Auction-Stackelberg game framework for access permission in femtocell networks with multiple network operators

With the explosive growth of indoor data traffic in forthcoming fifth generation cellular networks, it is imperative for mobile network operators to improve network coverage and capacity. Femtocells are widely recognized as a promising technology to address these demands. As femtocells are sold or loaned by a mobile network operator (MNO) to its residential or enterprise customers, MNOs usually employ refunding scheme to compensate the femtocell holders (FHs) providing indoor access to other subscribers by configuring the femtocell to operate in open or hybrid access mode. Due to the selfishness nature, competition between network operators as well as femtocell holders makes it challenging for operators to select appropriate FHs for trading access resources. This inspires us to develop an effective refunding framework, with aim to improve overall network resource utilization, through promoting FHs to make reasonable access permission for well-matched macro users. In this paper, we develop a two-stage auction–Stackelberg game (ASGF) framework for access permission in femtocell networks, where MNO and mobile virtual network operator lease access resources from multiple FHs. We first design an auction mechanism to determine the winner femtocell that fulfils the access request of macro users. We next formulate the access permission problem between the winner femtocell and operators as a Stackelberg game, and theoretically prove the existence of unique equilibrium. As a higher system payoff can be gained by improving individual players’ payoff in the game, each player can choose the best response to others’ action by implementing access permission, while avoiding solving a complicated optimization problem. Numerical results validate the effectiveness of our proposed ASGF based refunding framework and the overall network efficiency can be improved significantly

Stackelberg Game for Access Permission in Femtocell Network with Multiple Network Operators

Femtocells are widely recognized as a promising technology to meet the requirements of indoor coverage in forthcoming fifth generation cellular networks (5G). As femtocell holders (FHs) can be users themselves or mobile network operators, it makes challenges to holistic network resource utilization. In particular, due to the selfishness nature, FHs are usually unwilling to accommodate extra users without compensation. This inspires us to develop an effective refunding mechanism, with aim to allow competitive network operators to employ truthful refunding policy, and to encourage FHs to make appropriate access permission. In this paper, we first define a refunding strategy function and price-coefficient for the refunding policy. We then formulate the access permission as a Stackelberg game and theoretically prove the existence of unique Nash Equilibrium. Numerical results validate the effectiveness of our proposed mechanism and overall network efficiency is improved significantly as well

Game theory for collaboration in future networks

Cooperative strategies have the great potential of improving network performance and spectrum utilization in future networking environments. This new paradigm in terms of network management, however, requires a novel design and analysis framework targeting a highly flexible networking solution with a distributed architecture. Game Theory is very suitable for this task, since it is a comprehensive mathematical tool for modeling the highly complex interactions among distributed and intelligent decision makers. In this way, the more convenient management policies for the diverse players (e.g. content providers, cloud providers, home providers, brokers, network providers or users) should be found to optimize the performance of the overall network infrastructure. The authors discuss in this chapter several Game Theory models/concepts that are highly relevant for enabling collaboration among the diverse players, using different ways to incentivize it, namely through pricing or reputation. In addition, the authors highlight several related open problems, such as the lack of proper models for dynamic and incomplete information games in this area.info:eu-repo/semantics/acceptedVersio

Game theory for cooperation in multi-access edge computing

Cooperative strategies amongst network players can improve network performance and spectrum utilization in future networking environments. Game Theory is very suitable for these emerging scenarios, since it models high-complex interactions among distributed decision makers. It also finds the more convenient management policies for the diverse players (e.g., content providers, cloud providers, edge providers, brokers, network providers, or users). These management policies optimize the performance of the overall network infrastructure with a fair utilization of their resources. This chapter discusses relevant theoretical models that enable cooperation amongst the players in distinct ways through, namely, pricing or reputation. In addition, the authors highlight open problems, such as the lack of proper models for dynamic and incomplete information scenarios. These upcoming scenarios are associated to computing and storage at the network edge, as well as, the deployment of large-scale IoT systems. The chapter finalizes by discussing a business model for future networks.info:eu-repo/semantics/acceptedVersio

