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一种用于物联网时间序列数据库的新型非易失性存储器设备驱动程序。

A New NVM Device Driver for IoT Time Series Database.

作者信息

Cai Tao, Ma Yueming, Liu Peiyao, Niu Dejiao, Li Lei

机构信息

School of Computer Science and Communication Engineering, Jiangsu University, Zhenjiang 212000, China.

出版信息

Micromachines (Basel). 2022 Feb 27;13(3):385. doi: 10.3390/mi13030385.

Abstract

Numerous IoT devices in IoT systems collect data concurrently, which brings great challenges to IoT time series databases to store and manage these data. NVM device has high read-write speed compared with HDD and Flash-based SSD, and it is a possible way to solve the storage bottleneck. However, there are some limitations that should be solved such as the overhead of the I/O software stack for NVM devices and the lack of optimization for IoT time series databases in a Linux environment. By analyzing the characteristics of IoT time series databases and NVM devices, we optimized the device driver of NVM in Linux and provide a new structure of a NVM device driver for IoT time series databases. A multi-queue management strategy and a lightweight load balance mechanism based on frequency were designed to improve the concurrency and efficiency of NVM device drivers. The prototype of an IoT-oriented NVM device driver named TS-PMEM was implemented based on an open-source NVM device driver. Six prototypes were used for evaluation with YCSB-TS, a test tool for time series databases. Results showed that TS-PMEM can improve write throughput of the time series databases by 18.6%, query throughput by 10.6%, and reduce the write latency by 8.3% and query latency by 6.4%.

摘要

物联网系统中的众多物联网设备会同时收集数据,这给物联网时间序列数据库存储和管理这些数据带来了巨大挑战。与硬盘驱动器和基于闪存的固态硬盘相比,非易失性内存(NVM)设备具有较高的读写速度,这是解决存储瓶颈的一种可能途径。然而,仍有一些局限性需要解决,例如NVM设备的I/O软件栈开销以及在Linux环境中物联网时间序列数据库缺乏优化。通过分析物联网时间序列数据库和NVM设备的特性,我们优化了Linux中NVM的设备驱动程序,并为物联网时间序列数据库提供了一种新的NVM设备驱动程序结构。设计了一种多队列管理策略和基于频率的轻量级负载均衡机制,以提高NVM设备驱动程序的并发性和效率。基于开源NVM设备驱动程序实现了一个名为TS-PMEM的面向物联网的NVM设备驱动程序原型。使用六个原型通过时间序列数据库测试工具YCSB-TS进行评估。结果表明,TS-PMEM可以将时间序列数据库的写入吞吐量提高18.6%,查询吞吐量提高10.6%,并将写入延迟降低8.3%,查询延迟降低6.4%。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2ea7/8954946/d095f40835cc/micromachines-13-00385-g001.jpg

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