• The Transactions of the Korean Institute of Electrical Engineers A
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• v.54 no.10
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• pp.496-499
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• 2005

In many parts of the world, the electric power industry is undergoing unprecedented changes. Therefore, in order to reform the electric power industry efficiently and minimize the confusion of this restructuring, the systematic studies related to transmission pricing and transmission cost allocation issues are required essentially. However, even now, the basis of transmission cost allocation rate is not equipped so that the regulation body has determined the allocating rate under the common practice. In this paper, we demonstrate that the decision of transmission cost allocation rate is the regulation body's own right. For this analysis, we apply game theory to the procedure determining this rate and the competition to determine this rate between gencos and distcos is modeled as the arbitration game.

• Proceedings of the KIEE Conference
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• 2002.11b
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• pp.375-377
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• 2002

In many parts of the world. the electricity industry is undergoing unprecedented changes. Hence, in order to reform the electricity industry readily and efficiently and minimize the confusion by these restructuring, it is required the systematic studies related to transmission pricing and transmission cost allocation issues. However, even now the basis of transmission cost allocation rate is not equipped so that the regulation body has determined the allocating rate under the common practice. In this paper it is demonstrated that the decision of transmission cost allocation rate is the regulation body's own right. For the analysis, game theory is applied to the procedure determining this rate and the competition to determine this rate between generators and distributors is modeled as the arbitration game.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.57 no.4
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• pp.576-581
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• 2008

Electricity Market in Korea can't provide locational price signal through energy price because energy market is CBP(Cost Based Pool) using uniform price. Generators don't want to locate in a densely populated load area(like the metropolitan area). Because they are paid more fixed cost in metropolitan area. This situation has loss and congestion occurred in power system. However energy market without price signal can't lead generator to the metropolitan. So, market participants should be provided price signal through the transmission price instead of energy price. This paper proposes transmission pricing method considering reliability cost in order to offer price signal. Also, it proposes the method to allocate the transmission cost to each transmission line user through a fair and a reasonable manner. The transmission price is decided by the reliability value of each line. If a transmission line of high reliability value is broke, users using that line will get a loss and a discomfort. So, it is fair that users using a transmission line of high reliability value pay more than the other users. Also, it is reasonable that a transmission line owner get paid more form users using that line.

• Proceedings of the KIEE Conference
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• 2003.07a
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• pp.360-362
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• 2003

In operation of distribution system, DGs(Distributed Generations) are installed as an alternative of extension and establishment of substations, transmission and distribution lines according to increasing power demand. Optimal capacity and allocation of DGs improve power quality and reliability. This paper proposes a method for determining the optimal number, size and allocation of DGs needed to minimize operation cost of distribution system. Capacity of DGs for economic operation of distribution system can be estimated by the load growth and line capacity during operation planning duration. DG allocations are determined to minimize total cost with failure rate and annual reliability cost of each load point using GA(Genetic Algorithm).

• ETRI Journal
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• v.29 no.4
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• pp.445-451
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• 2007

An adaptive modulation scheme is presented for multiuser orthogonal frequency-division multiplexing systems. The aim of the scheme is to minimize the total transmit power with a constraint on the transmission rate for users, assuming knowledge of the instantaneous channel gains for all users using a combined bit-loading and subcarrier allocation algorithm. The subcarrier allocation algorithm identifies the appropriate assignment of subcarriers to the users, while the bit-loading algorithm determines the number of bits given to each subcarrier. The proposed bit-loading algorithm is derived from the geometric progression of the additional transmission power required by the subcarriers and the arithmetic-geometric means inequality. This algorithm has a simple procedure and low computational complexity. A heuristic approach is also used for the subcarrier allocation algorithm, providing a trade-off between complexity and performance. Numerical results demonstrate that the proposed algorithms provide comparable performance with existing algorithms with low computational cost.

