• KSII Transactions on Internet and Information Systems (TIIS)
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• v.9 no.6
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• pp.1996-2013
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• 2015

This paper considers a scenario that more D2D users exist in the cell, they compete for cellular resources to increase their own data rates, which may cause transmission interference to cellular users (CU) and the unfairness of resource allocation. We design a resource allocation scheme for selfish D2D users assisted by cooperative relay technique which is used to further enhance the users' transmission rates, meanwhile guarantee the QoS requirement of the CUs. Two transmission modes are considered for D2D users: direct transmission mode and cooperative relay transmission mode, both of which reuses the cellular uplink frequency resources. To ensure the fairness of resource distribution, Nash bargaining theory is used to determine the transmission mode and solve the bandwidth allocation problem for D2D users choosing cooperative relay transmission mode, and coalition formation game theory is used to solve the uplink frequency sharing problem between D2D users and CUs through a new defined "Selfish order". Through theoretical analysis, we obtain the closed Nash bargaining solution under CUs' rate constraints, and prove the stability of the formatted coalition. Simulation results show that the proposed resource allocation approach achieves better performance on resource allocation fairness, with only little sacrifice on the system sum rates.

• Journal of Communications and Networks
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• v.17 no.4
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• pp.440-448
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• 2015

In this paper, we study the problem of selfish behavior of secondary users (SUs) based on cognitive radio (CR) with the presence of primary users (PUs). SUs are assumed to contend on a channel using the carrier sense multiple access with collision avoidance (CSMA/CA) and PUs do not consider transmission of SUs, where CSMA/CA protocols rely on the random deference of packets. SUs are vulnerable to selfish attacks by which selfish users could pick short random deference to obtain a larger share of the available bandwidth at the expense of other SUs. In this paper, game theory is used to study the systematic cheating of SUs in the presence of PUs in multichannel CR networks. We study two cases: A single cheater and multiple cheaters acting without any restraint. We identify the Pareto-optimal point of operation of a network with multiple cheaters and also derive the Nash equilibrium of the network. We use cooperative game theory to drive the Pareto optimality of selfish SUs without interfering with the activity of PUs. We show the influence of the activity of PUs in the equilibrium of the whole network.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.5 no.3
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• pp.542-559
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• 2011

Most game-theoretic works of Aloha have emphasized investigating Nash equilibria according to the system state represented by the number of network users and their decisions. In contrast, we focus on the possible change of nodes' utility state represented by delay constraint and decreasing utility over time. These foregone changes of nodes' state are more likely to instigate selfish behaviors in networking environments. For such environment, in this paper, we propose a repeated Bayesian slotted Aloha game model to analyze the selfish behavior of impatient users. We prove the existence of Nash equilibrium mathematically and empirically. The proposed model enables any type of transmission probability sequence to achieve Nash equilibrium without degrading its optimal throughput. Those Nash equilibria can be used as a solution concept to thwart the selfish behaviors of nodes and ensure the system stability.

• Journal of information and communication convergence engineering
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• v.7 no.2
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• pp.148-151
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• 2009

We consider the problem of optimizing the performance of a system with resources shared by non-cooperative users. The worst-cast ratio between the cost of a Nash equilibrium and the optimal cost, called Price of Anarchy, is investigated. It measures the performance degradation due to the users' selfish behavior. As the objective function of the optimization problem, we are concerned in a load balancing measure, which is different from that used in the previous works. Also we consider the Stackelberg scheduling which can assign a fraction of the users to resources while the remaining users are free to act in a selfish manner.

• Journal of KIISE:Computer Systems and Theory
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• v.35 no.9_10
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• pp.417-420
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• 2008

We consider the problem of optimizing the performance of a system shared by selfish non-cooperative users. In this problem, small jobs which the users request should be scheduled on a set of shared machines with their speed functions, each of which dependson the amount of jobs allocated on a machine. The performance of the system is measured by the maximum of the completion times when the machines complete the jobs allocated on them. The selfish users can choose a machine on which their jobs are executed, and they choose the fastest machine. But it typically results in suboptimal system performance. The Price of Anarchy(PoA) was introduced as a measure of the performance degradation due to the user's selfish behavior. The PoA is the worst-case ratio of the cost of a Nash equilibrium to the optimal cost. In this paper, we estimate the PoA for the above scheduling problem.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.8 no.2
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• pp.355-370
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• 2014