Applications of Game Theory and Microeconomics in Cognitive Radio and Femtocell Networks

Cognitive radio networks have recently been proposed as a promising approach to overcome the serious problem of spectrum scarcity. Other emerging concept for innovative spectrum utilization is femtocells. Femtocells are low-power and short-range wireless access points installed by the end-user in residential or enterprise environments. A common feature of cognitive radio and femtocells is their two-tier nature involving primary and secondary users (PUs, SUs). While this new paradigm enables innovative alternatives to conventional spectrum management and utilization, it also brings its own technical challenges. A main challenge in cognitive radio is the design of efficient resource (spectrum) trading methods. Game and microeconomics theories provide tools for studying the strategic interactions through rationality and economic benefits between PUs and SUs for effective resource allocation. In this thesis, we investigate some efficient game theoretic and microeconomic approaches to address spectrum trading in cognitive networks. We propose two auction frameworks for shared and exclusive use models. In the first auction mechanism, we consider the shared used model in cognitive radio networks and design a spectrum trading method to maximize the total satisfaction of the SUs and revenue of the Wireless Service Provider (WSP). In the second auction mechanism, we investigate spectrum trading via auction approach for exclusive usage spectrum access model in cognitive radio networks. We consider a realistic valuation function and propose an efficient concurrent Vickrey-Clarke-Grove (VCG) mechanism for non-identical channel allocation among r-minded bidders in two different cases. The realization of cognitive radio networks in practice requires the development of effective spectrum sensing methods. A fundamental question is how much time to allocate for sensing purposes. In the literature on cognitive radio, it is commonly assumed that fixed time durations are assigned for spectrum sensing and data transmission. It is however possible to improve the network performance by finding the best tradeoff between sensing time and throughput. In this thesis, we derive an expression for the total average throughput of the SUs over time-varying fading channels. Then we maximize the total average throughput in terms of sensing time and the number of SUs assigned to cooperatively sense each channel. For practical implementation, we propose a dynamical programming algorithm for joint optimization of sensing time and the number of cooperating SUs for sensing purpose. Simulation results demonstrate that significant improvement in the throughput of SUs is achieved in the case of joint optimization. In the last part of the thesis, we further address the challenge of pricing in oligopoly market for open access femtocell networks. We propose dynamic pricing schemes based on microeconomic and game theoretic approaches such as market equilibrium, Bertrand game, multiple-leader-multiple-follower Stackelberg game. Based on our approaches, the per unit price of spectrum can be determined dynamically and mobile service providers can gain more revenue than fixed pricing scheme. Our proposed methods also provide residential customers more incentives and satisfaction to participate in open access model.1 yea

Cloud/fog computing resource management and pricing for blockchain networks

The mining process in blockchain requires solving a proof-of-work puzzle, which is resource expensive to implement in mobile devices due to the high computing power and energy needed. In this paper, we, for the first time, consider edge computing as an enabler for mobile blockchain. In particular, we study edge computing resource management and pricing to support mobile blockchain applications in which the mining process of miners can be offloaded to an edge computing service provider. We formulate a two-stage Stackelberg game to jointly maximize the profit of the edge computing service provider and the individual utilities of the miners. In the first stage, the service provider sets the price of edge computing nodes. In the second stage, the miners decide on the service demand to purchase based on the observed prices. We apply the backward induction to analyze the sub-game perfect equilibrium in each stage for both uniform and discriminatory pricing schemes. For the uniform pricing where the same price is applied to all miners, the existence and uniqueness of Stackelberg equilibrium are validated by identifying the best response strategies of the miners. For the discriminatory pricing where the different prices are applied to different miners, the Stackelberg equilibrium is proved to exist and be unique by capitalizing on the Variational Inequality theory. Further, the real experimental results are employed to justify our proposed model.Comment: 16 pages, double-column version, accepted by IEEE Internet of Things Journa