• Journal of KIISE:Software and Applications
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• v.27 no.3
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• pp.257-265
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• 2000

There is much selective confliction in nature where selfish and rational individuals exists. Iterated Prisoner's Dilemma (IPD) game deals with this problem, and has been used to study on the evolution of cooperation in social, economic and biological systems. So far, there has been much work about the relationship of the number of players and cooperation, strategy learning as a machine learning and the effect of payoff functions to cooperation. In this paper, We attempt to investigate the cooperative coalition size according to payoff functions, and observe the relationship of localization and the evolution of cooperation in NIPD (N-player IPD) game. Experimental results indicate that cooperative coalition size increases as the gradient of the payoff function for cooperation becomes steeper than that of defector's payoff function, or as the minimum coalition size gets smaller, Moreover, the smaller the neighborhood of interaction is, the higher the cooperative coalition emerges through the evolution of population.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.11
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• pp.5253-5270
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• 2016

With device-to-device (D2D) communications, an inactive user terminal can be utilized as a relay node to support multi-hop communication so that connective experience of the cell-edge user as well as the capacity of the whole system can be significantly improved. In this paper, we investigate the spectrum sharing for a cooperative relay assisted D2D communication underlying a cellular network. We formulate a joint relay selection and channel assignment problem to maximize the throughput of the system while guaranteeing the quality of service (QoS) requirements of cellular users (CUs) and D2D users (DUs). By exploiting coalition formation game theory, we propose two algorithms to solve the problem. The first algorithm is designed based on merge and split rules while the second one is developed based on single user's movement. Both of them are proved to be stable and convergent. Simulation results are presented to show the effectiveness of the proposed algorithms.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.5
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• pp.2286-2309
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• 2016

Overlay networks have been widely deployed upon the Internet by Service Providers (SPs) to provide improved network services. However, the interaction between each overlay and traffic engineering (TE) as well as the interaction among co-existing overlays may occur. In this paper, we adopt both non-cooperative and cooperative game theory to analyze these interactions, which are collectively called hybrid interaction. Firstly, we model a situation of the hybrid interaction as an n+1-player non-cooperative game, in which overlays and TE are of equal status, and prove the existence of Nash equilibrium (NE) for this game. Secondly, we model another situation of the hybrid interaction as a 1-leader-n-follower Stackelberg-Nash game, in which TE is the leader and co-existing overlays are followers, and prove that the cost at Stackelberg-Nash equilibrium (SNE) is at least as good as that at NE for TE. Thirdly, we propose a cooperative coalition mechanism based on Shapley value to overcome the inherent inefficiency of NE and SNE, in which players can improve their performance and form stable coalitions. Finally, we apply distinct genetic algorithms (GA) to calculate the values for NE, SNE and the assigned cost for each player in each coalition, respectively. Analytical results are confirmed by the simulation on complex network topologies.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.9 no.10
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• pp.3810-3830
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• 2015

In this paper, we investigate the differential game theoretic approach for distributed dynamic cooperative power control in cognitive radio ad hoc networks (CRANETs). First, a payoff function is defined by taking into consideration the tradeoff between the stock of accumulated power interference to the primary networks and the dynamic regulation of the transmit power of secondary users (SUs). Specifically, the payoff function not only reflects the tradeoff between the requirement for quickly finding the stable available spectrum opportunities and the need for better channel conditions, but also reveals the impact of the differentiated types of data traffic on the demand of transmission quality. Then the dynamic power control problem is modeled as a differential game model. Moreover, we convert the differential game model into a dynamic programming problem to obtain a set of optimal strategies of SUs under the condition of the grand coalition. A distributed dynamic cooperative power control algorithm is developed to dynamically adjust the transmit power of SUs under grand coalition. Finally, numerical results are presented to demonstrate the effectiveness of the proposed algorithm for efficient power control in CRANETs.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1998.06a
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• pp.669-673
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• 1998

This paper makes a study of the Shapley value in cooperative fuzzy games, games with fuzzy coalitions, which enable the representation of players' participation degree to each coalition. The Shapley value has so far been introduced only in an class of fuzzy games where a coalition value is not monotone with respect to each player's participation degree. We consider a more natural class of fuzzy games such that a coalition value is monotone with regard to each player's participation degree. The properties of fuzzy games in this class are investigated. Four axioms of Shapley functions are described and a Shapley function of a fuzzy fame in the class is given.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.8 no.12
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• pp.107-118
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• 1985

