Browsing by Author "Ji, Cheng"

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An I/O Scheduling Strategy for Embedded Flash Storage Devices With Mapping Cache
(2018-04-01)
Ji, Cheng
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Chang, Li-Pin
;
Wu, Chao
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Shi, Liang
;
Xue, Chun Jason
NAND flash memory has been the default storage component in embedded systems. One of the key technologies for flash management is the address mapping scheme between logical addresses and physical addresses, which deals with the inability of in-place-updating in flash memory. Demand-based page-level mapping cache is often applied to match the cache size constraint and performance requirement of embedded storage systems. However, recent studies showed that the management overhead of mapping cache schemes is sensitive to the host I/O patterns, especially when the mapping cache is small. This paper presents a novel I/O scheduling scheme, called MAP+, to alleviate this problem. The proposed scheduling approach reorders I/O requests for performance improvement from two angles. Prioritizing the requests that will hit in the mapping cache, and grouping requests with related logical addresses into large batches. Batches of requests are reordered to further optimize request waiting time. Experimental results show that MAP+ improved upon traditional I/O schedulers by 48% and 18% in terms of read and write latencies, respectively.
File Fragmentation in Mobile Devices: Measurement, Evaluation, and Treatment
(2019-09-01)
Ji, Cheng
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Chang, Li-Pin
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Hahn, Sangwook Shane
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Lee, Sungjin
;
Pan, Riwei
Mobile devices, such as smartphones, have become a necessity in our daily life. However, users may notice that after being used for a long time, mobile devices begin to exhibit a sluggish response. Based on an empirical study on a collection of aged smartphones, this work identified that file fragmentation is among the key factors that contribute to the progressive degradation of response time. This study takes a three-step approach: First, this study designed a set of reproducible file-system aging processes based on User-Interface (UI) script replay. Through the aging processes, it confirmed that file fragmentation quickly emerged, and SQLite files were among the most severely fragmented files. Second, based on the workloads of a selection of popular mobile applications, this study observed that file fragmentation did have an impact on user-perceived latencies. Specifically, the launching time of Chrome on an aged file system was 79 percent slower than it was on a pristine file system. Third, this study evaluated existing treatments of file fragmentation, including space preallocation, persistent journal, and file defragmentation to understand their efficacies and limitations. This study also evaluated a state-of-the-art copyless defragmenter, janusd, to show its advantage over the existing methods.
I/O Scheduling with Mapping Cache Awareness for Flash Based Storage Systems
(2016-01-01)
Ji, Cheng
;
Wu, Chao
;
Chang, Li-Pin
;
Shi, Liang
;
Xue, Jason
NAND flash memory has been the default storage component in mobile systems. One of the key technologies for flash management is the address mapping scheme between logical addresses and physical addresses, which deals with the inability of in-place-updating in flash memory. Demand-based page-level mapping cache is often applied to match the cache size constraint and performance requirement of mobile storage systems. However, recent studies showed that the management overhead of mapping cache schemes is sensitive to the host I/O patterns, especially when the mapping cache is small. This paper presents a novel I/O scheduling scheme, called MAP, to alleviate this problem. The proposed scheduling approach reorders I/O requests for performance improvement from two angles: Prioritizing the requests that will hit in the mapping cache, and grouping requests with related logical addresses into large batches. Experimental results show that MAP improved upon traditional I/O schedulers by 30% and 8% in terms of read and write latencies, respectively.
Improving File System Performance of Mobile Storage Systems Using a Decoupled Defragmenter
(2017-01-01)
Hahn, Sangwook Shane
;
Lee, Sungjin
;
Ji, Cheng
;
Chang, Li-Pin
;
Yee, Inhyuk
In this paper, we comprehensively investigate the file fragmentation problem on mobile flash storage. From our evaluation study with real Android smartphones, we observed two interesting points on file fragmentation on flash storage. First, defragmentation on mobile flash storage is essential for high I/O performance on Android smartphones because file fragmentation, which is a recurring problem (even after defragmentation), can significantly degrade I/O performance. Second, file fragmentation affects flash storage quite differently than HDDs. When files are fragmented on flash storage, the logical fragmentation and the physical fragmentation are de coupled and a performance degradation mostly comes from logical fragmentation. Motivated by our observations, we propose a novel defragger, Janus defragger (janusd), which supports two defraggers, janusdL for a logical defragger and janusdP for a physical defragger. JanusdL, which takes advantage of flash storage's internal logical to physical mapping table, supports logical defragmentation without data copies. JanusdL is very effective for most fragmented files while not sacrificing the flash lifetime. JanusdP, which is useful for physically fragmented files but requires data copies, is invoked only when absolutely necessary. By adaptively selecting janusdL and janusd P, janusd achieves the effect of full file defragmentation without reducing the flash lifetime. Our experimental results show that janusd can achieve at least the same level of I/O performance improvement as e4defrag without affecting the flash lifetime, thus making janusd an attractive defragmentation solution for mobile flash storage.
Lightweight Data Compression for Mobile Flash Storage
(2017-10-01)
Ji, Cheng
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Chang, Li-Pin
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Shi, Liang
;
Gao, Congming
;
Wu, Chao
Data compression is beneficial to flash storage lifespan. However, because the design of mobile flash storage is highly cost-sensitive, hardware compression becomes a less attractive option. This study investigates the feasibility of data compression on mobile flash storage. It first characterizes data compressibility based on mobile apps, and the analysis shows that write traffic bound for mobile storage volumes is highly compressible. Based on this finding, a lightweight approach is introduced for firmware-based data compression in mobile flash storage. The controller and flash module work in a pipelined fashion to hide the data compression overhead. Together with this pipelined design, the proposed approach selectively compresses incoming data of high compressibility, while leaving data of low compressibility to a compression-aware garbage collector. Experimental results show that our approach greatly reduced the frequency of block erase by 50.5% compared to uncompressed flash storage. Compared to unconditional data compression, our approach improved the write latency by 10.4% at a marginal cost of 4% more block erase operations.