Efficient Information Sampling in Multi-Category RFID Systems

In RFID-enabled applications, when a tag is put into use and associated with a specific object, the category-related information (e.g., the brands of clothes) about this object might be preloaded into the tag’s memory for the purpose of live query. Since such information reflects category attributes, all tags in the same category carry identical category information. To collect this information, we do not need to repeatedly interrogate each tag; one tag’s response in a category is sufficient. In this paper, we investigate the problem of category information collection in a multi-category RFID system, which is referred to as information sampling . We propose two time-efficiency protocols. The first is a two-phase sampling protocol (TPS) that works in the case of knowing tag IDs. By quickly zooming into a category and isolating a tag from this category, TPS is able to sample a category with small overhead. The second protocol, called back-and-forth sampling protocol (BFS), relaxes a key assumption in TPS and performs the sampling task efficiently without knowing any tag IDs or category IDs. By carrying out a step-forward frame and using the step-backward scheme, BFS is able to interrogate only 1.45 tags (close to the lower bound of one tag) on average for each category. We theoretically analyze the protocol performance of TPS and BFS and discuss the optimal parameter settings that minimize the overall execution time. Extensive simulations show that both the protocols outperform the benchmark, greatly improving the sampling performance.