• The KIPS Transactions:PartA
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• v.18A no.1
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• pp.19-24
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• 2011

As era of multi-core processors has arrived, transactional memory has been considered as an effective method to achieve easy and fast multi-threaded programming. Various hardware transactional memory systems such as UTM, VTM, FastTM, LogTM, and LogTM-SE, have been introduced in order to implement high-performance multi-core processors. Especially, LogTM-SE has provided study performance with an efficient memory management policy and a practical thread scheduling method through conflict detection based on signatures. However, increasing number of cores on a processor imposes the hardware complexity for signature processing. This causes overall performance degradation due to the heavy workload on signature comparison. In this paper, we propose a new architecture of multiple signature comparison to improve conflict detection of signature based transactional memory systems.

• The KIPS Transactions:PartC
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• v.9C no.1
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• pp.21-30
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• 2002

Nowadays the fair queuing field is studied actively for solving the unfair queuing problem which degrades the service performance of various applications on network. Above all DRR is a scheme that has lower work complexity and can be implemented easily. It guarantees the fair service by serving each queue every round Service Quantum(SQ) that includes the service deficit of the previous round. But it increases the delay by the numbers of unnecessary resetting of SQ or round circulation for the service that have the packet size over maximum several kbyte. In this paper, We propose the method that sets SQ dynamically to minimize this problem and the method that minimizes the work complexity on processing of packet. The proposed scheme minimizes the delay on various applications in enterprise environment by setting SQ dynamically and processing the packet simply.

• Journal of Electrical Engineering and Technology
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• v.13 no.3
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• pp.1069-1078
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• 2018

Demand response (DR) programs give opportunity to consumers to manage their electricity bills. Besides, distribution system operator (DSO) is interested in using DR programs to obtain technical and economic benefits for distribution network. Since small consumers have difficulties to individually take part in the electricity market, an entity named demand response provider (DRP) has been recently defined to aggregate the DR of small consumers. However, implementing DR programs face challenges to fairly allocate benefits and payments between DRP and DSO. This paper presents a procedure for modeling the interaction between DRP and DSO based on a bilevel programming model. Both DSO and DRP behave from their own viewpoint with different objective functions. On the one hand, DRP bids the potential of DR programs, which are load shifting and load curtailment, to maximize its expected profit and on the other hand, DSO purchases electric power from either the electricity market or DRP to supply its consumers by minimizing its overall cost. In the proposed bilevel programming approach, the upper level problem represents the DRP decisions, while the lower level problem represents the DSO behavior. The obtained bilevel programming problem (BPP) is converted into a single level optimizing problem using its Karush-Kuhn-Tucker (KKT) optimality conditions. Furthermore, point estimate method (PEM) is employed to model the uncertainties of the power demands and the electricity market prices. The efficiency of the presented model is verified through the case studies and analysis of the obtained results.

• Journal of KIISE:Databases
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• v.37 no.4
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• pp.203-208
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• 2010

This paper deals with an efficient index scheduling technique based on Hilbert curve and MBR for k-NN query in a single wireless broadcast channel environment. Previous works have two major problems. One is that they need a long time to process queries due to the back-tracking problem. The other is that they have to download too many spatial data since they can not reduce search space rapidly. Our proposed method broadcasts spatial data based on Hilbert curve order where a distributed index table is also broadcast with each spatial data. Each entry of index table represents the MBR which groups spatial data. By predicting the unknown location of spatial data, our proposed index scheme allows mobile clients to remove unnecessary data and to reduce search space rapidly. As a result, our method gives the decreased tuning time and access latency.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.41 no.4
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• pp.138-145
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• 2018

In the field of optimization, many studies have been performed on various types of Vehicle Routing Problem (VRP) for a long time. A variety of models have been derived to extend the basic VRP model, to consider multiple truck terminal, multiple pickup and delivery, and time windows characteristics. A lot of research has been performed to find better solutions in a reasonable time for these models with heuristic approaches. In this paper, by considering realtime traffic characteristics in Map Navigation environment, we proposed a method to manage realistic optimal path allocation for the logistics trucks and cargoes, which are dispersed, in order to realize the realistic cargo mixing allowance and time constraint enforcement which were required as the most important points for an online logistics brokerage service company. Then we developed a prototype system that can support above functionality together with delivery status monitoring on Map Navigation environment. First, through Map Navigation system, we derived information such as navigation-based travel time required for logistics allocation scheduling based on multiple terminal multiple pickup and delivery models with time constraints. Especially, the travel time can be actually obtained by using the Map Navigation system by reflecting the road situation and traffic. Second, we made a mathematical model for optimal path allocation using the derived information, and solved it using an optimization solver. Third, we constructed the prototype system to provide the proposed method together with realtime logistics monitoring by arranging the allocation results in the Map Navigation environment.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.20 no.9
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• pp.133-141
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• 2019

