• Journal of Communications and Networks
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• v.16 no.6
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• pp.627-638
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• 2014

In this paper, we study the joint price and power allocation in spectrum sharing macro-femtocell networks. The proposed game theoretic framework is based on bi-level Stackelberg game where macro base station (MBS) works as a leader and underlaid femto base stations (FBSs) work as followers. MBS has fixed data rate and imposes interference price on FBSs for maintaining its data rate and earns revenue while FBSs jointly adjust their power for maximizing their data rates and utility functions. Since the interference from FBSs to macro user equipment is kept under a given threshold and FBSs compete against each other for power allocation, there is a need to determine a power allocation strategy which converges to Stackelberg equilibrium. We consider two cases for MBS power allocation, i.e., fixed and dynamic power. MBS can adjust its power in case of dynamic power allocation according to its minimum data rate requirement and number of FBSs willing to share the spectrum. For both cases we consider uniform and non-uniform pricing where MBS charges same price to all FBSs for uniform pricing and different price to each FBS for non-uniform pricing according to its induced interference. We obtain unique closed form solution for each case if the co-interference at FBSs is assumed fixed. And an iterative algorithm which converges rapidly is also proposed to take into account the effect of co-tier interference on interference price and power allocation strategy. The results are explained with numerical simulation examples which validate the effectiveness of our proposed solutions.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 1996.10a
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• pp.103-112
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• 1996

Optimal pricing research in general has been focused on profit maximizing strategy under the given product life-time T. Here we have tried to study the effect of uncertain product life-time on dynamic optimal pricing strategy. In reality, the life-time of product is more likely to be uncertain and not known as well. In terms of approximating the model to the concerned reality, so-called model validity, it seems to be more desirable to consider the uncertainty of product life-time into the optimal pricing strategy model, For this purpose, we tried two different approaches. One is to consider diverse product life-time probability functions under fixed life-time T. In this case, we might have the same product life-time as the previous study, but the process could be different in the expectation of product's discontinuity. The other is that life-time itself is not determined and thus it is the situation in which we can only decide optimal price on incremental basis. The former is the situation in which although we got some strong guess on life-time of a certain product, the pattern of expected life-time probability could be different. The question is what could be optimal pricing strategies on such different product life-time situations. But since in the latter, we don't assume any idea on the life-time of product. proper optimal pricing could be derived only from the past prices and diffusion information. While the latter seems to be safer in the aspect of model assumption, the former could be more realistic because we might have more or less a prior knowledge on the product life-time itself.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.8 no.7
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• pp.2231-2245
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• 2014

Cognitive Radio (CR) has very promising potential to improve spectrum utilization by allowing unlicensed Secondary Users (SUs) to access the spectrum dynamically without disturbing licensed Primary Users (PUs). Mitigating interference is a fundamental problem in CR scenarios. This is particularly problematic for deploying CR in cellular networks, when users are located at the cell edge, as the inter-cell interference mitigation and frequency reuse are critical requirements for both PUs and SUs. Further cellular networks require higher cell edge performance, then SUs will meet more challenges than PUs. To solve the performance decrease for SUs at the cell edge, a novel Dynamic Spectrum Allocation (DSA) scheme based on Game Theory is proposed in this paper. Full frequency reuse can be realized as well as inter-cell interference mitigated according to SUs' sensing, measurement and interaction in this scheme. A joint power/channel allocation algorithm is proposed to improve both cell-edge user experience and network performance through distributed pricing calculation and exchange based on game theory. Analytical proof is presented and simulation results show that the proposed scheme achieves high efficiency of spectrum usage and improvement of cell edge SUs' performance.

• Architectural research
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• v.17 no.3
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• pp.109-115
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• 2015

The dynamic pricing of electricity, where the electricity rate increases in a time zone with a high demand for electricity is typically applied to a building whose power reception capacity is greater than a certain size. This includes the time of use(TOU) electricity pricing in Korea which can induce the effect of reducing the power demand of a building. Meanwhile, a VRF (Variable Refrigerant Flow) system that uses electricity is regarded as one of the typical heating and cooling systems along with central air conditioning (central HVAC) for its easy operation and application to the building. Thus, to reduce power energy and operating costs of a building in which the TOU and VRF systems are applied simultaneously, we suggested a control for changing the indoor temperature setting within the thermal comfort range or limiting the rotational speed of an inverter compressor. In this study, to describe the features of the above-mentioned control and verify its effects, we evaluated the results obtained from the analysis of its operation data. Through the actual measurements in winter operations for 73 days since mid- December 2014, we confirmed a reduction of 10.9% in power energy consumption and 12.2% in operating costs by the new control. Also, a reduction of 13.3% in power energy consumption was identified through a regression analysis.

• Journal of the Korean Society for Railway
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• v.10 no.2 s.39
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• pp.137-145
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• 2007

In traditional financial theory, the discount cash flow model(DCF or NPV) operates as the basic framework for most analyses. In doing valuation analysis, the conventional view is that the net present value(NPV) of a project is the measure of the present value of expected net cash flows. Thus, investing in a positive(negative) NPV project will increase(decrease) firm value. Recently, this framework has come under some fire for failing to consider the options of the managerial flexibilities. Real option valuation(ROV) considers the managerial flexibility to make ongoing decisions regarding the implementation of investment projects and the deployment of real assets. The appeal of the framework is natural given the high degree of uncertainty that firms face in their technology investment decisions. This paper suggests an algorithm for estimating volatility of logarithmic cash flow returns of real assets based on the Black-Sholes option pricing model, the binomial option pricing model, and the Monte Carlo simulation. This paper uses those models to obtain point estimates of real option value with the G7- HSR350X(high-speed train).

