Considering the potential benefits to lifespan and performance, zoned flash storage is expected to be incorporated into the next generation of consumer devices. However, due to the limited volatile cache and heterogeneous flash cells of consumer-grade flash storage, adopting a zone abstraction requires additional internal hardware design to maximize its benefits. To understand and efficiently improve the hardware design on consumer-grade zoned flash storage, we present ConZone—the first emulator tailored to the characteristics of consumer-grade zoned flash storage. Users can explore the internal architecture and management strategies of consumer-grade zoned flash storage and integrate the optimization with software. We validate the accuracy of ConZone by realizing a hardware architecture for consumer-grade zoned flash storage and comparing it with the state-of-the-art. We also make a case study for read performance research with ConZone to explore the design of mapping mechanisms and cache management strategies.

Three-dimensionalnandflash memory using the advanced multibit-per-cell technique is widely adopted due to its high density. However, it faces the problem of deteriorating read performance and energy consumption due to decreased reliability. Low-density parity-check code (LDPC) is typically adopted as an error correction code (ECC) to encode data and provide fault tolerance. To reduce the cost, LDPC with a high code rate is always adopted. However, LDPC will lead to read retry operations when the accessed data are not successfully decoded, and such retry-induced performance degradation is serious, especially for modern high-density flash memory. In this work, a reliability-aware differential ECC (READECC) approach is proposed to reduce redundancy protection and storage cost of LDPC with a low code rate and optimize the read performance. The basic idea is to adopt LDPC with a suitable code rate considering both data access characteristics and flash reliability characteristics. First, hot reads are identified based on the frequency of being accessed. Second, based on the reliability variation characteristics, the life of flash memory is divided into three reliability periods. As the reliability period shifts, the code rate of the LDPC adjusts adaptively to minimize redundancy protection. Third, an adaptive-sized logical page approach is further proposed to support LDPC with strong error correction capability (a low code rate) with a low storage cost. Through careful design and evaluation on 3-D triple-level-cellnandflash memory, READECC achieves encouraging optimizations with a negligible cost.

Modern mobile devices adopt two-level memory swapping consisting of ZRAM and storage devices to relieve memory pressure. In the swap subsystem, ZRAM can improve application responsiveness and reduce write traffic to storage devices while consuming physical memory and additional CPU cycles. To better utilize ZRAM and improve system performance, we propose ElasticZRAM, an elastic ZRAM to redesign the traditional memory swapping with full awareness of the characteristics of applications and NAND flash-based storage devices on mobile devices. Experimental results on Google Pixel 6 demonstrate that ElasticZRAM improves application response time by up to 24.8% with negligible overhead compared with state-of-the-arts.

Mobile devices always cache numerous files during application runtime, which can be trimmed to improve the user experience. However, existing cache file trimming methods are unaware of the cleaning cost within the file system and storage devices, which degrades the system performance and storage lifetime, resulting in low benefits of trimming cache files. Motivated by this, an adaptive cache file trimming (CacheTrimmer) scheme is proposed to trim cache files for performance and lifetime improvement. The basic idea is to determine the trimming timing based on the cleaning cost of the file system and storage device, maximizing the benefit of trimming cache files. Specifically, CacheTrimmer includes two components: First, a cleaning cost-aware trimming method is proposed to trim cache files by recording the index information of cache files in a list and determining the timing and size of file trimming. Second, to avoid trimming-induced intra-segment fragmentation and improve trimming efficiency, a log-structured cache scheme is further proposed to maintain the cache files in separate segments. We prototype CacheTrimmer with a real mobile platform. Experimental results under real workloads show that CacheTrimmer achieves encourage performance and lifetime improvement compared to the state-of-the-art.

WriteBooster is widely adopted as a non-volatile write buffer to enhance user experience for smartphones. How-ever, the host suffers sub-optimal write performance when using WriteBooster due to the lack of utilization of rich semantic infor-mation. With the zoned storage being included in smartphones, WriteBooster design presents new opportunities. In this paper, we propose Zoned-WB, a WriteBooster management scheme based on zoned storage to utilize the rich semantic information on the host to improve user experience. Specifically, Zoned- Wbincludes two parts, zoned storage-based WB and foreground request-aware WB. First, the zoned storage-based WB is aimed at designing WriteBooster management scheme based on zoned storage. Second, foreground request-aware WB is designed to adaptively adjust the capacity quota for different types of requests in Writebooster based on rich semantic information on the host. We evaluate Zoned-WB on a zoned storage emulator with workloads collected from smartphones. Evaluation results show that Zoned- Wbcan effectively improve user experience.

