• The KIPS Transactions:PartA
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• v.16A no.5
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• pp.357-368
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• 2009

Mobile IP storage has been proposed to overcome storage limitation in the flash memory and hard disks. It provides almost capacity-free space for mobile devices over wireless IP networks. However, battery lifetime of the mobile devices is reduced rapidly because of power consumption with continuous use of a WLAN device when multimedia contents are being streamed through the mobile IP storage. This paper proposes an energy-efficient WLAN device power control technique for streaming multimedia contents with the mobile IP storage. The proposed technique consists of a prefetch buffer input/output module, a WLAN device power control module, and a reconfigurable prefetch buffer module. Besides, it adaptively determines the size of the prefetch buffer according to a quality of the multimedia contents, and it dynamically controls the power mode of the WLAN device on the basis of power on-off operations while streaming the multimedia contents. We evaluate the performance of the proposed technique on a PXA270-based mobile device that employs the embedded linux 2.6.11, Intel iSCSI reference codes, and a WLAN device. Extensive experiments reveal that the proposed technique can save the energy consumption of the WLAN device up to 8.5 times with QVGA multimedia contents, as compared with no power control.

• The KIPS Transactions:PartA
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• v.8A no.4
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• pp.509-516
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• 2001

As results of many genome projects, genomic sequences of many organisms are revealed. Various methods such as global alignment, local alignment are used to analyze the sequences of the organisms, and k -mer analysis is one of the methods for analyzing the genomic sequences. The k -mer analysis explores the frequencies of all k-mers or the symmetry of them where the k -mer is the sequenced base with the length of k. However, existing on-memory algorithms are not applicable to the k -mer analysis because a whole genomic sequence is usually a large text. Therefore, efficient data structures and algorithms are needed. String B-tree is a good data structure that supports external memory and fits into pattern matching. In this paper, we improve the string B-tree in order to efficiently apply the data structure to k -mer analysis, and the results of k -mer analysis for C. elegans and other 30 genomic sequences are shown. We present a visualization system which enables users to investigate the distribution and symmetry of the frequencies of all k -mers using CGR (Chaotic Game Representation). We also describe the method to find the signature which is the part of the sequence that is similar to the whole genomic sequence.

• Journal of KIISE:Computer Systems and Theory
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• v.36 no.1
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• pp.26-32
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• 2009

The multi-level storage architecture has been widely adopted in servers and data centers. However, while prefetching has been shown as a crucial technique to exploit sequentiality in accesses common for such systems and hide the increasing relative cost of disk I/O, existing multi-level storage studies have focused mostly on cache replacement strategies. In this paper, we show that prefetching algorithms designed for single-level systems may have their limitations magnified when applied to multi-level systems. Overly conservative prefetching will not be able to effectively use the lower-level cache space, while overly aggressive prefetching will be compounded across levels and generate large amounts of wasted prefetch. We design and implement a hierarchy-aware lower-level prefetching strategy called PMS(Prefetching strategy for Multi-level Storage system) that applicable to any upper level prefetching algorithms. PMS does not require any application hints, a priori knowledge from the application or modification to the va interface. Instead, it monitors the upper-level access patterns as well as the lower-level cache status, and dynamically adjusts the aggressiveness of the lower-level prefetching activities. We evaluated the PMS through extensive simulation studies using a verified multi-level storage simulator, an accurate disk simulator, and access traces with different access patterns. Our results indicate that PMS dynamically controls aggressiveness of lower-level prefetching in reaction to multiple system and workload parameters, improving the overall system performance in all 32 test cases. Working with four well-known existing prefetching algorithms adopted in real systems, PMS obtains an improvement of up to 35% for the average request response time, with an average improvement of 16.56% over all cases.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2009.05a
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• pp.112-115
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• 2009

Inter-Prediction is always the main bottleneck in H.264/AVC Baseline Profile. This paper describes an efficient Inter-Prediction hardware architecture design. H.264/AVC decoder supports various block types such as $16{\times}16$, $16{\times}8$, $8{\times}16$, $8{\times}8$, $8{\times}4$, $4{\times}8$, $4{\times}4$ block types. Reference Software(JM) only considers the $4{\times}4$ block type when the reference block is being fetched. This causes duplicated pixels which needs extra fetch cycles. In order to eliminate some of the duplicated pixels, the $8{\times}8$ and $4{\times}4$ block types were considered in the previous design. If the block size is larger than or equal to the $8{\times}8$ block type, it will be separated into several $8{\times}8$ block types and if the block size is smaller than the $8{\times}8$ block type it will be separated into several $4{\times}4$ blocks. For further reduction of the fetch cycles, the various block types are considered in this paper. As a result, the maximum cycle reduction percentage is 18.6% comparing with the previous design.

