• ETRI Journal
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• v.33 no.6
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• pp.957-960
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• 2011

We present a fair and efficient solution for selfish readers with the Nash bargaining solution (NBS) to mitigate the effects of RFID frequency interference. We compare the NBS with a solution derived by the max log-sum scheme that maximizes total utility and show that for selfish and rational readers, the NBS brings success in bargaining on resource allocation between readers unlike the max log-sum scheme, although the NBS has less total payoff compared to the max log-sum scheme.

• KIPS Transactions on Computer and Communication Systems
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• v.10 no.8
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• pp.215-222
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• 2021

In order to alleviate the limited resource problem and interference problem in cellular networks, the dual connectivity technology has been introduced with the cooperation of small cell base stations. In this paper, we design a new efficient and fair resource allocation scheme for the dual connectivity technology. Based on two different bargaining solutions - Generalizing Tempered Aspiration bargaining solution and Gupta and Livne bargaining solution, we develop a two-stage radio resource allocation method. At the first stage, radio resource is divided into two groups, such as real-time and non-real-time data services, by using the Generalizing Tempered Aspiration bargaining solution. At the second stage, the minimum request processing speeds for users in both groups are guaranteed by using the Gupta and Livne bargaining solution. These two-step approach can allocate the 5G radio resource sequentially while maximizing the network system performance. Finally, the performance evaluation confirms that the proposed scheme can get a better performance than other existing protocols in terms of overall system throughput, fairness, and communication failure rate according to an increase in service requests.

• KIPS Transactions on Computer and Communication Systems
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• v.10 no.4
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• pp.93-100
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• 2021

The Ethereum shard system for solving the scalability problem of the blockchain has a load balancing issue, which is modeled as a graph partitioning problem. In this paper, we propose an adaptive online weighted graph partitioning algorithm that can negotiate between two utility of the shard system using the game theory's bargaining solution. The bargaining solution is an axiomatic solution that can fairly determine the points of conflict of utility. The proposed algorithm was improved to apply the existing online graph partitioning algorithm to the weighted graph, and load balancing was performed efficiently through the design considering the situation of the sharding system using the extension of Nash bargaining solution, which is extended to apply solution to non-convex feasible set of bargaining problem. As a result of the experiment, it showed up to 37% better performance than typical load balancing algorithm of shard system.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.37 no.4
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• pp.145-153
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• 2014

In this paper, we study the bargaining strategy of a manufacturer who sells a product through the online and offline distribution channels. To do this, we derive and analyze the equilibrium solutions for both simultaneous and sequential bargaining games. The result shows that the optimal bargaining strategy heavily depends on the size of the online distribution channel's loyal customers and the difference between the retail prices of the online and the offline distribution channels. It is also shown that, in some cases, the online distribution channel has incentive to downsize its loyal customers and its retail price for a better bargaining outcome.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.38 no.2
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• pp.31-39
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• 2015

In this paper, we study the bargaining strategy of a distributor who sells vertically differentiated, i.e. high and low brand products. We derive and analyze the equilibrium solutions for both simultaneous and sequential bargaining games among the distributor, the high brand product manufacturer and the low brand product manufacturer. The result shows that the optimal bargaining strategy for the distributor heavily depends on the relative quality and price level of the low brand product comparing to those of the high brand product. It is also shown that, for more bargaining profit, the distributor has strong motivation to prefer a low brand product which has lower quality level per unit price.

• Journal of Korean Society of Transportation
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• v.23 no.4 s.82
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• pp.37-45
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• 2005

This paper presents a relationship between Nash bargaining game and Wardrop user equilibrium, which has been widely used in transportation modeling for route choice problem. Wardrop user equilibrium assumes that drivers in road network have perfect information on the traffic conditions and they choose their optimal paths without cooperation each other. In this regards, if the bargaining game process is introduced in route choice modeling, we may avoid the strong assumptions to some extent. For such purpose, this paper derives a theorem that Nash bargaining solution is equivalent to Wardrop user equilibrium as the barging process continues and prove it with some numerical examples. The model is formulated based on two-person bargaining game. and n-person game is remained for next work.

• ETRI Journal
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• v.33 no.3
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• pp.407-414
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• 2011

In an effort to reduce energy consumption, research into adaptive power management in real-time systems has become widespread. In this paper, a novel dynamic voltage scaling scheme is proposed for multiprocessor systems. Based on the concept of the Nash bargaining solution, a processor's clock speed and supply voltage are dynamically adjusted to satisfy these conflicting performance metrics. In addition, the proposed algorithm is implemented to react adaptively to the current system conditions by using an adaptive online approach. Simulation results clearly indicate that the superior performance of the proposed scheme can strike the appropriate performance balance between contradictory requirements.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.51 no.7
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• pp.311-316
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• 2002

It has been a basic model for the present electric power industry that more than two generators compete, and thereby the market clearing price and the generation schedules are determined through the bid process. In order for this paradigm to be applicable to real electric power systems and markets, it is necessary to reflect many physical and economic constraints related to frequency and transmission in the dispatching schedule. The paper presents an approach to deriving a Nash bargaining solution in a competitive electricity market where multiple generators are playing with the system operator who mitigates the transmission congestion to minimize the total transaction cost. In this study, we take the effect of the line flows and the role of system operator into the Game. Finally, a case study has been demonstrated to verify the proposed cooperative game.

• Journal of KIISE:Information Networking
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• v.37 no.6
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• pp.415-419
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• 2010

Bandwidth is an extremely valuable and scarce resource in a wireless network. Therefore, efficient bandwidth management is necessary in order to provide high quality service to users with different requirements. In this paper, we propose a bandwidth reservation algorithm based on Nash Bargaining Solution. The proposed algorithm has low complexity and are quite flexible in the different situations of network. Simulation results indicate that the proposed scheme has excellent performance than other existing schemes.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.65 no.3
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• pp.463-468
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• 2016

The overall performance of multiuser systems significantly depends on how effectively and fairly manage resources shared by them. The efficient resource management strategies are even more important for multimedia users since multimedia data is delay-sensitive and massive. In this paper, we focus on resource allocation based on a game-theoretic approach, referred to as Nash bargaining solution (NBS), to provide a quality of service (QoS) guarantee for each user. While the NBS has been known as a fair and optimal resource management strategy, it is challenging to find the NBS efficiently due to the computationally-intensive task. In order to reduce the computation requirements for NBS, we propose an approach that requires significantly low complexity even when networks consist of a large number of users and a large amount of resources. The proposed approach linearizes utility functions of each user and formulates the problem of finding NBS as a convex optimization, leading to nearly-optimal solution with significantly reduced computation complexity. Simulation results confirm the effectiveness of the proposed approach.