Taming Performance Variability of Healthcare Data Service Frameworks with Proactive and Coarse-Grained Memory Cleaning
Bibliographic Data
| ID | 15513948 |
|---|---|
| Authors | Eunji Lee (0000-0001-8369-7736, Soongsil University, corresponding author) |
| Year | 2019 |
| Volume | 16 |
| Issue | 17 |
| Pages | 3096-3096 |
| Publication date | 2019-08-26 |
| Peer Reviewed | Yes |
| Open Access | Yes |
| Type | ARTICLE |
| Venue | International Journal of Environmental Research and Public Health (JOURNAL) |
| Journal identifiers | ISSN: 1661-7827 • E-ISSN: 1660-4601 |
| Publisher | Multidisciplinary Digital Publishing Institute (PUBLISHER • CH) |
| DOI | 10.3390/ijerph16173096 |
| PMID | 31454944 |
| OpenAlex | W2970978896 |
| Language | EN |
| References cited | 2 |
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
Database · Database transaction · Embedded system · Latency (audio · Operating system · Scheme (mathematics · Storage management · Advanced Data Storage Technologies · Cloud Computing and Resource Management · Computer Science · Distributed systems and fault tolerance
| Citation velocity | historical |
|---|---|
| Highly cited | No |