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Summary
This summary is machine-generated.

Optimized Non-Volatile Memory (NVM) device drivers for Internet of Things (IoT) time series databases improve performance. The new TS-PMEM driver enhances data storage and retrieval efficiency for IoT systems.

Keywords:
I/O software stackIoTIoT time series databaseNVM storage systemstorage device driver

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Area of Science:

  • Computer Science
  • Data Storage Technologies
  • Database Systems

Background:

  • Internet of Things (IoT) systems generate vast amounts of concurrent data, challenging existing time series databases.
  • Non-Volatile Memory (NVM) offers high read-write speeds but faces limitations in IoT environments due to I/O software stack overhead and lack of specific optimizations.

Purpose of the Study:

  • To address the storage bottleneck in IoT time series databases by optimizing NVM device drivers.
  • To enhance the efficiency and concurrency of NVM device drivers for IoT data management within a Linux environment.

Main Methods:

  • Analyzed characteristics of IoT time series databases and NVM devices.
  • Developed an optimized NVM device driver structure for IoT time series databases in Linux.
  • Implemented a multi-queue management strategy and a lightweight, frequency-based load balancing mechanism.
  • Created a prototype named TS-PMEM based on an open-source NVM driver and evaluated it using YCSB-TS.

Main Results:

  • TS-PMEM improved write throughput by 18.6% and query throughput by 10.6%.
  • Write latency was reduced by 8.3%, and query latency decreased by 6.4%.
  • Demonstrated significant performance gains in handling IoT time series data.

Conclusions:

  • The optimized TS-PMEM NVM device driver effectively overcomes storage challenges in IoT time series databases.
  • The proposed driver structure and mechanisms enhance concurrency and efficiency for IoT data management.
  • TS-PMEM offers a viable solution for improving the performance of IoT data storage and retrieval.