Cooperative spectrum sensing has been considered as a promising approach to improve the sensing performance in distributed cognitive radio networks. However, there may exist some selfish secondary users (SUs) who are unwilling to cooperate. The presence of selfish SUs could cause catastrophic damage to the performance of cooperative spectrum sensing. Following the social perspective, we propose a Social Tie-based Incentive Scheme (STIS) to deal with the selfish problem for cooperative spectrum sensing in distributed cognitive radio networks. This scheme inspires SUs to contribute sensing information for the SUs who have social tie but not others, and such willingness varies with the strength of social tie value. The evaluation of each SU's social tie derives from its contribution for others. Finally, simulation results validate the effectiveness of the proposed scheme.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.12
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• pp.6214-6242
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• 2019

Routing in mobile ad hoc networks is performed in a distributed fashion where each node acts as host and router, such that it forwards incoming packets for others without relying on a dedicated router. Nodes are mostly resource constraint and the users are usually inclined to conserve their resources and exhibit selfish behaviour by not contributing in the routing process. The trust and reputation models have been proposed to motivate selfish nodes for cooperation in the packet forwarding process. Nodes having bad trust or reputation are detected and secluded from the network, eventually. However, due to the lack of proper identity management and use of non-persistent identities in ad hoc networks, malicious nodes can pose various threats to these methods. For example, a malicious node can discard the bad reputed identity and enter into the system with another identity afresh, called whitewashing. Similarly, a malicious node may create more than one identity, called Sybil attack, for self-promotion, defame other nodes, and broadcast fake recommendations in the network. These identity-based attacks disrupt the overall detection of the reputation systems. In this paper, we propose a reputation-based scheme that detects selfish nodes and deters identity attacks. We address the issue in such a way that, for normal selfish nodes, it will become no longer advantageous to carry out a whitewash. Sybil attackers are also discouraged (i.e., on a single battery, they may create fewer identities). We design and analyse our rationale via game theory and evaluate our proposed reputation system using NS-2 simulator. The results obtained from the simulation demonstrate that our proposed technique considerably diminishes the throughput and utility of selfish nodes with a single identity and selfish nodes with multiple identities when compared to the benchmark scheme.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.36 no.2A
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• pp.179-187
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• 2011

Recently, cognitive radio attracts lots of interest to effectively utilize the limited spectral resource. In the previous researches, we proposed a method to enhance the system capacity of the overall network by using Selfish Symbiotic architecture and Non-selfish Symbiotic architecture. In this research, we further enhance the previous works to OFDM-based CR networks by using efficient subchannel allocation. The system performance is evaluated through intensive simulations with multiple primary users as well as a single primary user with different numbers of CR users.

• Journal of the Korea Society of Computer and Information
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• v.23 no.3
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• pp.25-31
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• 2018

In this paper, we consider the game theoretic approach to investigate the transmit power optimization problem where D2D users share the uplink of the cellular system. Especially, we formulate the transmit power optimization problem as a non cooperative power control game. In the user wide sense, each user may try to select its transmit power level so as to maximize its utility in a selfish way. In the system wide, the transmit power levels of all users eventually converge to the unique point, called Nash Equilibrium. We first formulate the transmit power optimization problem as a non cooperative power control game. Next, we examine the existence of Nash Equilibrium. Finally, we present the numerical example that shows the convergence to the unique transmit power level.

• International journal of advanced smart convergence
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• v.7 no.1
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• pp.15-23
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• 2018

Spectrum allocation is a key operation in cognitive radio networks (CRNs), where secondary users (SUs) are usually selfish - to achieve itself utility maximization. In view of this context, much prior lit literature proposed spectrum allocation base on non-cooperative game models. However, the most of them proposed non-cooperative game models based on complete information of CRNs. In practical, primary users (PUs) in a dynamic wireless environment with noise uncertainty, shadowing, and fading is difficult to attain a complete information about them. In this paper, we propose a non-cooperative game joint hidden markov model scheme for spectrum allocation in CRNs. Firstly, we propose a new hidden markov model for SUs to predict the sensing results of competitors. Then, we introduce the proposed hidden markov model into the non-cooperative game. That is, it predicts the sensing results of competitors before the non-cooperative game. The simulation results show that the proposed scheme improves the energy efficiency of networks and utilization of SUs.