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Lightweight, Integrated Data Deduplication for Write Stress Reduction of Mobile Flash Storage
(2018-11-01)
Yen, Miao-Chiang
;
Chang, Shih-Yi
;
Chang, Li-Pin
;
資訊工程學系
;
Department of Computer Science
Recently, smartphone users are becoming reluctant to replace their devices, so providing reliable data storage throughout the increasingly long smartphone replacement cycle is an imminent challenge. We advocate an integrated approach to data deduplication, which involves the host I/O stack and the storage firmware, to reduce the write stress of mobile storage for lifespan extension. First, we identified that the SQLite library produces a large amount of copy-induced duplicate data, which can be fully revealed to the mobile storage through proper file format alignment. Second, inspired by the short flash read latency, we present a firmware-based method to efficiently identify duplicate data without any hardware support. Third, we enhance the flash garbage collector with the awareness of data deduplication. Based on a selection of popular mobile applications, our simulation results show that prior methods, which employ data compression or differential logging, are ineffective for encrypted mobile storage. Compared to flash management without deduplication, our lightweight, integrated approach reduced the total flash-block erase count by 48.7%, average write response time by 43.8%, and total energy consumption by 25.1% on average under the workloads of all the selected mobile applications.
Eager Synching: A Selective Logging Strategy for Fast fsync() on Flash-Based Android Devices
(2017-04-01)
Chang, Li-Pin
;
Sung, Po-Han
;
Chen, Po-Tsang
;
Chen, Po-Hung
;
資訊工程學系
Flash storage has been a standard component in Android devices. Recent research has reported that application data management in Android involves frequent fsync() operations. The current fsync() implementations, including those of ext4 and F2FS, have several common drawbacks. Specifically, ext4 commits a transaction every time to sync a file, whereas F2FS commits a checkpoint to sync a directory. Committing a transaction or checkpoint flushes all dirty data from the page cache to the flash storage via many small, random block write requests. The resultant high I/O frequency and excessive write traffic cause a high fsync() latency. This study presents an efficient fsync() method, called eager synching, which is based on a simple idea: write less, and write sequentially. To sync a file, eager synching writes only a subset of all dirty data in the page cache to a sequential log space using a few sequential block write requests. It does not involve transaction or checkpoint committing. We successfully implemented eager synching in ext4 and F2FS, and our experimental results show that, compared with the original fsync() methods of ext4 and F2FS, eager synching reduced the average and maximum fsync() latencies by up to 72% and 91%, respectively, block-level write traffic by up to 35%, and I/O frequency by up to 66%. Through enhanced crash recovery procedures, eager synching can successfully recover all previously synched files while still guaranteeing the file system integrity. We also conducted live application replays using the proposed eager synching approach and observed that this approach significantly improved the application frame updating rate and application execution time.
Calibrating parameters and formulas for process-level energy consumption profiling in smartphones
(2014-09-01)
Lin, Ying-Dar
;
Rattagan, Ekarat
;
Lai, Yuan-Cheng
;
Chang, Li-Pin
;
Yo, Yun-Chien
Battery-powered mobile devices substantially constrain energy resources. Process-level energy profiling tools can identify the most energy-consuming process and detail the energy usage of hardware components. With the help of energy profiling tools, programmers can fine-tune the energy consumption of processes to extend battery lifetime. However, profiling tools are highly dependent on hardware and must be calibrated for each hardware platform. Furthermore, for any new hardware components, new energy estimation formulas must be created. To solve these two problems regarding off-the-shelf products, this work proposes a two-phase calibrating approach. The first phase reconstructs the power table with a power meter, while the second creates new energy estimation formulas using linear regression analysis. The accuracy of the calibrated tool was evaluated in five scenarios and its error ratio is proven to be below 10%, occasionally less than 5%. Hence, this proposed approach to energy consumption profiling represents a major step in off-the-shelf devices. (C) 2014 Elsevier Ltd. All rights reserved.

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