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In Wireless Sensor Networks (WSNs), unlicensed users, that is, sensor nodes, have excessively exploited the unlicensed radio spectrum. Through Cognitive Radio (CR), licensed radio spectra, which are owned by licensed users, can be partly or entirely shared with unlicensed users. This paper proposes a strategic bargaining spectrum-sharing scheme, considering a CR-based heterogeneous WSN (HWSN). The sensors of HWSNs are discrepant and exist in different wireless environments, which leads to various signal-to-noise ratios (SNRs) for the same or different licensed users. Unlicensed users bargain with licensed users regarding the spectrum price. In each round of bargaining, licensed users are allowed to adaptively adjust their spectrum price to the best for maximizing their profits. . Then, each unlicensed user makes their best response and informs licensed users of "bargaining" and "warning". Through finite rounds of bargaining, this scheme can obtain a Nash bargaining solution (NBS), which makes all licensed and unlicensed users reach an agreement. The simulation results demonstrate that the proposed scheme can quickly find a NBS and all players in the game prefer to be honest. The proposed scheme outperforms existing schemes, within a certain range, in terms of fairness and trade success probability. [ABSTRACT FROM AUTHOR]

We consider a distributed reactive power compensation problem in a distribution network in which users locally generate reactive power using distributed generation units to contribute to the local voltage control. We model and analyze the interaction between one electric utility company and multiple users by using the Nash bargaining theory. On one hand, users determine the amount of active and reactive power generation for their distributed generation units. On the other hand, the electric utility company offers reimbursement for each user based on the amount of reactive power dispatched by that user. We first quantify the benefit for the electric utility company and users in the reactive power compensation problem. Then we derive the optimal solution for the active and reactive power generation, as well as reimbursement for each user under two different bargaining protocols, namely sequential bargaining and concurrent bargaining. Numerical results show that both the electric utility company and users benefit from the proposed decentralized reactive power compensation mechanism, and the overall system efficiency is improved. [ABSTRACT FROM PUBLISHER]

This paper presents a bargaining-based resource allocation and price agreement in an environment of cloud-assisted Wireless Body Area Networks (WBANs). The challenge is to finalize a price agreement between the Cloud Service Providers (CSPs) and the WBANs, followed by a cost-effective mapping among them. Existing solutions primarily focus on profits of the CSPs, while guaranteeing different user satisfaction levels. Such pricing schemes are bias prone, as quantifying user satisfaction is fuzzy in nature and hard to implement. Moreover, such an traditional approach may lead to an unregulated market, where few service providers enjoy the monopoly/oligopoly situation. However, in this work, we try to remove such biasness from the pricing agreements, and envision this challenge from a comparatively fair point of view. In order to do so, we use the concept of bargaining, an interesting approach involving cooperative game theory. We introduce an exposition - multi-stage Nash bargaining solution (MUST-NBS), that unfolds into multiple stages of bargaining, as the name suggests, until we conclude price agreement between the CSPs and the WBANs. In addition, the proposed approach also consummates the final mapping between the CSPs and the WBANs, depending on the cost-effectiveness of the WBANs. Analysis of the proposed algorithms and the inferences of the results validates the usefulness of the proposed mapping technique. [ABSTRACT FROM AUTHOR]

The impacts of road congestion charges on traffic safety are often overlooked in evaluating the benefits of congestion charging practices and searching for traffic safety strategies. This paper aims to examine how congestion pricing affects both efficiency and automobile safety. The first part of the study proposes and formulates the general traffic accident minimization pricing (TAMP) problem. Considering within-day and day-to-day travel demand fluctuations, a multiobjective kbilevel optimization model under stochastic travel demand is developed based on the TAMP problem. This model is employed to determine the optimal toll levels that minimize both the negative externalities of congestion and accidents. Numerical results indicate that the traditional efficiency-oriented congestion pricing scheme, which does not consider impacts to safety, is often implemented in a less beneficial manner with regard to accident reduction. [ABSTRACT FROM AUTHOR]

