• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.5
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• pp.1973-1991
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• 2018

Multimedia applications over wireless networks have been evolving to augmented reality or virtual reality services. However, a rich data size compared to conventional multimedia services causes bandwidth bottlenecks over wireless networks, which is one of the main reasons why those applications are not used widely. To overcome this limitation, bandwidth aggregation techniques, which exploit a multi-path transmission, have been considered to maximize link utilization. Currently, most of the conventional researches have been focusing on the user end problems to improve the quality of service (QoS) through optimal load distribution. In this paper, we address the joint pricing and load distribution problem for multi-homing in heterogeneous wireless access networks (ANs), considering the interests of both the users and the service providers. Specifically, we consider profit from resource allocation and cost of power consumption expenditure for operation as an utility of each service provider. Here, users decide how much to request the resource and how to split the resource over heterogeneous wireless ANs to minimize their cost while supporting the required QoS. Then, service providers compete with each other by setting the price to maximize their utilities over user reactions. We study the behaviors of users and service providers by analyzing their hierarchical decision-making process as a multileader-, multifollower Stackelberg game. We show that both the user and service provider strategies are closed form solutions. Finally, we discuss how the proposed scheme is well converged to equilibrium points.

• 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.

• Proceedings of the KIEE Conference
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• 2005.07a
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• pp.775-777
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• 2005

In this paper, effects of the subsidy in the electricity market on the market equilibrium are analyzed. The generation competition markets are considered as the basic market structure. The market equilibrium with Cournot game model is derived, first. Then, the variation of Nash equilibrium is investigated when the subsidies to generation companies are provided. The market equilibrium with the subsidy in the electricity market, which is equivalent to the subgame perfect equilibrium, is analytically derived using Stackelberg game model and backward induction method. From this, how the provisions of subsidy to generation companies can affect the strategic behaviors of the generation companies and corresponding market equilibrium are explored, in this paper. Numerical examples are provided to illustrate the basic idea of this paper.

• Journal of Satellite, Information and Communications
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• v.12 no.4
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• pp.100-105
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• 2017

In this paper, we study an interference avoidance scenario in the presence of a interferer which can rapidly observe the transmit power of backscatter communications and effectively interrupt backscatter signals. We consider a power control with a sub-channel allocation to avoid interference attacks and a power-splitting ratio for backscattering and RF energy harvesting in sensors. We formulate the problem based on a Stackelberg game theory and compute the optimal transmit power, power-splitting ratio, and sub-channel allocation parameter to maximize a utility function against the interferer. We propose the utility maximization using Lagrangian dual decomposition for the backscatter communications and the interferer to prove the existence of the Stackelberg equilibrium. Numerical results show that the proposed algorithms effectively maximize the utility, compared to that of the algorithm based on the Nash game, so as to overcome a malicious interference in backscatter communications.

• Journal of KIISE:Information Networking
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• v.37 no.2
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• pp.94-98
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• 2010

In this paper, we formalize a new adaptive online price control scheme based on the Stackelberg game model. By using the hierarchical interaction strategy, control decisions in each mechanism act cooperatively and collaborate with each other to satisfy conflicting performance criteria. In addition, our dynamic online approach is practical for real network implementation. With a simulation study, the proposed scheme can adaptively adjust the network price to approximate an optimized solution under widely diverse network situations.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.9 no.11
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• pp.4291-4310
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• 2015

This paper investigates the traffic offloading over unlicensed bands for two-tier multi-mode small cell networks. We formulate this problem as a Stackelberg game and apply a hierarchical learning framework to jointly maximize the utilities of both macro base station (MBS) and small base stations (SBSs). During the learning process, the MBS behaves as a leader and the SBSs are followers. A pricing mechanism is adopt by MBS and the price information is broadcasted to all SBSs by MBS firstly, then each SBS competes with other SBSs and takes its best response strategies to appropriately allocate the traffic load in licensed and unlicensed band in the sequel, taking the traffic flow payment charged by MBS into consideration. Then, we present a hierarchical Q-learning algorithm (HQL) to discover the Stackelberg equilibrium. Additionally, if some extra information can be obtained via feedback, we propose an improved hierarchical Q-learning algorithm (IHQL) to speed up the SBSs' learning process. Last but not the least, the convergence performance of the proposed two algorithms is analyzed. Numerical experiments are presented to validate the proposed schemes and show the effectiveness.

• 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.

• Journal of KIISE
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• v.44 no.8
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• pp.854-859
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• 2017

Caching popular videos in the storage of base stations is an efficient method to reduce the transmission latency. This paper proposes an incentive proactive cache mechanism in the wireless network to motivate the content providers (CPs) to participate in the caching procedure. The system consists of one/many Infrastructure Provider (InP) and many CPs. The InP aims to define the price it charges the CPs to maximize its revenue while the CPs compete to determine the number of files they cache at the InP's base stations (BSs). We conceive this system within the framework of Stackelberg game where InP is considered as the leader and CPs are the followers. By using backward induction, we show closed form of the amount of cache space that each CP renting on each base station and then solve the optimization problem to calculate the price that InP leases each CP. This is different from the existing works in that we consider the non-uniform pricing scheme. The numerical results show that InP's profit in the proposed scheme is higher than in the uniform pricing.

• Korean Management Science Review
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• v.23 no.3
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• pp.243-257
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• 2006

ITU-T's NgN(Next generation Network) architecture is expected to offer a new Internet platforms such as QoS(Quality of Service) guaranteed services as it overcame the limitations of the existing best-effort Internet architecture. However, policy development crucial for the NgN framework(e.g., interconnections and billing) is lagging far behind technology development. For example, arguments over network neutrality clearly indicate little understanding of the Internet industry structure where diverse providers including ISP and CP coexist. This study employs a network economics approach to predict how the competitive landscape involving various providers will evolve under the traffic-based billing system under the NgN environment. Applied is the non-cooperative game theory, in particular, Stackelberg's repeated game in order to build and analyze model for competition among those providers. We also studied possible impacts that CPs would have on the competitive landscape if they have an option to replace ISP: i.e., CDN(Content Delivery Network) provider. Lastly, based on the model analysis and experiments, presented are their implications to policy development and tile future prospect.

• KIPS Transactions on Computer and Communication Systems
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• v.8 no.7
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• pp.167-176
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• 2019

Recently, as the types of services that can be enjoyed in mobile telecommunication networks such as social networks and video streaming are increasing, mobile users(MUs) can access mobile contents easily by consuming mobile data. However, under a mobile telecommunication environment, MUs have to pay a high data fee to a network service provider(SP) in order to enjoy contents. The 'data sponsor' technique, introduced as a way to solve this problem, has attracted attention as a breakthrough method for enhancing contents accessibility of MUs. In this paper, we propose an algorithm that determines the optimal discount rate through the Stackelberg game in the data sponsor environment. We also propose an algorithm to design edge caching, which caches highly popular content for MUs on edge server, through many-to-many matching game. Simulation results clearly indicate that the profit for CP's content consumption is improved by about 6~11%, and the profit of CP according to the ratio of edge caching is improved by about 12% than the other existing schemes under data sponsor environment.