• Journal of Korea Multimedia Society
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• v.8 no.9
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• pp.1216-1226
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• 2005

In this paper, a preventive transmission rate decision algorithm, called PTRD, is proposed for the transmission of live video over networks with dynamic bandwidth allocation capability. Frame analyzer predicts the bit-rates of future frames before encoding by analyzing the source information such as spatial variances and the degree of scene changes. By using the predicted bit-rates, transmission rate bounds are derived from the constraints of encoder and decoder buffers. To resolve the problem of renegotiation cost increment due to frequent renegotiations, the PTRD algorithm is presented to decide transmission rates considering the elapsed time after the recent renegotiation and the perceived video quality. From the simulation results, compared to the normalized LMS based method, PTRD is shown to achieve high channel utilization with low renegotiation cost and no delay violation.

• Journal of Information Processing Systems
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• v.17 no.4
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• pp.721-736
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• 2021

For the mobile edge computing (MEC) system supporting dense network, a joint allocation algorithm of computing and communication resources based on reinforcement learning is proposed. The energy consumption of task execution is defined as the maximum energy consumption of each user's task execution in the system. Considering the constraints of task unloading, power allocation, transmission rate and calculation resource allocation, the problem of joint task unloading and resource allocation is modeled as a problem of maximum task execution energy consumption minimization. As a mixed integer nonlinear programming problem, it is difficult to be directly solve by traditional optimization methods. This paper uses reinforcement learning algorithm to solve this problem. Then, the Markov decision-making process and the theoretical basis of reinforcement learning are introduced to provide a theoretical basis for the algorithm simulation experiment. Based on the algorithm of reinforcement learning and joint allocation of communication resources, the joint optimization of data task unloading and power control strategy is carried out for each terminal device, and the local computing model and task unloading model are built. The simulation results show that the total task computation cost of the proposed algorithm is 5%-10% less than that of the two comparison algorithms under the same task input. At the same time, the total task computation cost of the proposed algorithm is more than 5% less than that of the two new comparison algorithms.

• Proceedings of the KIEE Conference
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• 2003.11a
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• pp.460-462
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• 2003

One of many elements considered important is TR-Cost in restructed electrical power market. KEMA supposed the TR-Cost system which involved an allocation rate of groups of generator and load as 5 to 5 but it isn't based on electrical and economic theory. Also there is a defect that we cann't calculate each allocation to numerous members forming the group of generators and loads. Therefore, in this paper, we propose an allocation method by using "generator forcused TR MLF" & "load forcused TR MLF" in consideration of economic signal.

• Journal of Navigation and Port Research
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• v.28 no.4
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• pp.299-303
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• 2004

In the Internet, to guarantee transmission rate and delay and to achieve fair bandwidth allocation, many per-flow scheduling algorithms, such as fair queueing, which have many desirable properties for congestion control, have been proposed and designed. However, algorithms based on per-flow need maintain rate state, buffer management and packet scheduling, so that it cost great deal ： implement. Therefore, in this paper, to implement routers cost-effectively, we propose CS-FNE algorithm based on FNE in Core-Stateless network We evaluate CS-FNE comparing with four additional algorithms i.e., CSFQ, FRED, RED and DRR, in several different, configurations and traffic sources. Through simulation results, we show that CS-FNE algorithm can allocate fair bandwidth approximately and is simpler and easier to implement than other per-flow basis queueing mechanisms.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.12
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• pp.5191-5211
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• 2016

It is essential to satisfy class-specific QoS constraints to provide broadband services for new generation networks. The present study proposes a QoS-driven multicast scheme for wireless networks in which the transmission rate and end-to-end delay are assumed to be bounded during a multiple multicast session. A distributed algorithm was used to identify a cost-efficient sub-graph between the source and destination which can satisfy QoS constraints of a multicast session. The model was then modified as to be applied for wireless networks in which satisfying interference constraints is the main challenge. A discrete power control scheme was also applied for the QoS-aware multicast model to accommodate the effect of transmission power level based on link capacity requirements. We also proposed random power allocation (RPA) and gradient power allocation (GPA) algorithms to efficient resource distribution each of which has different time complexity and optimality levels. Experimental results confirm that the proposed power allocation techniques decrease the number of unavailable links between intermediate nodes in the sub-graph and considerably increase the chance of finding an optimal solution.