• Proceedings of the Korea Information Processing Society Conference
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• 2011.04a
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• pp.216-219
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• 2011

이 기종의 컴퓨팅 자원들로 구성된 데이터센터에서 사용자가 제출한 클라우드 작업의 서비스 품질을 보장하기 위해서는 효율적인 작업할당 기법이 필요하다. 본 논문에서는 작업의 처리시간을 사용자의 QoS 로 정의하고 작업처리시간을 최소화하면서 동시에 모든 사용자에게 차별 없이 동일한 수준의 서비스를 제공할 수 있는 최적 작업할당 문제를 정의한다. 협력적 게임모형인 NBS(Nah Bargaining Solution)을 이용하여 정의한 문제를 해결하였고 이를 이용하여 각 자원에 할당되는 작업부하를 효율적으로 제어함으로써 파레토 최적을 유지할 수 있는 협력적 부하분산 정책을 도출하였다. 또한, 성능 평가를 통해 제안한 기법이 작업처리시간을 최소화하면서도 모든 자원에서의 작업처리시간이 동일함을 보였다.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.8 no.11
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• pp.3674-3710
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• 2014

In this tutorial, we integrate the concept of cognitive radio technology into game theory and supermarket game theory to address the problem of resource allocation in multiuser multicarrier cognitive radio networks. In addition, multiuser multicarrier transmission technique is chosen as a candidate to study the resource allocation problem via game and supermarket game theory. This tutorial also includes various definitions, scenarios and examples related to (i) game theory (including both non-cooperative and cooperative games), (ii) supermarket game theory (including pricing, auction theory and oligopoly markets), and (iii) resource allocation in multicarrier techniques. Thus, interested readers can better understand the main tools that allow them to model the resource allocation problem in multicarrier networks via game and supermarket game theory. In this tutorial article, we first review the most fundamental concepts and architectures of CRNs and subsequently introduce the concepts of game theory, supermarket game theory and common solution to game models such as the Nash equilibrium and the Nash bargaining solution. Finally, a list of related studies is highlighted and compared in this tutorial.

• Journal of Internet Computing and Services
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• v.15 no.3
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• pp.63-69
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• 2014

For the safety messages in IEEE 802.11p vehicles network environment(WAVE), strict periodic beacon broadcasting requires status advertisement to assist the driver for safety. WAVE standards apply multiple radios and multiple channels to provide open public road safety services and improve the comfort and efficiency of driving. Although WAVE standards have been proposed multi-channel multi-radio, the standards neither consider the WAVE multi-radio environment nor its effect on the beacon broadcasting. Most of beacon broadcasting is designed to be delivered on only one physical device and one control channel by the WAVE standard. also conflict-free channel assignment of the fewest channels to a given set of radio nodes without causing collision is NP-hard, even with the knowledge of the network topology and all nodes have the same transmission radio. Based on the latest standard IEEE 802.11p and IEEE 1609.4, this paper proposes an interference aware-based channel assignment algorithm with Nash bargaining solution that minimizes interference and increases throughput with wireless mesh network, which is deigned for multi-radio multi-cahnnel structure of WAVE. The proposed algorithm is validated against numerical simulation results and results show that our proposed algorithm is improvements on 8 channels with 3 radios compared to Tabu and random channel allocation algorithm.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.8
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• pp.3474-3497
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• 2016

Network Function Virtualization (NFV) and Software Defined Networking (SDN) are recently considered as very promising drivers of the evolution of existing middlebox services, which play intrinsic and fundamental roles in today's networks. To address the virtual service deployment issues that caused by introducing NFV or SDN to networks, this paper proposes an optimal solution by combining quantum genetic algorithm with cooperative game theory. Specifically, we first state the concrete content of the service deployment problem and describe the system framework based on the architecture of SDN. Second, for the service location placement sub-problem, an integer linear programming model is built, which aims at minimizing the network transport delay by selecting suitable service locations, and then a heuristic solution is designed based on the improved quantum genetic algorithm. Third, for the service amount placement sub-problem, we apply the rigorous cooperative game-theoretic approach to build the mathematical model, and implement a distributed algorithm corresponding to Nash bargaining solution. Finally, experimental results show that our proposed method can calculate automatically the optimized placement locations, which reduces 30% of the average traffic delay compared to that of the random placement scheme. Meanwhile, the service amount placement approach can achieve the performance that the average metric values of satisfaction degree and fairness index reach above 90%. And evaluation results demonstrate that our proposed mechanism has a comprehensive advantage for network application.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.6
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• pp.2811-2830
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• 2017

In this paper, we study the problem of mobile data offloading for a network that contains multiple mobile network operators (MNOs), multiple WiFi or femtocell access points (APs) and multiple mobile users (MUs). MNOs offload their subscribed MUs' data traffic by leasing the unused Internet connection bandwidth of third party APs. We propose a combinatorial auction-based two-stage matching mechanism comprised of MU-AP matching and AP-MNO matching. The MU-AP matching is designed to match the MUs to APs in order to maximize the total offloading data traffic and achieve better MU satisfaction. Conversely, for AP-MNO matching, MNOs compete for APs' service using the Nash bargaining solution (NBS) and the Vickrey auction theories and, in turn, APs will receive monetary compensation. We demonstrated that the proposed mechanism converges to a distributed stable matching result. Numerical results demonstrate that the proposed algorithm well capture the tradeoff among the total data traffic, social welfare and the QoS of MUs compared to other schemes. Moreover, the proposed mechanism can considerably offload the total data traffic and improve the network social welfare with less computation complexity and communication overhead.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2005.05a
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• pp.890-894
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• 2005