• Journal of the Korea Society of Computer and Information
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• v.18 no.11
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• pp.1-12
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• 2013

In multi-core processors, Last Level Cache(LLC) can reduce the speed gap between the memory and the core. For this reason, LLC has big impact on the performance of processors. LLC is composed of shared cache and private cache. In computer architecture community, most researchers have mainly focused on the management techniques for shared cache, while management techniques for private cache have not been widely researched. In conventional private LLC, memory is statically assigned to each core, resulting in serious performance degradation when the workloads are not fairly distributed. To overcome this problem, this paper proposes the replacement policy for managing private cache of LLC efficiently. As proposed core-aware cache replacement policy can reconfigure LLC dynamically, hit rate of LLC is increases drastically. Moreover, proposed policy uses 2-bit saturating counters to improve the performance. According to our simulation results, the proposed method can improve hit rates by 9.23% and reduce the access time by 12.85% compared to the conventional method.

• KIPS Transactions on Software and Data Engineering
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• v.10 no.5
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• pp.195-200
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• 2021

Due to the development of video sharing platforms, the amount of video uploads is exploding. Such videos often include various types of music, among which cover songs are included. In order to protect the copyright of music, an algorithm to find the original song of the cover song is essential. However, it is not easy to find the original song because the cover song is a modification of the composition, speed and overall structure of the original song. So far, there is no known effective algorithm for searching the original song of the cover song. In this paper, we propose an algorithm for searching the original song of the cover song using the inflection points of the melody line. Inflection points represent the characteristic points of change in the melody sequence. The proposed algorithm compares the original song and the cover song using the sequence of inflection points for the representative phrase of the original song. Since the characteristics of the representative phrase are used, even if the cover song is a song made by modifying the overall composition of the song, the algorithm's search performance is excellent. Also, since the proposed algorithm uses only the features of the inflection point sequence, the memory usage is very low. The efficiency of the algorithm was verified through performance evaluation.

• Geophysics and Geophysical Exploration
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• v.25 no.3
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• pp.109-119
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• 2022

The computational efficiency of reverse time migration (RTM) based on numerical modeling is not secured due to the high-frequency band of several hundred Hz or higher for data acquired through a three-dimensional (3D) ultra-high-resolution (UHR) seismic survey. Therefore, this study develops an RTM program to derive high-quality 3D geological structures using UHR seismic data. In the traditional 3D RTM program, an excitation amplitude technique that stores only the maximum amplitude of the source wavefield and a domain-limiting technique that minimizes the modeling area where the source and receivers are located were used to significantly reduce memory usage and calculation time. The program developed through this study successfully derived a 3D migration image with a horizontal grid size of 1 m for the 3D UHR seismic survey data obtained from the Korea Institute of Geoscience and Mineral Resources in 2019, and geological analysis was conducted.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2022.05a
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• pp.171-173
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• 2022

The 4th industrial revolution technology is developing people's lives more efficiently. GIS provided on the Internet services such as traffic information and time information makes people getting more quickly to destination. National geographic information service(NGIS) and each local government are making basic data to investigate SOC accessibility for analyzing optimal point. To construct the shortest distance, the accessibility from the starting point to the arrival point is analyzed. Applying road network map, the starting point and the ending point, the shortest distance, the optimal accessibility is calculated by using Dijkstra algorithm. The analysis information from multiple starting points to multiple destinations was required more than 3 steps of manual analysis to decide the position for the optimal point, within about 0.1% error. It took more time to process the many-to-many (M×N) calculation, requiring at least 32G memory specification of the computer. If an optimal proximity analysis service is provided at a desired location more versatile, it is possible to efficiently analyze locations that are vulnerable to business start-up and living facilities access, and facility selection for the public.

