• The Journal of Korean Institute of Communications and Information Sciences
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• v.37 no.4B
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• pp.245-257
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• 2012

As one of the most challenging tasks in designing the Internet routers, packet classification is required to achieve the wire-speed processing for every incoming packet. Packet classification algorithm which applies binary search on trie levels to the area-based quad-trie is an efficient algorithm. However, it has a problem of unnecessary access to a hash table, even when there is no node in the corresponding level of the trie. In order to avoid the unnecessary off-chip memory access, we proposed an algorithm using Bloom filters along with the binary search on levels to multiple disjoint tries. For ACL, FW, IPC sets with about 1000, 5000, and 10000 rules, performance evaluation result shows that the search performance is improved by 21 to 33 percent by adding Bloom filters.

• Journal of Digital Contents Society
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• v.14 no.1
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• pp.89-95
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• 2013

Many peer-to-peer (p2p) systems have been studied in distributed, ubiquitous computing environments. Distributed hash table (DHT)-based p2p systems can improve load-balancing even though locality utilization and user mobility are not guaranteed. We propose a mobile locality-based hierarchical p2p overlay network (MLH-Net) to address locality problems without any other services. MLH-Net utilizes mobility features in a mobile environment. MLH-Net is constructed as two layers, an upper layer formed with super-nodes and a lower layer formed with normal-nodes. The simulation results demonstrate that MLH-Net can decrease discovery routing hops by 13% compared with JXTA and 69% compared with Chord. It can decrease the discovery routing distance by 17% compared with JXTA and 83% compared with Chord depending on the environment.

• Journal of the Korea Society of Computer and Information
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• v.16 no.3
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• pp.131-140
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• 2011

File pollution (i.e., sharing of corrupted files, or contaminating index information with bogus index records) is a de facto problem in many file sharing Peer-to-Peer (P2P) systems in use today. Since pollution squanders network resources and frustrates users with unprofitable downloads (due to corrupted files) and unproductive download trials (due to bogus index records), the viability of P2P systems (and similar distributed information-sharing applications) is questionable unless properly addressed. Thus, developing effective anti-pollution mechanisms is an immediate problem in this literature. This paper provides useful information and deep insight with future researchers who want to design an effective anti-pollution mechanism throughout an extensive measurement study of user behavior and file pollution in a representative DHT-based P2P system, the Kad network.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• v.9 no.2
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• pp.89-92
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• 2005

Centralized P2P system, Napster and Unstructured P2P system, Gnutella accomplish main current. Centralized system and unstructured system have a restriction in a scalability. To solve the this problem, structured system is appeared. CAN, Chord, Pastry and Tapestry are delegation of this system. Although structured system don't aware physical proximity of node because it uses Distribute Hash Table. In proposing system, a node can communicate with physical proximity of node using concept of LAN. Internet traffic is also decreased because communication in the Chord network divide in two(original network and sub network).

• Journal of Computing Science and Engineering
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• v.1 no.2
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• pp.177-194
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• 2007

Index selection is one of the most important decisions to take in the physical design of relational data warehouses. Indices reduce significantly the cost of processing complex OLAP queries, but require storage cost and induce maintenance overhead. Two main types of indices are available: mono-attribute indices (e.g., B-tree, bitmap, hash, etc.) and multi-attribute indices (join indices, bitmap join indices). To optimize star join queries characterized by joins between a large fact table and multiple dimension tables and selections on dimension tables, bitmap join indices are well adapted. They require less storage cost due to their binary representation. However, selecting these indices is a difficult task due to the exponential number of candidate attributes to be indexed. Most of approaches for index selection follow two main steps: (1) pruning the search space (i.e., reducing the number of candidate attributes) and (2) selecting indices using the pruned search space. In this paper, we first propose a data mining driven approach to prune the search space of bitmap join index selection problem. As opposed to an existing our technique that only uses frequency of attributes in queries as a pruning metric, our technique uses not only frequencies, but also other parameters such as the size of dimension tables involved in the indexing process, size of each dimension tuple, and page size on disk. We then define a greedy algorithm to select bitmap join indices that minimize processing cost and verify storage constraint. Finally, in order to evaluate the efficiency of our approach, we compare it with some existing techniques.

