67-79
• /
• 2005

For tracing tag locations, the trajectories should be modeled and indexed in a radio frequency identification (RFID) system. The trajectory of a tag is represented as a line that connects two spatiotemporal locations captured when the tag enters and leaves the vicinity of a reader. If a tag enters but does not leave a reader, its trajectory is represented only as a point captured at entry. Because the information that a tag stays in a reader is missing from the trajectory represented only as a point, it is impossible to find the tag that remains in a reader. To solve this problem we propose the data model in which trajectories are defined as intervals and new index scheme called the Interval R-tree. We also propose new insert and split algorithms to enable efficient query processing. We evaluate the performance of the proposed index scheme and compare it with the R-tree and the R*-tree. Our experiments show that the new index scheme outperforms the other two in processing queries of tags on various datasets.