• KIPS Transactions on Computer and Communication Systems
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• v.6 no.2
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• pp.59-66
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• 2017

MySQL database is the second place in the market share of the current database. Especially InnoDB storage engine has been used in the default storage engine from the version of MySQL5.5. And many companies are using the MySQL database with InnoDB storage engine. Study on the structural features and the log of the InnoDB storage engine in the field of digital forensics has been steadily underway, but for how to restore on a record-by-record basis for the deleted data, has not been studied. In the process of digital forensic investigation, database administrators damaged evidence for the purpose of destruction of evidence. For this reason, it is important in the process of forensic investigation to recover deleted record in database. In this paper, We proposed the method of recovering deleted data on a record-by-record in database by analyzing the structure of MySQL InnoDB storage engine. And we prove this method by tools. This method can be prevented by database anti forensic, and used to recover deleted data when incident which is related with MySQL InnoDB database is occurred.

• Journal of KIISE
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• v.43 no.11
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• pp.1216-1222
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• 2016

The advent of large-scale web services has resulted in gradual increase in the amount of data used in those services. These big data are managed efficiently by DBMS such as MySQL and MariaDB, which use InnoDB engine as their storage engine, since InnoDB guarantees ACID and is suitable for handling large-scale data. To improve I/O performance, InnoDB caches data and index of its database through a buffer pool. It also supports multiple buffer pools to mitigate lock contentions. However, the multiple buffer pool scheme leads to the additional data consistency overhead. In this paper, we analyze the overhead of the multiple buffer pool scheme. In our experimental results, although multiple buffer pool scheme mitigates the lock contention by up to 46.3%, throughput of DMBS is significantly degraded by up to 50.6% due to increased disk I/O and fsync calls.

• Journal of KIISE
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• v.44 no.2
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• pp.208-212
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• 2017

Flash SSDs have many advantages over the existing hard disks such as energy efficiency, shock resistance, and high I/O throughput. For these reasons, in combination with the emergence of innovative technologies such as 3D-NAND and V-NAND for cheaper cost-per-byte, flash SSDs have been rapidly replacing hard disks in many areas. However, the existing database engines, which have been developed mainly assuming hard disks as the storage, could not fully exploit the characteristics of flash SSDs (e.g. internal parallelism). In this paper, in order to utilize the internal parallelism intrinsic to modern flash SSDs for faster query processing, we implemented a prefetching method using asynchronous input/output as a new functionality for secondary index scans in MySQL InnoDB engine. Compared to the original InnoDB engine, the proposed prefetching-based scan scheme shows three-fold higher performance in the case of 16KB-page sizes, and about 4.2-fold higher performance in the case of 4KB-page sizes.

• The Journal of the Convergence on Culture Technology
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• v.9 no.3
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• pp.803-809
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• 2023

This paper analyzes and evaluates to optimally build a data collection system essential for factory energy management systems on an edge-based lightweight platform. A "Sensor/OPC-UA simulator" was developed based on sensors in an actual food factory and used to evaluate the storage engine of edge devices. The performance of storage engines in edge devices was evaluated to suggest the optimal storage engine. The experimental results show that when using the RocksDB storage engine, it has less than half the memory and database size compared to using InnoDB, and has a 3.01 times faster processing time. This study enables the selection of advantageous storage engines for managing time-series data on devices with limited resources and contributes to further research in this field through the sensor/OPC simulator.

• Publications of The Korean Astronomical Society
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• v.26 no.4
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• pp.159-168
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• 2011

We constructed two test server systems for KMTNet data management. One is the photometry database server which is optimized for stable operation, and the other is the photometric data process server which is optimized for fast I/O between devices. The performances of servers and data storage units were tested using various methods. Database upload was also checked using five different methods. From tests, we concluded that the most efficient method to upload photometric data processing results to database is the use of three nodes with job scheduler under the InnoDB engine. In this study we provide the test results for prototype servers for KMTNet data management.