LAUSR.org creates dashboard-style pages of related content for over 1.5 million academic articles. Sign Up to like articles & get recommendations!

iNVMFS: An Efficient File System for NVRAM-Based Intermittent Computing Devices

Developing toward battery-less, energy-harvesting designs is a promising direction for sensor-scale devices. The recent introduction of byte-addressable, nonvolatile memory (NVRAM) enables intermittent computing, which preserves as much program progress across… Click to show full abstract

Developing toward battery-less, energy-harvesting designs is a promising direction for sensor-scale devices. The recent introduction of byte-addressable, nonvolatile memory (NVRAM) enables intermittent computing, which preserves as much program progress across power interruptions as possible using fine-grained checkpoints. Sensing applications strongly demand local storage for near-data processing, and there is no exception for intermittent computing devices. While checkpointing on program progress is being studied recently, there is little work regarding how sensor file systems support intermittent computing. On power recovery, although the program progress is reverted to the latest checkpoint, the storage state stays at the instant of power loss. To remedy this problem, we present a lightweight file system for efficient operations on files and checkpoints. Our design exploits the byte addressability of NVRAM and uses as much in-place byte writing as possible while guaranteeing the safety of checkpoint operations. We evaluated our design against two prior checkpoint-enabled file systems, and results show that on average, our design reduced the total time overhead and energy consumption by 77% and 78%, respectively.

Keywords: intermittent; intermittent computing; computing devices; file system

Journal Title: IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems
Year Published: 2022

Link to full text (if available)


Share on Social Media:                               Sign Up to like & get
recommendations!

Related content

More Information              News              Social Media              Video              Recommended



                Click one of the above tabs to view related content.