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- W3210390939 abstract "IoT time series data is an important form of big data. How to improve the efficiency of storage system is crucial for IoT time series database to store and manage massive IoT time series data from various IoT devices. Mixing NVM and SSD is an effective method to improve the I/O performance of storage systems. However, there are great differences between HDD and NVM or SSD. As a result, NVM and SSD cannot be directly used in the current time series database effectively. We design an IoT time series database with an embedded engine in storage device drivers for the hybrid solid-state storage system consisting of NVM and SSD. The I/O software stack of storing and managing IoT time series data can be shortened to improve the efficiency. Based upon the intrinsic characteristics of IoT time series data and different features of NVM and SSD, a redundancy elimination and compression fusion strategy, a hierarchical management strategy, and a heterogeneous time series data index are designed to improve the efficiency. Finally, a prototype of embedded IoT time series database named TS-NSM is implemented, and YCSB-TS is used to measure the IOPS. The results show that TS-NSM can improve the write IOPS up to 243.6 times and 174.3 times, respectively, compared with InfluxDB and OpenTSDB, and improve the read IOPS up to 10.1 times and 14.4 times, respectively." @default.
- W3210390939 created "2021-11-08" @default.
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- W3210390939 date "2021-10-25" @default.
- W3210390939 modified "2023-10-14" @default.
- W3210390939 title "The Embedded IoT Time Series Database for Hybrid Solid-State Storage System" @default.
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- W3210390939 doi "https://doi.org/10.1155/2021/9948533" @default.
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