Coordination between supply chain partners is viewed critical to effective supply chain management. In many situations such as mutual investments or developing infrastructures for their operations related with each other, the coordination issue arises. Depending on the bargaining power balance between them, it is determined who will be able to exert more influence in making decisions related with such coordination. We consider two cases of the decision-making structure in the context of a simple supply chain consisting of two players, i.e., (1) the first case in which a supply chain partner dominates the decision-making process and the other passively follows the dominant player's decision, and (2) the other case in which the two players share the decision-making process equally. We examine which of the cases is better for the companies and where comes the value of the better case. To answer the research questions, we set up an optimal control theory model and derive an analytical solution. The analysis outcome indicates that the shared decision-making in general produces better results for both companies in the supply chain, and the value of the shared decision-making comes from more effective resource utilization than the dominated case.

• Industrial Engineering and Management Systems
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• v.14 no.3
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• pp.248-274
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• 2015

This study discusses a contract to promote collection and recycling of used products in a green supply chain (GSC). A collection incentive contract is combined with a reward-penalty contract. The collection incentive contract for used products is made between a retailer and a manufacturer. The reward-penalty contract for recycling used products is made between a manufacturer and an external institution. A retailer pays an incentive for collecting used products from customers and delivers them to a manufacturer with a product order quantity under uncertainty in product demand. A manufacturer remanufactures products using recyclable parts with acceptable quality levels and covers a part of the retailer's incentive from the recycled parts by sharing the reward from an external institution. Product demand information is assumed as (i) the distribution is known (ii) mean and variance are known. Besides, the optimal decisions for product quantity, collection incentive of used products and lower limit of quality level for recyclable parts under decentralized integrated GSCs. The analysis numerically investigates how (1) contract for recycling activity, (ii) product demand information and (iii) quality of recyclable parts affect the optimal operation for each GSC. Supply chain coordination to shift IGSC is discussed by adopting Nash Bargaining solution.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2004.10a
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• pp.535-538
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• 2004

Coordination between supply chain partners is viewed critical to effective supply chain management. Depending on the bargaining power balance between them, it is determined who will be able to exert more influence in making decisions related with such coordination. We consider two cases of the decision-making structure in the context of a simple supply chain consisting of two players, i.e., (1) the first case in which a supply chain partner dominates the decision-making process and the other passively follows the dominant player's decision, and (2) the other case in which the two players share the decision-making process equally. In this paper, we examine which of the cases is better for the companies and where comes the value of the better case. To answer the research questions, we set up an optimal control theory model and derive an analytical solution. The analysis outcome indicates that the shared decision-making in general produces better results for both companies in the supply chain, and the value of the shared decision-making comes from more effective resource utilization than the dominated case.

• Industrial Engineering and Management Systems
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• v.13 no.2
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• pp.129-147
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• 2014

This study proposes an optimal operational policy for a green supply chain (GSC) where a retailer pays an incentive for collection of used products from customers and determines the optimal order quantity of a single product under uncertainty in product demand. A manufacturer produces the optimal order quantity of product using recyclable parts with acceptable quality levels and covers a part of the retailer's incentive from the recycled parts. Here, two scenarios for the product demand are assumed as: the distribution of product demand is known, and only both mean and variance are known. This paper develops mathematical models to find how order quantity, collection incentive of used products and lower limit of quality level for recycling affect the expected profits of each member and the whole supply chain under both a decentralized GSC (DGSC) and an integrated GSC (IGSC). The analysis numerically compares the results under DGSC with those under IGSC for each scenario of product demand. Also, the effect of the quality of the recyclable parts on the optimal decisions is shown. Moreover, supply chain coordination to shift the optimal decisions of IGSC is discussed based on: I) profit ratio, II) Nash bargaining solution, and III) Combination of (I) and (II).

• The Journal of Society for e-Business Studies
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• v.19 no.1
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• pp.43-61
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• 2014

This research is an application of game theory to developing the supplier selection and demand allocation mechanism, which are the essential and major research areas of supply chain planning and operation. In this research, the most popular and widely accepted mechanism, the progressive reverse auction is analyzed and compared with the other game theoretic approach, Kalai-Smorodinsky Bargaining Solution in the viewpoint of holistic efficiency of supply chain operation. To logically and exquisitely compare the efficiencies, a heuristic algorithm based on Genetic Algorithm is devised to find the other optimal demand allocation plan. A well known metric, profit-cost ratio, as well as profit functions for both suppliers and buyer has been designed for evaluating the overall profitability of supply chain. The experimental results with synthesis data and supply chain model which were made to mimic practical supply chain are illustrated and analyzed to show how the proposed approach can enhance the profitability of supply chain planning. Based on the result, it can be said that the proposed mechanism using bargainging solution mayguarantee the better profitability for the whole supply chin including both suppliers and buyer, even though quite small portion of buyer's profitability should be sacrified.