• Journal of KIISE
• /
• v.42 no.4
• /
• pp.434-441
• /
• 2015

Next generation memory technologies, which we denote as 'new memory', have both non-volatile and byte addressable properties. These characteristics are expected to bring changes to the conventional computer system structure. In this paper, we propose a fast boot technique for hybrid main memory architectures that have both new memory and DRAM. The key technique used for fast booting is write-tracking. Write-tracking is used to detect and manage modified data detection and involves setting the kernel region to read-only. This setting is used to trigger intentional faults upon modification requests. As the fault handler can detect the faulting address, write-tracking makes use of the address to manage the modified data. In particular, in our case, we make use of the MMU (Memory Management Unit) translation table. When a write occurs to the boot completed state, write-tracking preserves the original state of the modified address of the kernel region to a particular location, and execution continues. Upon booting, the fast booting process restores the preserved data to the original kernel region allowing rapid system boot-up. We develop the fast booting technique in an actual embedded board equipped with new memory. The boot time is reduced to less than half a second compared to around 15 seconds that is required for the original system.

• Journal of KIISE:Computing Practices and Letters
• /
• v.16 no.1
• /
• pp.1-10
• /
• 2010

Recently heterogeneous storage system such as hybrid hard disk drive (H-HDD) combining flash memory and magnetic disk is launched, according as the read performance of NAND flash memory is enhanced as similar to that of hard disk drive (HDD) and the power consumption of NAND flash memory is reduced less than that of HDD. However, the read and write operations of NAND flash memory are slower than those of rotational disk. Besides, serious overheads are incurred on CPU and main memory in the case that intensive write requests to flash memory are repeatedly occurred. In this paper, we propose the Least Frequently Used-Hot scheme that replaces the data blocks whose reference frequency of read operation is low and update frequency of write operation is high, and the data flushing scheme that rearranges the data blocks into the multi-zone of the rotation disk. Experimental results show that the execution time of the proposed method is 38% faster than those of conventional LRU and LFU block replacement schemes in I/O performance aspect and the proposed method increases the life span of Non-Volatile Cache 40% higher than those of conventional LRU, LFU, FIFO block replacement schemes.

• Journal of KSNVE
• /
• v.2 no.4
• /
• pp.265-272
• /
• 1992

The simplest method which has been used extensively for vibration analysis is the transfer matrix method introduced by Myklestad and was later extended by many researchers. The crude approximation results in considerable error on the predicted natural frequencies and to increase the accuracy the number of elements used in the analysis must be increased. In addition, numerical instability can occur as a result of matrix multiplication. Also the main disadvantage of the finite element method is the large computer memory requirements for complex systems. The new method proposed in this paper combines the transfer matrix and finite dynamic element techniques to form a powerful algorithm for vibration analysis of rotor system. It is shown that the accuracy improves significantly when the transfer matrix for each segment is obtained from finite dynamic element techniques.

• Journal of Korea Multimedia Society
• /
• v.10 no.11
• /
• pp.1384-1397
• /
• 2007

This paper proposes fast storage techniques for hybrid query of data streams. DSMS(Data Stream Management System) have been researched for processing data streams that have busting income. To process hybrid query that retrieve both current incoming data streams and past data streams data streams have to be stored into disk. But due to fast input speed of data stream and memory and disk space limitation, the main research is not about querying to stored data streams but about querying to current incoming data streams. Proposed techniques of this paper use circular buffer for maximizing memory utility and for make non blocking insertion possible. Data in a disk is compressed to maximize the number of data in the disk. Through experiences, proposed technique show that bursting insertion is stored fast.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.17 no.10
• /
• pp.2701-2717
• /
• 2023

In this paper, a hybrid fuzzy-based method is suggested for determining India's best system for power generation. This suggested approach was created using a fuzzy-based combination of the Giza Pyramids Construction (GPC) and Recalling-Enhanced Recurrent Neural Network (RERNN). GPC is a meta-heuristic algorithm that deals with solutions for many groups of problems, whereas RERNN has selective memory properties. The evaluation of the current load requirements and production profile information system is the main objective of the suggested method. The Central Electricity Authority database, the Indian National Load Dispatch Centre, regional load dispatching centers, and annual reports of India were some of the sources used to compile the data regarding profiles of electricity loads, capacity factors, power plant generation, and transmission limits. The RERNN approach makes advantage of the ability to analyze the ideal power generation from energy data, however the optimization of RERNN factor necessitates the employment of a GPC technique. The proposed method was tested using MATLAB, and the findings indicate that it is effective in terms of accuracy, feasibility, and computing efficiency. The suggested hybrid system outperformed conventional models, achieving the top result of 93% accuracy with a shorter computation time of 6814 seconds.

