• Proceedings of the Korean Institute Of Construction Engineering and Management
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• autumn
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• pp.410-415
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• 2001

Earned Value Management System(EVMS) has been considered as a useful tool of managing construction projects lately and its instruction into a private industry is now under consideration by the Korean government. It is on the basis of C/SCSC that had been released by the U.S. Department of Defense(DOD) since 1967. Its research has been in the active progress in order to utilize the earned value concept as a project management tool for construction project ordered by both government and private sector. Material Requirement Planning(MRP) is also known as a tool of planning and scheduling resources for assembly product as a part of inventory control models in the manufacturing industry. The purpose of this study is the effective employment of Earned Value Management to manage the construction projects by utilizing Material Requirement Planning(MRP), based on project management software and Workpackaging model.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.26 no.11C
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• pp.113-122
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• 2001

Several guidelines can be developed for a satellite-based ATM switch. One of the most important of these is that the switch must provide a requirement for CLRs on the order of 10-10 to meet the QoS of high- performance traffic and avoid costly retransmissions. In this paper, the proposed approach shows not only the better traffic performance but also requires the little switching elements and buffers compared with original Knockout switch and other scheduling algorithm. As a result, the complexity becomes reduced. Simulation results indicate that proposed approach shows excellent cell loss ratio compared with existing switch architecture. Also, iii performance can be approached to the cell loss ratio, which is requirement for the satellite system, as window size increases. An(1 it shows thats low complexity is induced. Therefore, the proposed approach is appropriate for satellite on-board ATM switch architecture.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.23 no.6
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• pp.1514-1525
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• 1998

Two main characteristics of VBR MPEG video traffic are different statistics according to different picture types and the periodic traffic pattern due to GOP structure. Especially, the I-pictures at the beginning of each GOP generate $$\mu$h more traffic than other pictures. When several VBR Mpeg video sources are superposed, the I-picture starting times of these sources may significantly affect the cell loss characteristics of ATM $$\mu$tiplexers. In this paper, we propse a performance model for ATM $$\mu$tiplexers with VBR MPEG video sources whose starting times are arbitrary given. For analysis, both single and superposed source traffic are modeled as NDPPs (non-deterministic periodic processes), and the ATM $$\mu$tiplexer is modeled as a U-state NDPPD/D/1/B queueing system. It is hown that the numerical results are very close to the si$$\mu$ation results. From the relationships between the starting tiem distributions and the corresponding $$\mu$tiplexer performances, some considerations for designing a scheduling policy in order to obtain the maxi$$\mu$ $$\mu$tiplexing gain are presented.

• Journal of Communications and Networks
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• v.14 no.6
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• pp.662-671
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• 2012

Plug-in hybrid electric vehicles (PHEVs) will be widely used in future transportation systems to reduce oil fuel consumption. Therefore, the electrical energy demand will be increased due to the charging of a large number of vehicles. Without intelligent control strategies, the charging process can easily overload the electricity grid at peak hours. In this paper, we consider a smart charging and discharging process for multiple PHEVs in a building's garage to optimize the energy consumption profile of the building. We formulate a centralized optimization problem in which the building controller or planner aims to minimize the square Euclidean distance between the instantaneous energy demand and the average demand of the building by controlling the charging and discharging schedules of PHEVs (or 'users'). The PHEVs' batteries will be charged during low-demand periods and discharged during high-demand periods in order to reduce the peak load of the building. In a decentralized system, we design an energy cost-sharing model and apply a non-cooperative approach to formulate an energy charging and discharging scheduling game, in which the players are the users, their strategies are the battery charging and discharging schedules, and the utility function of each user is defined as the negative total energy payment to the building. Based on the game theory setup, we also propose a distributed algorithm in which each PHEV independently selects its best strategy to maximize the utility function. The PHEVs update the building planner with their energy charging and discharging schedules. We also show that the PHEV owners will have an incentive to participate in the energy charging and discharging game. Simulation results verify that the proposed distributed algorithm will minimize the peak load and the total energy cost simultaneously.

• Journal of Digital Contents Society
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• v.10 no.1
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• pp.169-175
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• 2009

Grid computing is an application to obtain the most efficient performance from computing resources in terms of cost and convenience. It is also considered as a good method to solve a problem that cannot be settled by conventional computing technologies such as clustering or is requiring supercomputing capability due to its complex and long-running task. In order to run grid computing effectively, it needs to connect high-performance computing resources in real-time which are distributed geographically. Answering to the needs of this grid application, researchers in several universities with Argonne National Laboratory in the USA (ANL) as the main axis have developed Globus. It is noticed, however, that the quality of service (QoS) is not guaranteed when certain jobs are exchanged through networks in the context of Globus. To tackle with this problem, the ANL has invented Globus Architecture for Reservation and Allocation (GARA). The researchers of this paper constructed a testbed for evaluating the ability to reserve resource in the GARA system and implemented the GARA code for it. We analyzed the applied results and discussed future research plans.

