Efficient Protocols for Collecting Histograms in Large-Scale RFID Systems

摘要: Collecting histograms over RFID tags is an essential premise for effective aggregate queries and analysis in large-scale RFID-based applications. In this paper we consider efficient collection of from the massive number tags, without need to read all tag data. order achieve time efficiency, propose a novel, ensemble sampling-based method simultaneously estimate size categories. We first problem basic histogram collection, algorithm based on idea sampling. further problems advanced respectively, with iceberg query top- $k$ query. Efficient algorithms are proposed tackle above such that qualified/unqualified categories can be quickly identified. This framework very flexible compatible current tag-counting estimators, which efficiently leveraged each category. Experiment results indicate our solutions much better performance than estimation/identification schemes.