The Nash Bargaining Solution (NBS) has been broadly suggested as an effective solution for the problem of fair allocation of multiple resources, namely bandwidth allocation in datacenters. In spite of being thoroughly studied, and provably strategy-proof for most scenarios, NBS-based allocation methods lack research on the strategic behavior of tenants in the case of proportionality of resource demands, which is common in datacenter workloads. We found that misbehavior is beneficial: by lying about bandwidth demands tenants can improve their allocations. We show that a sequence of selfish improvements leads to trivial demand vectors for all tenants. It essentially removes sharing incentives which are very important for datacenter networks. In this paper, we analytically prove that tenants can misbehave in 2- and 3- tenants cases. We show that misbehavior is possible in one recently proposed NBS-based allocation system if proportionality of demands is taken into account. Monte Carlo simulations were done for 2-15 tenants to show a misbehavior possibility and its impact on aggregated bandwidth. We propose to use another game-theoretic approach, namely Dominant Resource Fairness (DRF) to allocate bandwidth in the case of proportional demands. We show that this method performs significantly better than NBS after misbehavior. [ABSTRACT FROM AUTHOR]

Mathematical models involving more than one objective seem more adherent to real problems. Often players have more than one goal which are often not comparable. These situations are typical for game-theoretic models in economic and ecology. In this paper, new approaches to construct equilibria in dynamic multicriteria games are constructed. We consider a dynamic, discrete-time, game model where the players use a common resource and have different criteria to optimize. First, we construct the guaranteed payoffs in a several ways. Then, we find an equilibrium as a solution of a Nash bargaining scheme with the guaranteed payoffs playing the role of status quo points. The obtained equilibrium, called a multicriteria Nash equilibrium, gives a possible solution concept for dynamic multicriteria games. [ABSTRACT FROM AUTHOR]

Long-term sustainability in airline transportation entails mitigating the detrimental impact of CO 2 emissions on the environment. However, it is also necessary that it does not affect the airlines' performance. In this regard, it is important to achieve optimal and efficient targets by inputs, good outputs, and undesirable outputs. The purpose of this study is to compute the input and output targets using the bargaining approach for a sample of major global airlines for the period 2018. This has been undertaken utilising the proposed data envelopment analysis (DEA)-based Nash bargaining model wherein its novelty lies in incorporating weakly disposable undesirable outputs. This model achieves reasonable and optimal targets for not just inputs and outputs but also for undesirable outputs by carrying out an unbiased, rational negotiation between the inputs and outputs. The results show that weakly efficient airlines attain the optimal targets by improving their environmental performance and inefficient airlines can achieve their input/output targets by carrying out an unbiased, rational negotiation between the inputs, good outputs, and bad output. The policy implications emanating from the findings have also been highlighted. • DEA-based Nash bargaining model with weak disposable undesirable outputs is proposed. • Unbiased, rational negotiation between inputs, desirable outputs, and undesirable outputs achieves Nash targets. • Targets depict improvement in input and output efficiency and environmental performance of airlines. • Bargaining solution attained is based on the rationale of utility maximisation. [ABSTRACT FROM AUTHOR]

Making use of the game theory,a model of service selection based on Nash bargaining solution was build,and an approach for enhancing Web service trustworthiness was proposed.A bargaining algorithm is designed between ser-vice sides of both complete rationality,through adjusting service price,to achieve maximum utility for both service re-questor and provider,and increase the success rate of transactions and service trustworthiness.Results of experiments show that,on the basis of the game that according to quality of service,reputation and security between service provider and requestor,the service selection can promote the establishment of trustable service computing environment and en-hance credibility of the service.

The approaches to construct optimal behavior in dynamic multicriteria games with finite horizon are presented. To obtain a multicriteria Nash equilibrium, the bargaining construction (Nash product) is adopted. To construct a multicriteria cooperative equilibrium, a Nash bargaining scheme is applied. Dynamic multicriteria bioresource management problem with finite harvesting times is considered. The players’ strategies and the payoffs are obtained under cooperative and noncooperative behavior.

