A Hierarchical Heterogeneous IoT Time Series Data Index for NVM

The index plays an important role in the performance of IoT time series data storage systems. However, the current index designed for HDD or SSD can not adapt to the characteristics of IoT time series data and effectively leverage the performance advantages of NVM. A new hierarchical heterogeneous index is designed for IoT time series storage system based on NVM. The structure is given first and the group consists of several data blocks used to manage IoT time series data. The ordered construction strategy is designed for skip list by the sustained generation of IoT time series data and creating the index for each IoT time series data block group. Meanwhile, a compression and reconstruction strategy for skip list is given to effectively utilize NVM. Then, a TS- Radix tree is presented to index IoT time series data block groups by the temporal characteristics of IoT time series data. Finally, a prototype of it is implemented and YCSB-TS is used to evaluate. The results show that this new index can effectively improve the throughput of random and range queries by up to 262.4^%, surpassing the performance of InfluxDB, OpenTSDB, and KairosDB.