Non-volatile random-access memory (NVRAM) becomes a mainstream storage device in embedded systems due to its favorable features, such as small size, low power consumption, and short read/write latency. Unlike dynamic random access memory (DRAM), NVRAM has asymmetric performance and energy consumption on read/write operations. Generally, on NVRAM, a write operation consumes more energy and time than a read operation. Unfortunately, current mobile/embedded file systems, such as EXT2/3 and EXT4, are very unfriendly for NVRAM devices. The reason is that current mobile/embedded file systems employ a journaling mechanism for increasing its data reliability. Although a journaling mechanism raises the safety of data in a file system, it also repeatedly writes data to a data storage while data is committed and checkpointed. Though several related works have been proposed to reduce the amount of write traffic to NVRAM, they still cannot effectively minimize the write amplification of a journaling mechanism. Such observations motivate us to design a two-phase write reduction journaling file system called wrJFS. In the first phase, wrJFS classified data into two categories: Metadata and user data. As the size of metadata is usually very small (few bytes), byte-enabled journaling strategy will handle metadata during commit and checkpoint stages. In contrast, the size of user data is very large relative to metadata; thus, user data will be processed in the second phase. In the second phase, user data will be compressed by hardware encoder to reduce the write size and managed compressed-enabled journaling strategy to avoid the write amplification on NVRAM. Moreover, we analyze the overhead of wrJFS and show that the overhead is negligible. According to the experimental results, the proposed wrJFS outperforms other journaling file systems even though the experiments include the overhead of data compression.

Non-volatile random-access memory (NVRAM) becomes a mainstream storage device in embedded systems due to its favorable features, such as small size, low power consumption, and short read/write latency. On NVRAM, a write operation consumes more energy and time than a read operation. However, current mobile/embedded file systems (e.g., EXT2/3 and EXT4) are very unfriendly for NVRAM devices. The reason is that a journaling mechanism writes the same data twice during data commitment and checkpoint. Such observations motivate this paper to design a two-phase write reduction journaling file system called wrJFS. In the first phase, wrJFS classified data into two categories: Metadata and user data. Metadata will be handled by partial byte-enabled journaling strategy, and user data will be processed in the second phase. In the second phase, user data will be compressed by hardware encoder so as to reduce the write size, and managed compressed-enabled journaling strategy to avoid the write amplification. The experimental results show that the proposed wrJFS can reduce the size of the write request by 89.7% on average, compared with the original EXT3.

Recently, many applications and users rely on cloud storage services, such as Google drive, Dropbox, iCloud and Sky drive, to store private files and system data, and cloud storage services must thus be reliable and secure. To increase reliability, previous studies have proposed a variety of erasure coding algorithms for data fault tolerance for use in storage systems. Although these data fault tolerance mechanisms increase data reliability, implementation also increases storage system costs and energy consumption due to data redundancy. However, to date energy-efficient schemes have only been developed based on a RAID architecture, and none have been implemented using an erasure coding algorithm. To address this issue, this study proposes an energy-aware I/O framework with a quality-of-service (QoS) aware data reconstruction scheduler for erasure coding algorithms, called the EEC-scheme. This approach reduces storage system energy consumption and decreases response times for user requests when the system restores failed disks. A series of experiments show that the proposed scheme can significantly reduce power consumption in storage systems.