The Internet of Things (IOT) has been widely applied in many fields, while the IOT data are always large volume, update frequently and inherently multi-dimensional, these characteristics bring big challenges to the traditional DBMSs. The traditional DBMSs have rich functionality and can deal with multi-attributes access efficiently, they can not scale good enough to deal with large volume data and can not support high insert throughput. The cloud-based database systems have good scalability, but they don't support multidimensional access natively.In order to deal with the large volume of IOT data, we propose an update and query efficient index framework (UQE-Index) based on key-value store that can support high insert throughput and provide efficient multi-dimensional query simultaneously.We implemented a prototype based on HBase and did comprehensive experiments to test our solution's scalability and efficiency.
Unlike EMINC and RT-CAN, the UQE-Index framework REF implements a three-level indexing structure atop HBase key-value store [8] .
An efficient index for massive IOT data in cloud environment
CIKM '12
Computer Science