• Journal of Internet Computing and Services
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• v.15 no.3
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• pp.101-107
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• 2014

With the development of online service, recent forms of databases have been changed from static database structures to dynamic stream database structures. Previous data mining techniques have been used as tools of decision making such as establishment of marketing strategies and DNA analyses. However, the capability to analyze real-time data more quickly is necessary in the recent interesting areas such as sensor network, robotics, and artificial intelligence. Landmark window-based frequent pattern mining, one of the stream mining approaches, performs mining operations with respect to parts of databases or each transaction of them, instead of all the data. In this paper, we analyze and evaluate the techniques of the well-known landmark window-based frequent pattern mining algorithms, called Lossy counting and hMiner. When Lossy counting mines frequent patterns from a set of new transactions, it performs union operations between the previous and current mining results. hMiner, which is a state-of-the-art algorithm based on the landmark window model, conducts mining operations whenever a new transaction occurs. Since hMiner extracts frequent patterns as soon as a new transaction is entered, we can obtain the latest mining results reflecting real-time information. For this reason, such algorithms are also called online mining approaches. We evaluate and compare the performance of the primitive algorithm, Lossy counting and the latest one, hMiner. As the criteria of our performance analysis, we first consider algorithms' total runtime and average processing time per transaction. In addition, to compare the efficiency of storage structures between them, their maximum memory usage is also evaluated. Lastly, we show how stably the two algorithms conduct their mining works with respect to the databases that feature gradually increasing items. With respect to the evaluation results of mining time and transaction processing, hMiner has higher speed than that of Lossy counting. Since hMiner stores candidate frequent patterns in a hash method, it can directly access candidate frequent patterns. Meanwhile, Lossy counting stores them in a lattice manner; thus, it has to search for multiple nodes in order to access the candidate frequent patterns. On the other hand, hMiner shows worse performance than that of Lossy counting in terms of maximum memory usage. hMiner should have all of the information for candidate frequent patterns to store them to hash's buckets, while Lossy counting stores them, reducing their information by using the lattice method. Since the storage of Lossy counting can share items concurrently included in multiple patterns, its memory usage is more efficient than that of hMiner. However, hMiner presents better efficiency than that of Lossy counting with respect to scalability evaluation due to the following reasons. If the number of items is increased, shared items are decreased in contrast; thereby, Lossy counting's memory efficiency is weakened. Furthermore, if the number of transactions becomes higher, its pruning effect becomes worse. From the experimental results, we can determine that the landmark window-based frequent pattern mining algorithms are suitable for real-time systems although they require a significant amount of memory. Hence, we need to improve their data structures more efficiently in order to utilize them additionally in resource-constrained environments such as WSN(Wireless sensor network).

• Journal of KIISE:Computing Practices and Letters
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• v.9 no.4
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• pp.393-409
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• 2003

In this paper, we present a multi-task debugging environment for Qplus-T embedded-system such as internet information appliances. We will propose the structure and functions of a remote multi-task debugging environment supporting environment effective ross-development. And, we are going enhance the communication architecture between the host and target system to provide more efficient cross-development environment. The remote development toolset called Q+Esto consists to several independent support tools: an interactive shell, a remote debugger, a resource monitor, a target manager and a debug agent. Excepting a debug agent, all these support tools reside on the host systems. Using the remote multi-task debugger on the host, the developer can spawn and debug tasks on the target run-time system. It can also be attached to already-running tasks spawned from the application or from interactive shell. Application code can be viewed as C/C++ source, or as assembly-level code. It incorporates a variety of display windows for source, registers, local/global variables, stack frame, memory, event traces and so on. The target manager implements common functions that are shared by Q+Esto tools, e.g., the host-target communication, object file loading, and management of target-resident host tool´s memory pool and target system´s symbol-table, and so on. These functions are called OPEn C APIs and they greatly improve the extensibility of the Q+Esto Toolset. The Q+Esto target manager is responsible for communicating between host and target system. Also, there exist a counterpart on the target system communicating with the host target manager, which is called debug agent. Debug agent is a daemon task on real-time operating systems in the target system. It gets debugging requests from the host tools including debugger via target manager, interprets the requests, executes them and sends the results to the host.