This paper firstly replaces the first-come-first-service (FCFS) mechanism with the time-sharing (TS) mechanism in fog computing nodes (FCNs). Then a collaborative load-balancing algorithm for the TS mechanism is proposed for FCNs. The algorithm is a variant of a work-stealing scheduling algorithm, and is based on the Nash bargaining solution (NBS) for a cooperative game between FCNs. Pareto optimality is achieved through the collaborative working of FCNs to improve the performance of every FCN. Lastly the simulation results demonstrate that the game-theory based work-stealing algorithm (GWS) outperforms the classical work-stealing algorithm (CWS).

This paper presents a novel Nash bargaining solution (NBS)-based cooperative game-theoretic framework for power control in a distributed multiple-radar architecture underlying a wireless communication system. Our primary objective is to minimize the total power consumption of the distributed multiple-radar system (DMRS) with the protection of wireless communication user’s transmission, while guaranteeing each radar’s target detection requirement. A unified cooperative game-theoretic framework is proposed for the optimization problem, where interference power constraints (IPCs) are imposed to protect the communication user’s transmission, and a minimum signal-to-interference-plus-noise ratio (SINR) requirement is employed to provide reliable target detection for each radar. The existence, uniqueness and fairness of the NBS to this cooperative game are proven. An iterative Nash bargaining power control algorithm with low computational complexity and fast convergence is developed and is shown to converge to a Pareto-optimal equilibrium for the cooperative game model. Numerical simulations and analyses are further presented to highlight the advantages and testify to the efficiency of our proposed cooperative game algorithm. It is demonstrated that the distributed algorithm is effective for power control and could protect the communication system with limited implementation overhead.

In this work, a multi-person mean-field-type game is formulated and solved that is described by a linear jump-diffusion system of mean-field type and a quadratic cost functional involving the second moments, the square of the expected value of the state, and the control actions of all decision-makers. We propose a direct method to solve the game, team, and bargaining problems. This solution approach does not require solving the Bellman–Kolmogorov equations or backward–forward stochastic differential equations of Pontryagin’s type. The proposed method can be easily implemented by beginners and engineers who are new to the emerging field of mean-field-type game theory. The optimal strategies for decision-makers are shown to be in a state-and-mean-field feedback form. The optimal strategies are given explicitly as a sum of the well-known linear state-feedback strategy for the associated deterministic linear–quadratic game problem and a mean-field feedback term. The equilibrium cost of the decision-makers are explicitly derived using a simple direct method. Moreover, the equilibrium cost is a weighted sum of the initial variance and an integral of a weighted variance of the diffusion and the jump process. Finally, the method is used to compute global optimum strategies as well as saddle point strategies and Nash bargaining solution in state-and-mean-field feedback form.

Co-channel interference occurs in coexisting Wireless Body Area Networks (WBANs) and has an impact on the capacity allocation of the networks. The proposed Two Stage Capacity Allocation (TSCA) mitigates interference and maximizes the capacity of poor channel quality WBANs with high priority data. It uses traditional interference mitigation schemes such as transmission power level control, channel switching and relay-aided transmission in each instant of pause time. The proposed work introduces a metric called Emergency Residual Index (ER-Index) and chooses any one of the mitigation schemes. The ER Index value provides a trade-off between residual energy, emergency factor and channel metrics. Further, TSCA executes a two-stage capacity allocation method. The TSCA scheme is a combination of the Nash bargaining solution and the Min-Max algorithm. The mitigated interference is 45% compared to Dynamic link quality-based Sub Channel Allocation (DSCA) and 60% compared to Traffic Aware Medium Access Control (TA-MAC). The average energy consumption is decreased up to 37.82% compared to TA-MAC and 25.59% compared to the DSCA algorithm. [ABSTRACT FROM AUTHOR]