Crew rostering in railway operations is usually done by arranging a crew diagram in accordance with working standards every month. This study was done to identify the problems related to the creation of crew rosters in railway operations and to suggest an optimum crew rostering method that can be applied in railway operations planning. To do this, the work standards of a railway company were identified, and a genetic algorithm was used to develop an optimal roster with equal working time while considering actual working patterns. The optimization process is composed of analysis of the input data, creation of work patterns, creation of a solution, and optimization steps. To verify the method, the roster derived from the proposed process was compared with a manually created roster. The results of the study could be used to reduce the deviation of business hours when generating a roster because the standard deviation of working time is the objective function.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.20 no.6
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• pp.3-13
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• 2010

Differential Fault Analysis (DFA) is widely known for one of the most efficient method analyzing block cipher. In this paper, we propose a new type of DFA on DES (Data Encryption Standard). DFA on DES was first introduced by Biham and Shamir, then Rivain recently introduced DFA on DES middle rounds (9-12 round). However previous attacks on DES can only be applied to the encryption process. Meanwhile, we first propose the DFA on DES key-schedule. In this paper, we proposed a more efficient DFA on DES key schedule with random fault. The proposed DFA method retrieves the key using a more practical fault model and requires fewer faults than the previous DFA on DES.

• Journal of Korea Water Resources Association
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• v.55 no.spc1
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• pp.1197-1210
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• 2022

Recently, users' complaints on drinking water quality are increasing according to emerging interest in the drinking water service issues such as pipe aging and various water quality accidents. In the case of drinking water quality complaints, not only the water pollution but also the inconvenience on the chlorine residual for disinfection are included, thus various efforts, such as rechlorination treatment, are being attempted in order to keep the chlorine concentration supplied evenly. In this research, for a more accurate water quality simulation of water distribution network, the water quality reaction coefficients were estimated, and an optimization method of chlorination/ rechlorination scheduling was proposed consideirng satisfaction of water quality standards and chlorine residual equalization. The proposed method was applied to a large-scale real water network, and various chlorination schemes were comparatively analyzed through the grid search algorithm and optimized based on the suitability and uniformity of supplied chlorine residual concentration.

• Journal of the Korea Society of Computer and Information
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• v.14 no.2
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• pp.103-110
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• 2009

We are witnessing rapid increase of the number of wireless devices available today such as cell phones, PDAs, Wibro enabled devices. Because of the inherent limitation of the bandwidth available for wireless channels, broadcast systems have attracted the attention of the research community. The main problem in this area is to develop an efficient broadcast program. In this paper, we propose a dynamic broadcast method that overcomes the limitations of static broadcast programs. It optimizes the scheduling based on the probabilistic model of user requests. We show that dynamic broadcast system can indeed improve the quality of service using user requests. This paper extends our previous work in [1] to include more thorough explanation of the proposed methodology and diverse performance evaluation models.

• The Journal of the Korea institute of electronic communication sciences
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• v.18 no.6
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• pp.1081-1086
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• 2023

The rapid growth and increasing complexity of modern networks have highlighted the limitations of traditional network architectures. The emergence of SDN (Software-Defined Network) in response to these challenges has changed the existing network environment. The SDN separates the control unit and the data unit, and adjusts the network operation using a centralized controller. However, this structure has also recently caused a huge amount of traffic due to the rapid spread of numerous Internet of Things (IoT) devices, which has not only slowed the transmission speed of the network but also made it difficult to ensure quality of service (QoS). Therefore, this paper proposes a method of load distribution by switching the IP and any server (processor) from the existing data processing scheduling technique, RR (Round-Robin), to mapping when a large amount of data flows in from a specific IP, that is, server overload and data loss.