In most file systems, if a file is deleted, only the metadata of the file is deleted or modified and the file's data is still stored on the physical media. Some users require that deleted files no longer be accessible. This requirement is more important in embedded systems that employ flash memory as a storage medium. In this paper, we have designed a NAND flash file system that has a secure deletion functionality. We modified YAFFS to support secure deletion. Our method uses encryption to delete files and forces all keys of a specific file to be stored in the same block. Therefore, only one erase operation is required to securely delete a file. The proposed method securely deletes not only keys but also all of the metadata of that file. Our simulation results show that the number of block erases due to file creation and file modification is very low and the amortized number of block erases is lower than the simple encryption method. Even though we applied our method only to the YAFFS, our method can be easily applied to other NAND flash file systems.

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Incremental checkpointing, which is intended to minimize checkpointing overhead, saves only the modified pages of a process. However, the cumulative size of incremental checkpoints increases at a steady rate over time because many updated values may be saved for the same page. In this paper, we present a comprehensive overview of Pickpt, which is a page-level incremental checkpointing facility. Pickpt provides space-efficient techniques for minimizing the use of disk space. For our experiments, the results show that the use of disk space of Pickpt was significantly reduced compared with existing incremental checkpointing.

During the last several years, dynamic voltage scaling (DVS) algorithms are being used for energy consumption on real, fully functional battery supplied devices, adjusting the clock speed and supply voltage dynamically. Most DVS algorithms are investigated in interval-based and task-based strategies. Taskbased algorithms consider task information, especially task deadline, on deciding what speed to choose at any given time.Interval-based algorithms predict the CPU speed of the upcoming interval based on observations of the CPU utilization of previous intervals, and then set the speed for that interval based on this prediction. Most DVS algorithms have only been tested in simulation environments. In this paper, those interval-based DVS algorithms are modified with different parameters on different workloads, and evaluated to know which one saves the most energy while not degrading computer performance.