RFID数据仓库上的多时空粒度近似聚集查询

Multi-granularity Temporal and Spatial Approximate Aggregate Query on RFID Data Warehouse

随着物联网的发展,以RFID为代表的物联网传感器数据的存储、查询、处理等课题正成为研究的热点。结合数据仓库时空维度和列存储的思想,建立了一种列式RFID数据仓库,并根据RFID的时空特性,设计了一种支持连续聚集查询的多时空粒度数据结构和快速更新算法。它去除了传统聚集查询的部分冗余操作,适合处理大规模RFID数据仓库上的连续实时聚集查询。通过实验证明,该模型与算法在一些典型的物联网应用中取得了较高的效率,可广泛地适用于海量RFID数据仓库上的OLAP分析。

With the development of Internet of Things（IOT）,the research concerning storage,query,processing,etc.of sensor data,such as RFID,is becoming more and more popular.In this paper,with the thoughts of temporal and spatial dimensions in data warehouse and column-style storage,we built a column-style warehouse for RFID data.Moreover,according to the temporal and spatial characteristics of RFID data,we designed a data structure for continuousaggregate query of multiple temporal and spatial granularity and a fast updating algorithm,which can remove a part of redundant operation in traditional aggregate query.The structure and algorithm can be applied for processing large-scale continuous aggregate query in RFID data warehouse.The experiment results show that the model and algorithm can achieve high efficiency in some typical application of IOT（Internet of Things）,and can be widely applied to massive data OLAP analysis in RFID data warehouse.