• Journal of Communications and Networks
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• v.18 no.3
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• pp.513-522
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• 2016

We propose a mechanism for monitoring load in quality of service (QoS)-enabled wireless networks and show how it can be used for network management as well as for dynamic pricing. Mobile network traffic, especially video, has grown exponentially over the last few years and it is anticipated that this trend will continue into the future. Driving factors include the availability of new affordable, smart devices, such as smart-phones and tablets, together with the expectation of high quality user experience for video as one would obtain at home. Although new technologies such as long term evolution (LTE) are expected to help satisfy this demand, the fact is that several other mechanisms will be needed to manage overload and congestion in the network. Therefore, the efficient management of the expected huge data traffic demands is critical if operators are to maintain acceptable service quality while making a profit. In the current work, we address this issue by first investigating how the network load can be accurately monitored and then we show how this load metric can then be used to provide creative pricing plans. In addition, we describe its applications to features like traffic offloading and user satisfaction tracking.

• Proceedings of the KIEE Conference
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• 2007.07a
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• pp.830-831
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• 2007

부하의 가격에 대한 높은 반응성(price-responsiveness)과 이를 이끌어 낼 수 있는 적절한 수요관리(demand response) 정책은 구조 개편된 전력 시장에서 가격 변동성 및 설비에 대한 투자 부족 문제를 효과적으로 해결하는 데 필수적이라는 데에는 많은 연구자들이 동의하고 있다. 그럼에도 불구하고, 특히 전력 사용을 미리 계획하지 않는 소규모 소비자들의 경우, 전력 소비가 본질적으로 매우 탄력적이지 못하므로(inelastic) 가격에 민감한 부하를 이끌어 내기 위한 수요관리 정책은 신중하게 세워져야 한다. 본 논문은 최종 소비자에게 전력을 제공하면서 critical peak pricing(CPP)를 동적으로 관리하고 이러한 수요관리에 대한 인센티브를 가진 개체를 도입함으로써 가격에 민감한 부하를 이끌어 내는 수요 반응의 접근법을 제시할 것이다. 가격에 민감한 부하 및 수요 반응 정책의 문제는 정책적, 경제적, 기술적 측면에서 검토되어야 하는 바이나, 본 논문에서는 기술적 측면 및 경제적인 인센티브의 수식화에 초점을 맞추었다. 정책에 인센티브를 가진 개체의 이윤 방정식을 세움으로써 문제를 정식화하였으며, 문제의 최적 해를 구하기 위해 예측 가격을 바탕으로 backward dynamic programming을 통한 swing option 평가 기법을 사용하여 최적의 수요관리 시점을 구해야 함을 제안하는 바이다.

• The Journal of Society for e-Business Studies
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• v.14 no.4
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• pp.133-148
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• 2009

This study has tried to suggest a new model that can effectively redistribute the tickets in the online ticket resale market, while suggesting a new allocation mechanism based on an agent negotiation. To this end, this study has analyzed an auction in the online ticket resale market through Game theory. As a result of new agent mechanism, it has been proved that the price stability of ticket resale market leads to an increase. An agent negotiation helps to stabilize the ticket prices that are usually inclined to rise at auction, benefiting all the participants in the negotiations, consequently showing a Pareto solution. Especially, a framework for a negotiation process is suggested and domain and processes ontology are designed interrelatedly. With this modeling, a possibility of Ontology based agent negotiation is suggested.

• Korean System Dynamics Review
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• v.6 no.1
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• pp.99-123
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• 2005

Although the generation market is competitive, the power market is easily exercised the market power by one generator due to its special futures such as a limited supplier, large investment cost, transmission constraints and loss. Specially, as Korea Electric industry restructuring is similar US competitive wholesale electricity market structure which discovered the several evidences of market power abuse, when restructuring is completed the possibility that market power will be exercised is big. Market power interferes with market competitions and efficiency of system. The goal of this study is to investigate the market price effects of the potential market power and the proposed market power mitigation strategy in Korean market using the forecasting wholesale electricity market model. This modeling is developed based on the system dynamics approach. it can analyze the dynamic behaviors of wholesale prices in Korean market. And then it is expanded to include the effect of market condition changed by 'strategic behavior' and 'real time pricing.' This model can generate the overall insights regarding the dynamic impact of output withholding by old gas fire power plant bon as a marginal plant in Korean market at the macro level. Also it will give the energy planner the opportunity to create different scenarios for the future for deregulated wholesales market in Korea.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2006.11a
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• pp.142-146
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• 2006

This paper considers a SCM issue concerned with an integrated problem of inventory control and dynamic pricing strategies when demands are price and time dependent. The associated price markdowns are conducted for inventory control in a two-layer market consisting of retailer and outlet as in fashion apparel market. The objective function consists of revenue terms (sales revenue and salvage value) and purchasing cost term. Specifically, decisions on price markdowns and order quantity are made to maximize total profit in the supply chain so as to have zero inventory level at the end of the sales horizon. To solve the proposed problem, a gradient method is applied, which shows an optimal decision on both the initial inventory level and the discount pricing policy. Sensitivity analysis is conducted on the demand parameters and the final comments on the practical use of the proposed model are presented.