For mobile distributed file systems (MDFSs), files can be easily shared among multiple mobile devices. However, it requires the connected remote devices to be online all the time for timely file browsing, which incurs significant energy consumption. This is unacceptable for battery-powered mobile devices. To address this issue, we propose EEPC, an energy-efficient persistent cache scheme for MDFSs. It consists of several techniques. First, a proactive cache invalidation mechanism is designed to ensure optimistic access to the local persistent cache, which greatly reduces unnecessary read requests. Second, a lazy cache synchronization policy is designed to reorganize writeback requests, which ensures that remote devices remain in a low-power state for a long time. Finally, a cache admission and eviction scheme is proposed, which considers both file access frequency and recency, and an adaptable file prefetching scheme is adopted to quickly recover invalidated cache files. Evaluations on real devices show that EEPC maintains at least 60% of sleep time for remote devices and greatly extends the interval between two wake-ups, regardless of the frequency of remote file accesses. Compared with the state-of-the-art, the energy consumption of remote devices can be reduced by 33.6%, on average.

Memory swapping ensures smooth application switching for mobile systems by caching applications in the background. To further play the role of memory swapping, remote swapping across mobile devices has been widely studied, which caches applications to nearby remote devices by remote paging. However, due to the massive remote I/Os and unguaranteed swap throughput, the current remote swapping is limited with an unsatisfactory user experience, especially under variable network conditions. This paper first studies the access characteristics of applications and clarifies the impact of various network traffic on remote swapping. Motivated by these, an efficient access characteristic-guided remote swapping framework (ACR-Swap + ) is proposed to optimize remote swapping across mobile devices with resilient remote paging. ACR-Swap + first performs selective remote paging based on the swap-in frequency of different processes and then prefetches data across devices based on the process running states. Finally, it conducts hierarchical remote paging to avoid the impact of network traffic on remote swapping. Evaluations on Google Pixel 6 show that ACR-Swap + reduces the application switching latency by 21.6% and achieves a negligible performance fluctuation under various network traffic compared to the state of the art.

The prevalence of cross-device resource sharing enables users to utilize various device resources of the connected mobile devices seamlessly. Since there are often numerous connected mobile devices under the same network, cross-device tasks are often executed concurrently. However, the existing resource sharing schemes suffer from significant performance degradation for the parallel cross-device tasks due to competition for limited system resources (e.g., network and CPU). This paper first analyzes the performance penalty in parallel execution of the cross-device resource sharing tasks. Then, a novel multi-task perceiving and scheduling framework (MTPS) is proposed to guarantee the quality of service of the parallel tasks. The basic idea of MTPS is to first build a master-slave system model to reorganize mobile devices under the same network. Then, MTPS perceives the running cross-device resource sharing tasks and schedules the parallel execution of multiple tasks to avoid mutual interference. Experimental results on real devices show that MTPS can reduce the average completion time of file sharing by 63.5%, and maintain at least 24 frames per second for screen casting at optimal levels in the presence of other tasks.

Mobile systems and applications are becoming increasingly feature-rich and powerful, which constantly suffer from memory pressure, especially for devices equipped with limited DRAM. Swapping inactive DRAM pages to the storage device is a promising solution to extend the physical memory. However, existing mobile devices usually adopt flash memory as the storage device, where swapping DRAM pages to flash memory may introduce significant performance overhead. In this paper, we first conduct an in-depth analysis of the I/O characteristics of the flash-based memory swapping, including the I/O interference and swap I/O randomness in swap subsystem. Then an I/O efficiency optimization framework for memory swapping (IOSR) is proposed to enhance the performance of flash-based memory swapping for mobile devices. IOSR consists of two methods: swap I/O scheduling (SIOS) and swap I/O pattern reshaping (SIOR). SIOS is designed to schedule the swap I/O to reduce interference with other processes I/Os. SIOR is designed to reshape the swap I/O pattern with process-oriented swap slot allocation and adaptive granularity swap read-ahead. IOSR is implemented on Google Pixel 4. Experimental results show that IOSR reduces the application switching time by 31.7% and improves the swap-in bandwidth by 35.5% on average compared to the state-of-the-art.