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A Study on Buffer Management for Read-Once Pages Using a Read Buffer
Seongjae Moon, Sang-Won Lee, Young Ik Eom
http://doi.org/10.5626/JOK.2025.52.7.611
The relational database systems store pages in main memory to minimize storage access and improve transaction throughput. However, read-once pages, referenced only once before eviction, may force dirty pages to be flushed, reducing the page hit ratio. In SSD-based DBMS, read-once pages cause I/O serialization, forcing faster read operations to wait for slower write operations to complete. We analyze the I/O serialization caused by read-once pages and their characteristics, and propose a buffer management scheme to isolate read-once pages by using a read buffer. In the TPC-C benchmark, dirty pages evicted due to read-once pages account for about 8.9% of all flush operations. By isolating read-once pages into the read buffer, we reduced single page flushes by 56% and the page miss ratio in the normal buffer by 32% while increasing transaction throughput by 8% compared to Vanilla MySQL.
A Study on Sales Prediction Model Based on BiLSTM-GAT Using Credit Card Transaction Data
Wonseok Jung, Dohyung Kim, Young Ik Eom
http://doi.org/10.5626/JOK.2024.51.9.807
Sales prediction using credit card transaction data is essential for understanding consumer buying patterns and market trends. However, traditional statistical and machine learning models have limitations when it comes to analyzing temporal features and the relationships between different variables, such as geographical data and sales information by service types, population, and transaction times. This paper proposes two models that can simultaneously analyze the relationships based on commercial district features and sales time-series features. To evaluate the performance of these models, we constructed graphs based on the distances and sales similarity of features between commercial districts. We then compared the performance of the proposed models with traditional time-series models, namely LSTM and BiLSTM. The results of the experiment showed that the GAT-BiLSTM model improved prediction accuracy by approximately 15% compared to the BiLSTM model, while the BiLSTM-GAT model improved it by about 29% over the BiLSTM model, as measured by RMSE.
Managing DISCARD Commands in F2FS File System for Improving Lifespan and Performance of SSD Devices
Jinwoong Kim, Donghyun Kang, Young Ik Eom
http://doi.org/10.5626/JOK.2024.51.8.669
The DISCARD command is an interface that helps improve the lifespan and performance of SSDs by informing the SSD devices about invalid file system blocks. However, in the F2FS file system, the DISCARD command is only sent to the SSD during idle time, which limits the potential for improving lifespan and performance. In this paper, we propose an EPD scheme to efficiently transfer DISCARD commands during short idle times, as well as a seg-ment allocation scheme called PSA, which replaces DISCARD commands with overwrite commands. To evaluate the effectiveness of these proposed schemes, we conducted several experiments using various workloads to verify the lifespan and performance of real SSD devices. The results showed that the proposed schemes can improve the write amplification factor (WAF) by up to 40% and throughput by up to 160%, when compared to the traditional F2FS file system.
Analyses of the Memory Usage Efficiency of the Scudo Memory Allocator
KyungSeok Lee, Taehyung Lee, Young Ik Eom
http://doi.org/10.5626/JOK.2023.50.2.103
Optimizing memory usage is important in mobile systems because diverse applications share limited system memory in those systems. Although the default memory allocator of Android, Scudo, is designed to mitigate vulnerabilities related to heap memory and optimize the memory allocation performance, it has inefficiency in terms of memory usage aspects. This paper addresses two problems based on the structure and operation mechanism of Scudo. First, the problems that occur due to the static number of local caches are analyzed. Second, the internal fragmentation problems induced by the inefficient free-chunk management policy are analyzed. The evaluation results show that, according to the characteristics of applications, there are some performance overheads and memory waste due to the static number of local caches in Android systems. Furthermore, we confirm that repeated allocation and free operations fragment almost all allocated physical pages in Scudo; hence pages are not actively reclaimed to the OS even after 90% of allocated chunks are freed.
An Efficient RocksDB Leveling Technique using F2FS Multi-Head Logging
Jeongho Lee, Jonggyu Park, Young Ik Eom
http://doi.org/10.5626/JOK.2022.49.8.655
RocksDB has been considered one of the most representative LSM-tree based key-value stores, and it is actively used in high-performance database systems. However, because of the nature of such database systems, which run for an extended period of time and frequently write to the underlying storage devices, the systems may incur file system-level fragmentation. Additionally, various optimizations in RocksDB may accelerate the file system-level fragmentation under aged systems, which hinders the maintenance of long-term superior performance of flash-based storage devices such as SSDs. In this paper, we first analyze the fragmentation problem of RocksDB on F2FS and propose a new RocksDB leveling technique that exploits F2FS multi-head logging. The experimental results using an SSD confirm that the proposed method improves the throughput by 7% and reduces tail latency by 18%, compared with the conventional F2FS file system, and improves the throughput by 56% and reduces tail latency by 19%, compared with the EXT4 file system.
