A memory management scheme for enhancing performance of applications on Android

In this paper, we propose a novel and efficient flash translation layer scheme called BLTF: Block Link-Table FTL. In this proposed scheme, all blocks can be used for servicing update requests, so updates operation can be performed on any of the physical blocks, through uniting log blocks and physical blocks, it can avoid uneven erasing and low block utilization. The invalid blocks, in BLTF scheme, could be reclaimed properly and intensively, it can avoid merging log blocks with physical blocks. At last, the BLTF is tested by simulation, which demonstrates the BLTF can effectively solve data storage problems. Through comparison with other algorithms, we can know that the proposed BLTF greatly prolongs service life of flash devices and improves efficiency of blocks erasing operation.

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DWARM: A wear-aware memory management scheme for in-memory file systems

Future Generation Computer Systems ◽

10.1016/j.future.2018.02.038 ◽

2018 ◽

Vol 88 ◽

pp. 1-15 ◽

Cited By ~ 5

Author(s):

Lin Wu ◽

Qingfeng Zhuge ◽

Edwin Hsing-Mean Sha ◽

Xianzhang Chen ◽

Linfeng Cheng

Keyword(s):

Memory Management ◽

File Systems ◽

Management Scheme

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Taming Performance Variability of Healthcare Data Service Frameworks with Proactive and Coarse-Grained Memory Cleaning

International Journal of Environmental Research and Public Health ◽

10.3390/ijerph16173096 ◽

2019 ◽

Vol 16 (17) ◽

pp. 3096

Author(s):

Eunji Lee

Keyword(s):

Data Storage ◽

Memory Management ◽

Buffer Management ◽

Coarse Grained ◽

Healthcare Data ◽

Management Scheme ◽

High Responsiveness ◽

Performance Optimizations ◽

Memory Buffer ◽

Embedded Database

This article explores the performance optimizations of an embedded database memory management system to ensure high responsiveness of real-time healthcare data frameworks. SQLite is a popular embedded database engine extensively used in medical and healthcare data storage systems. However, SQLite is essentially built around lightweight applications in mobile devices, and it significantly deteriorates when a large transaction is issued such as high resolution medical images or massive health dataset, which is unlikely to occur in embedded systems but is quite common in other systems. Such transactions do not fit in the in-memory buffer of SQLite, and SQLite enforces memory reclamation as they are processed. The problem is that the current SQLite buffer management scheme does not effectively manage these cases, and the naïve reclamation scheme used significantly increases the user-perceived latency. Motivated by this limitation, this paper identifies the causes of high latency during processing of a large transaction, and overcomes the limitation via proactive and coarse-grained memory cleaning in SQLite.The proposed memory reclamation scheme was implemented in SQLite 3.29, and measurement studies with a prototype implementation demonstrated that the SQLite operation latency decreases by 13% on an average and up to 17.3% with our memory reclamation scheme as compared to that of the original version.

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