• Journal of KIISE:Computing Practices and Letters
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• v.15 no.2
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• pp.77-88
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• 2009

According to the size of NAND flash memory as the storage system of mobile device becomes large, the performance of address translation and life cycle management in FTL (Flash Translation Layer) to interact with file system becomes very important. In this paper, we propose the continuity counters, which represent the number of continuous physical blocks whose logical addresses are consecutive, to reduce the number of address translation. Furthermore we propose the prefetching method which preloads frequently accessed pages into main memory to enhance I/O performance of flash memory. Besides, we use the 2-bit write prediction and asynchronous writing method to predict addresses repeatedly referenced from host and prevent from writing overhead. The experiments show that the proposed method improves the I/O performance and extends the life cycle of flash memory. As a result, proposed CFTL (Clustered Flash Translation Layer)'s performance of address translation is faster 20% than conventional FTLs. Furthermore, CFTL is reduced about 50% writing time than that of conventional FTLs.

• The Journal of Korean Institute of Next Generation Computing
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• v.15 no.5
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• pp.7-19
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• 2019

Ransomware is a malicious program that requires the cost of decryption after encrypting files on the user's desktop. Since the frequency and the financial damage of ransomware attacks are increasing each year, ransomware prevention, detection and recovery system are needed. Baek et al. proposed SSD-Insider, an algorithm for detecting ransomware within SSD. In this paper, we propose an AdvanSSD-Insider algorithm that substitutes a hash table used for the overwriting check with a bloom filter in the SSD-Insider. Experimental results show that the AdvanSSD-Insider algorithm reduces memory usage by up to 90% and execution time by up to 77% compared to the SSD-Insider algorithm and achieves the same detection accuracy. In addition, the AdvanSSD-Insider algorithm can monitor 10 times longer than the SSD-Insider algorithm in same memory condition. As a result, detection accuracy is increased for some ransomware which was difficult to detect using previous algorithm.

• The Journal of the Korea institute of electronic communication sciences
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• v.14 no.2
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• pp.417-424
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• 2019

This paper presents the design of a JPEG-LS codec for lossless image compression from AR/VR device. The proposed JPEG-LS(: LosSless) codec is mainly composed of a context modeling block, a context update block, a pixel prediction block, a prediction error coding block, a data packetizer block, and a memory block. All operations are organized in a fully pipelined architecture for real time image processing and the LOCO-I compression algorithm using improved 2D approach to compliant with the SBT coding. Compared with a similar study in JPEG-LS, the Block-RAM size of proposed STB-FLC architecture is reduced to 1/3 compact and the parallel design of the predication block could improved the processing speed.

• Database Research
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• v.34 no.3
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• pp.14-27
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• 2018

Recently, to alleviate the memory bottleneck problme occurred in Symmetric Multiprocessing (SMP) architecture, Non-Uniform Memory Access (NUMA) architecture was proposed. In addition, since an aggregation operator is an important operator providing properties and summary of data, the efficiency of the aggregation operator is crucial to overall performance of a system. Thus, in this paper, we propose an efficient aggregation processing technique on NUMA architecture. Our proposed technique consists of partition phase and merge phase. In the partition phase, the target relation is partitioned into several partial relations according to grouping attribute. Thus, since each thread can process aggregation operator on partial relation independently, we prevent the remote memory access during the merge phase. Furthermore, at the merge phase, we improve the performance of the aggregation processing by letting each thread compute aggregation with a local hash table as well as avoiding lock contention to merge aggregation results generated by all threads into one.

• Smart Media Journal
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• v.10 no.1
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• pp.25-31
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• 2021

As the machine learning becomes more common, development of application using machine learning is actively increasing. In addition, research on machine learning platform to support development of application is also increasing. However, despite the increasing of research on machine learning platform, research on suitable load balancing for machine learning platform is insufficient. Therefore, in this paper, we propose a load balancing scheme that can be applied to machine learning distributed environment. The proposed scheme composes distributed servers in a level hash table structure and assigns machine learning task to the server in consideration of the performance of each server. We implemented distributed servers and experimented, and compared the performance with the existing hashing scheme. Compared with the existing hashing scheme, the proposed scheme showed an average 26% speed improvement, and more than 38% reduced the number of waiting tasks to assign to the server.