• The Journal of the Korea Contents Association
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• v.4 no.2
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• pp.50-60
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• 2004

Recently, most of the embedded system is required not only many functions but also real-time characteristics in purpose. In the hard real-time system, especially, strict deadline of periodic task can affect the performance of the system. In this paper, we design and implement the scheduler based on RM(Rate-Monotonic) rule. This scheduler makes feasible patterns based on EDF(Earliest deadline first) rule with extended schedulability inspection before execution, for periodic task-set that has high CPU utilization and then, execute periodic task-set depended on feasible patterns. The feasible pattern formed into EDF rule is capable of the efficiency of CPU up to 100 percentage and by the referenced execution of the feasible pattern is possible of removing the red-time scheduling overhead that is the defect of the order of dynamic assignment rule.

• Journal of the Korean Institute of Intelligent Systems
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• v.13 no.6
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• pp.635-642
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• 2003

Reinforcement learning got successful results in a lot of applications such as control and scheduling. Various function approximation methods have been studied in order to improve the learning speed and to solve the shortage of storage in the standard reinforcement learning algorithm of Q-Learning. Most function approximation methods remove some special quality of reinforcement learning and need prior knowledge and preprocessing. Fuzzy Q-Learning needs preprocessing to define fuzzy variables and Local Weighted Regression uses training examples. In this paper, we propose a function approximation method, Fuzzy Q-Map that is based on on-line fuzzy clustering. Fuzzy Q-Map classifies a query state and predicts a suitable action according to the membership degree. We applied the Fuzzy Q-Map, CMAC and LWR to the mountain car problem. Fuzzy Q-Map reached the optimal prediction rate faster than CMAC and the lower prediction rate was seen than LWR that uses training example.

• Journal of Intelligence and Information Systems
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• v.12 no.2
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• pp.99-123
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• 2006

In an effect to composite an optimal supply chain, this study has introduced an agent-based negotiation as a method to assign a lot of orders to a large number of participants. As a resources allocation mechanism to form a strategic cooperation based on information sharing between supply chain members(buyers, manufacturers, suppliers), this agent negotiation provides coordination functions allowing all participants to make a profit and accomplishing Pareto optimum solution from the viewpoint of a whole supply chain. A SET model-based scheduling takes into consideration both earliness production cost and tardiness production cost, along with a competitive relationship between multiple participants. This study has tried to prove that the result of an agent-based negotiation is a Pareto optimal solution under the dynamic supply chain environment, establishing the mathematical formulation for a performance test, and making a comparison with the heuristic Branch & Bound method.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.14 no.12
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• pp.2811-2817
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• 2010

In this paper we propose the QAC-MAC that supports Quality of Service(QoS) and saves energy resources of the sensor node, and hence prolonging the lifetime of the sensor network with multiple sink nodes. Generally, the nodes nearest to the sink node often experience heavy congestion since all data is forwarded toward the sink through those nodes. So this critically effects on the delay-constraint data traffics. QAC-MAC uses a hybrid mechanism that adapts scheduled scheme for medium access and scheduling and unscheduled scheme based on TDMA for no data collision transmission. Generally speaking, characteristics of the real-time traffic with higher priority tends to be bursty and has same destination. QAC-MAC adapts cross-layer concept to rearrange the data transmission order in each sensor node's queue, saves energy consumption by allowing few nodes in data transmission, and prolongs the network lifetime.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.22 no.8
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• pp.1133-1138
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• 2018

Lightweight Encryption Algorithm (LEA) is one of the most promising lightweight block cipher algorithm due to its high efficiency and security level. There are many works on the efficient LEA implementation. However, many works missed the secure application services where the IoT platforms perform secure communications between heterogeneous IoT platforms. In order to establish the secure communication channel between them, the encryption should be performed in the on-the-fly method. In this paper, we present the LEA implementation performing the on-the-fly method over the ARM Cortex-M3 processors. The general purpose registers are fully utilized to retain the required variables for the key scheduling and encryption operations and the rotation operation is optimized away by using the barrel-shifter technique. Since the on-the-fly method does not store the round keys, the RAM requirements are minimized. The implementation is evaluated over the ARM Cortex-M3 processor and it only requires 34 cycles/byte.