This paper is considerd a coalition formation problem with several game theoretical hypothesis and analyzed its usefulness in elect ion games.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.10
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• pp.4661-4680
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• 2016

Cognitive radio (CR) technology is an effective solution to the spectrum scarcity issue. Collaborative spectrum sensing is known as a promising technique to improve the performance of spectrum sensing in cognitive radio networks (CRNs). However, collaborative spectrum sensing is vulnerable to spectrum data falsification (SSDF) attack, where malicious users (MUs) may send false sensing data to mislead other secondary users (SUs) to make an incorrect decision about primary user (PUs) activity, which is one of the key adversaries to the performance of CRNs. In this paper, we propose a coalition based malicious users detection (CMD) algorithm to detect the malicious user in CRNs. The proposed CMD algorithm can efficiently detect MUs base on the Geary'C theory and be modeled as a coalition formation game. Specifically, SSDF attack is one of the key issues to affect the resource allocation process. Focusing on the security issues, in this paper, we analyze the power allocation problem with MUs, and propose MUs detection based power allocation (MPA) algorithm. The MPA algorithm is divided into two steps: the MUs detection step and the optimal power allocation step. Firstly, in the MUs detection step, by the CMD algorithm we can obtain the MUs detection probability and the energy consumption of MUs detection. Secondly, in the optimal power allocation step, we use the Lagrange dual decomposition method to obtain the optimal transmission power of each SU and achieve the maximum utility of the whole CRN. Numerical simulation results show that the proposed CMD and MPA scheme can achieve a considerable performance improvement in MUs detection and power allocation.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.42 no.3
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• pp.15-24
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• 2019

Fair Allocation of profits or costs arising from joint participation by multiple individuals or entities with different purposes is essential for their continuing involvement and for their dissatisfaction reduction. In this research, fair allocation of the profits of forming a grand coalition in Three-Echelon Supply Chain (TESC) game that is composed of manufacturer, distributor and retailer, is studied. In particular, the solutions of the proportional method of profit, the proportional method of marginal profit, and Shapley value based on cooperative game theory are proved to be in the desirable characteristics of the core. The proportional method of profit and the proportional method of marginal profit are often used because of their ease of application. These methods distribute total profit in proportion to profits or marginal profits of each game participant. In addition, Shapley value can be defined as the average marginal profit when one game player is added at a time. Even though the calculation of the average of all possible marginal profits is not simple, Shapley value are often used as a useful method. Experiments have shown that the solution of the incremental method, which calculates the marginal cost of adding game players in the order of manufacturers, distributors and retailers, does not exist in the core.

• Journal of Electrical Engineering and Technology
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• v.12 no.6
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• pp.2157-2165
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• 2017

This study deals with the design of the mechanism in which demand response (DR) resources are traded in the power generation market. In general, a DR aggregator (DRA), which extends DR resources and provides technical support, is central to this mechanism. In this study, power users, called DR customer (DRC), participate in load reduction and are also modeled to participate directly in DR-related bidding. The DRA provides incentives to the DRC, indirectly impacting the market, and the DRC use the bid parameters strategically. We present the conditions for finding Nash Equilibrium (NE) in game problems of various participants including market operators, and analyze the characteristics of DRA and DRC related models. It also analyzes the impact of the participants on the market according to various types of competition and coalitions between DRA and DRC.

• Journal of Satellite, Information and Communications
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• v.10 no.1
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• pp.49-55
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• 2015

In cognitive radio network (CRN), spectrum sensing is an elementary level of technology for non-interfering to licensed user. Required sample number for spectrum sensing is directly related to the throughput of secondary user and makes the tradeoff between the throughput of secondary user and interference to primary user. Required spectrum sensing sample is derived from required false alarm, detection probability and minimum required SNR of primary user (PU). If we make clustering and minimize the required transmission boundary of secondary user (SU), we can relax the required PU SNR for spectrum sensing because the required SNR for PU signal sensing is related to transmission range of SU. Therefore we can achieve efficient throughput of CRN by minimizing spectrum sensing sample. For this, we design the tradeoff between gain and loss could be obtained from clustering, according to the size of cluster members through game theory and simulation results confirm the effectiveness of the proposed method.