• Journal of KIISE:Databases
• /
• v.37 no.6
• /
• pp.308-314
• /
• 2010

As the price of flash memory continues to drop and the technology of flash SSD controller innovates, high performance flash SSDs with affordable prices flourish in the storage market. Nevertheless, it is hard to expect that flash SSDs will replace harddisks completely as database storage. Instead, the approach to use flash SSD as a cache for harddisks would be more practical, and, in fact, several hybrid storage architectures for flash memory and harddisk have been suggested in the literature. In this paper, we propose a new approach to use flash SSD as an extended buffer for main buffer in database systems, which stores the pages replaced out from main buffer and returns the pages which are re-referenced in the upper buffer layer, improving the system performance drastically. In contrast to the existing approaches to use flash SSD as a cache in the lower storage layer, our approach, which uses flash SSD as an extended buffer in the upper host, can provide fast random read speed for the warm pages which are being replaced out from the limited main buffer. In fact, for all the pages which are missing from the main buffer in a real TPC-C trace, the hit ratio in the extended buffer could be more than 60%, and this supports our conjecture that our simple extended buffer approach could be very effective as a cache. In terms of performance/price, our extended buffer architecture outperforms two other alternative approaches with the same cost, 1) large main buffer and 2) more harddisks.

• The Journal of Korean Institute of Next Generation Computing
• /
• v.14 no.5
• /
• pp.40-52
• /
• 2018

Solid state drive (SSD) cache technologies that are used as a second-tier cache between the main memory and hard disk drive (HDD) have been widely studied. The SSD cache requires a new prefetching scheme as well as cache replacement algorithms. This paper presents a prefetching scheme for a storage-class cache using SSD. This prefetching scheme is designed for the storage-class cache and based on a long-term scheduling in contrast to the short-term prefetching in the main memory. Traditional prefetching algorithms just consider only read, but the presented prefetching scheme considers both read and write. An experimental evaluation shows 2.3% to 17.8% of hit rate with a 64GB of SSD and the 4GiB of prefetching size using an I/O trace of 14 days. The proposed prefetching scheme showed significant improvement of cache hit rate and can be easily implemented in storage-class cache systems.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.15 no.5
• /
• pp.1590-1609
• /
• 2021

Laughter is one of the most important nonverbal sound that human generates. It is a means for expressing his emotions. The acoustic and contextual features of this specific sound are different from those of speech and many difficulties arise during their modeling process. During this work, we propose an audio laughter generation system based on unsupervised generative models: the autoencoder (AE) and its variants. This procedure is the association of three main sub-process, (1) the analysis which consist of extracting the log magnitude spectrogram from the laughter database, (2) the generative models training, (3) the synthesis stage which incorporate the involvement of an intermediate mechanism: the vocoder. To improve the synthesis quality, we suggest two hybrid models (LSTM-VAE, GRU-VAE and CNN-VAE) that combine the representation learning capacity of variational autoencoder (VAE) with the temporal modelling ability of a long short-term memory RNN (LSTM) and the CNN ability to learn invariant features. To figure out the performance of our proposed audio laughter generation process, objective evaluation (RMSE) and a perceptual audio quality test (listening test) were conducted. According to these evaluation metrics, we can show that the GRU-VAE outperforms the other VAE models.

• Journal of KIISE
• /
• v.42 no.6
• /
• pp.691-698
• /
• 2015

Application launch time is an important performance metric to user experience in desktop and laptop environment, which mostly depends on the performance of secondary storage. Application launch times can be reduced by utilizing solid-state drive (SSD) instead of hard disk drive (HDD). However, considering a cost-performance trade-off, utilizing SSDs as caches for slow HDDs is a practicable alternative in reducing the application launch times. We propose a new SSD caching scheme which migrates data blocks from HDDs to SSDs. Our scheme operates entirely in the file system level and does not require an extra layer for mapping SSD-cached data that is essential in most other schemes. In particular, our scheme does not incur mapping overheads that cause significant burdens on the main memory, CPU, and SSD space for mapping table. Experimental results conducted with 8 popular applications demonstrate our scheme yields 56% of performance gain in application launch, when data blocks along with metadata are migrated.

• The KIPS Transactions:PartD
• /
• v.12D no.5 s.101
• /
• pp.689-698
• /
• 2005

Various systems are used to provide the location based services. But, the existing systems have some problems which have difficulties in dealing with faster services for above million people. In order to solve it, a multi-level DBMS which supports both fast data processing and large data management support should be used. The multi-level DBMS with snapshots has all the data existing in disk database and the data which are required to be processed for fast processing are managed in main memory database as snapshots. To optimize performance of this system for location based services, the query classification component which classifies the queries for efficient snapshot usage is needed. In this paper, the query classification component in multi-level DBMS for location based services is designed and implemented. The proposed component classifies queries into three types: (1) memory query, (2) disk query, (3) hybrid query, and increases the rate of snapshot usage. In addition, it applies division mechanisms which divide aspatial and spatial filter condition for partial snapshot usage. Hence, the proposed component enhances system performance by maximizing the usage of snapshot as a result of the efficient query classification.