Radar Signal Processor for High-Resolution Target Detection
http://doi.org/10.5626/JOK.2022.49.5.369
Recently, as the technology of multi-function radar is developed, the radar deception technology of ballistic missiles is also developing. For some ballistic missiles, the propellant explodes in the air after the stage is separated, causing the warhead and many fragments to fly together, which lowers the multi-function radar’s ability to engage ballistic missiles. Thus, there is a need for a radar system capable of operating a broadband waveform to intercept a warhead, by quickly discriminating between a high-speed warhead and fragments while retaining the existing target detection/tracking function. It is possible to find and intercept warhead among fragments by extracting the length of a target, using a broadband waveform and performing warhead classification using this. In this paper, we describe the process of performing the target detection/tracking function using a narrowband waveform such as doppler processing, pulse compression, threshold processing, and target processing and high-resolution target length extraction and phase diffraction correction for accurate length extraction using a wideband waveform to create a radar system that satisfies these requirements. Also, it shows the results of designing and implementing these functions with signal processing software and performing tests.
Design of Durable Node Replication for Persistent Memory Data Structures on NUMA Architectures
http://doi.org/10.5626/JOK.2022.49.1.8
Recently, advances in persistent memory and NUMA technologies have allowed for the provision of high performance and large storage space to the applications such as big data and machine learning. Such PM environments on multi-node systems require a change in the data structures, which are being used in each layer of the software stack. In terms of the research on PM data structures, however, it is a difficult problem to ensure high level of concurrency as well as non-volatility which is an important characteristics of NUMA and PM, respectively. In this paper, we propose an NRPM that extends the node replication, which is a representative of NUMA algorithms. NRPM outperforms hash algorithm by up to 5x by improving concurrency in the multi-node PM server using shared-log and flat combining methods. We confirmed the validity of NRPM through various performance analyses considering the characteristics of NUMA-PM.
Analyses of Linux I/O Interfaces for High-Performance I/O Operations in Key-Value Stores
http://doi.org/10.5626/JOK.2021.48.12.1274
Recently, to utilize high-performance storage devices, various I/O interfaces have been studied. In particular, asynchronous I/O interfaces are now getting attention. However, those asynchronous I/O interfaces have the disadvantage of relatively higher latency and more CPU consumption than synchronous I/O interfaces. In this paper, we first analyze the characteristics of each I/O interface and then apply it to the key-value store to measure the performance at the application layer. The experiments show that the asynchronous I/O interface consumes 2.73× more CPU resources than the synchronous I/O interface, but delivers up to 2.42× higher IOPS depending upon the batching I/O size. In addition, experiments on key-value stores show up to 6.60× higher throughput and 61.09% lower latency when asynchronous I/O interfaces are used in the read-intensive workload.
An Analysis of the Performance Interference among Column Families in RocksDB
Hoyoung Lee, Minho Lee, Young Ik Eom
http://doi.org/10.5626/JOK.2021.48.7.835
RocksDB is one of the representative LSM-tree-based key-value stores and provides a column family feature to classify key-value pairs based on the characteristics of data. Each column family has its write buffer and manages the classified key-value pairs with it, whereas column families have to share a single WAL file for data consistency. However, sharing the WAL file induces performance interference among the column families and reduces the write performance of RocksDB. In this paper, we have analyzed the performance degradation of RocksDB caused by performance interference among multiple column families. Consequently, we measured the write performance of RocksDB by varying the size of WAL file and the number of column families. Experimental results clearly show that the write performance of RocksDB decreases by up to 57.08% according to the size of the WAL file and the number of the constructed column families.
Distributed Storage System for Reducing Write Amplification on Non-Volatile Memory
http://doi.org/10.5626/JOK.2020.47.2.129
Recently, research on non-volatile memory, such as 3DXpoint, in distributed storage systems has received considerable interest from both academia and industry. However, in order to utilize these state-of-the-art non-volatile memory devices effectively in distributed storage systems, there is a need for improvements in traditional architectures of HDD/SSD-based storage systems. This is because current distributed storage system structures use a dedicated space for journaling to make up for slow storage performance. Also, considering the performance characteristics of non-volatile memory, which are similar to that of DRAM, current distributed storage system structures are not only inefficient in terms of overall performance but also cause write amplification. In this paper, we propose an architecture that mitigates the effects of write amplification in non-volatile memory-based distributed storage systems. To evaluate the proposed architecture and scheme, we have conducted diverse experiments in a CEPH storage system environment. Through these experiments, we have confirmed that the DAXNJ structure proposed in this paper decreases write amplification by 61% during 1M object write operations and increases the overall system performance by 15%.
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