Negotiation procedures between a supplier and a retailer in a supply chain model including buyback contract have been studied in recent years. The negotiation procedures in the above studies have consisted of three successive steps: (i) show the necessity that the conclusion of the contract based on a set of contract parameters brings respective incentives to both of the supplier and retailer, (ii) present a mutual relationship between contract parameters of guaranteeing simultaneously optimalities of both of the supplier and retailer, and (iii) determine a unique combination of contract parameters using the Nash bargaining theory. Through successive steps (i)-(iii), some sets of contract parameters have been screened step by step, and eventually, an optimal set of contract parameters has been uniquely decided in step (iii) as a bargaining solution. However, the mathematical significance of respective conditions derived in steps (i) and (ii) for the bargaining solution of step (iii) has not been fully explained. Therefore, we reconsider respective roles of steps (i) and (ii) in the negotiation procedure based on a supply chain model including buyback contract. Then, we confirm the usefulness of the negotiation procedure consisting of three successive steps in the preceding studies. [ABSTRACT FROM AUTHOR]

A generalization of the class of bargaining problems examined by Engwerda and Douven [(2008) On the sensitivity matrix of the Nash bargaining solution, Int. J. Game Theory 37, 265-279] is studied. The generalized class consists of nonconvex bargaining problems in which the feasible set satisfies the requirement that the set of weak Pareto-optimal solutions can be described by a smooth function. The intrinsic comparative statics of the aforesaid class are derived and shown to be characterized by a symmetric and positive semidefinite matrix, and an upper bound to the rank of the matrix is established. A corollary to this basic result is that a Nash bargaining solution is intrinsically a locally nondecreasing function of its own disagreement point. Other heretofore unknown results are similarly deduced from the basic result. [ABSTRACT FROM AUTHOR]

In the context of networking, research has focused on non-cooperative games, where the selfish agents cannot reach a binding agreement on the way they would share the infrastructure. Many approaches have been proposed for mitigating the typically inefficient operating points. However, in a growing number of networking scenarios, selfish agents are able to communicate and reach an agreement. Hence, the degradation of performance should be considered at an operating point of a cooperative game. Accordingly, our goal is to lay foundations for the application of the cooperative game theory to fundamental problems in networking. We explain our choice of the Nash bargaining scheme (NBS) as the solution concept, and introduce the price of selfishness (PoS), which considers the degradation of performance at the worst NBS. We focus on the fundamental load balancing game of routing over parallel links. First, we consider agents with identical performance objectives. We show that, while the price of anarchy (PoA) here can be large, through bargaining, all agents, and the system, strictly improve their performance. Interestingly, in a two-agent system or when all the agents have identical demands, we establish that they reach social optimality. We then consider agents with different performance objectives and demonstrate that the PoS and PoA can be unbounded, yet we explain why both measures are unsuitable. Accordingly, we introduce the price of heterogeneity (PoH), as an extension of the PoA. We establish an upper bound on the PoH and indicate its further motivation for bargaining. Finally, we discuss network design guidelines that follow from our findings. [ABSTRACT FROM PUBLISHER]

A new feature pertaining to proposer's ability to implement offers is introduced in the extensive form bargaining mechanism studied in Okada (1996). This mechanism is used to analyze the coalitional setting of strictly supermodular games. The new feature in the mechanism is that the proposer has a choice to implement his proposal with any subset of responders who have accepted it. Thus the institutional feature of ‘every responder has veto power’ is relaxed here. It is shown that for all sufficiently high discount factors δ , there exists an efficient subgame perfect equilibrium in pure stationary strategies (SSPE) whose limiting outcome is the core-constrained Nash Bargaining Solution. Moreover, all efficient SSPE are payoff-equivalent in the limit as δ → 1 . [ABSTRACT FROM AUTHOR]

This article studies the decisive mechanism of the Internet financial interest rate. Considering the possibility of basic symmetry for the credit information in the internet financial market with the application and development of the big data technology, a Nash Bargaining Module is established in the article, which includes the main decisive factors of the Internet financial interest rate (the program natural risk, program rate of return, loan period, loan scale, loan urgency, operating capacities of the borrower, the competition of the credit market, and the regime risk) as variables for analysis of their effects on the internet financial interest rates. According to relevant researches, the uncertainty of the loan projects in themselves and the costs for the implementation of secured credit contracts, rather than the reverse selection and moral risks arising from information asymmetry, form the main issues of the Internet financial interest rate. [ABSTRACT FROM AUTHOR]

Long-term evolution in unlicensed spectrum (LTE-U) is an emerging technology for expanding cellular network capacity without additional spectrum cost. This paper investigates effective spectrum sharing for coexisting Wi-Fi and LTE-U services. Based on a novel hyper access point (HAP) we introduced for effectively embedding LTE-U in unlicensed Wi-Fi band, LTE-U can directly take advantage of the Wi-Fi point coordination function protocol. To facilitate the coexistence, our HAP dedicates a contention-free period to LTE-U users and allows a contention period (CP) for traditional Wi-Fi users. We investigate the optimization of joint user association and resource allocation to further improve system throughput and user fairness. We formulate a network utility maximization problem based on the Nash bargaining solution (NBS), for which we derive a closed-form expression for the optimal CP length under a given user association. We analyze this NBS-based utility maximization and the performance of the proposed algorithm under log-normal fading, Rayleigh fading, and Rician fading channel models, respectively. Our numerical results corroborate our analysis and demonstrate effective improvement of the system performance by the proposed HAP algorithm against traditional LTE-U deployment. [ABSTRACT FROM PUBLISHER]

Many production systems consist of a sequence of processes or stages. For these systems, relational network DEA can be used and an overall system efficiency (equal to the efficiency of the different processes) can be computed. However, there can be alternative solutions that give different estimations of the process efficiencies and therefore lead to different decompositions of the overall system efficiency. It is not obvious which efficiency decomposition to use. In this paper, it is shown how a Nash bargaining game can be used to compute point estimates of the efficiency of the processes for multistage systems. The proposed approach extends and improves over existing approaches for production systems with just two stages. The rationality principles behind the proposed solution approach are presented and an interesting interpretation of the resulting efficiency decomposition is provided. The fact that this rigorous solution approach leads to such a simple and elegant efficiency decomposition should facilitate its adoption by Expert and Intelligent Systems practitioners. [ABSTRACT FROM AUTHOR]

Visual sensor networks (VSNs) consist of several camera nodes with wireless communication capabilities that can perform visual analysis tasks such as object identification, recognition, and tracking. Often, VSN deployments result in many camera nodes with overlapping fields of view. In the past, such redundancy has been exploited in two different ways: (1) to improve the accuracy/quality of the visual analysis task by exploiting multiview information or (2) to reduce the energy consumed for performing the visual task, by applying temporal scheduling techniques among the cameras. We propose a game theoretic framework based on the Nash bargaining solution to bridge the gap between the two aforementioned approaches. The key tenet of the proposed framework is for cameras to reduce the consumed energy in the analysis process by exploiting the redundancy in the reciprocal fields of view. Experimental results in both simulated and real-life scenarios confirm that the proposed scheme is able to increase the network lifetime, with a negligible loss in terms of visual analysis accuracy. © 2016 SPIE and IS&T [DOI: 10.1117/1.JEI.25.4.041002] [ABSTRACT FROM AUTHOR]

Traditional mobile data offloading transfers cellular users to WiFi networks to relieve the cellular system from the pressure of the ever-increasing data traffic load. However, the spectrum utilization of the WiFi network is bound to suffer from potential packet collisions due to its contention-based access protocol, especially when the number of competing WiFi users grows large. To tackle this problem, we propose transfering some WiFi users to be served by the LTE system, in contrast to the traditional mobile data offloading which effectively offloads LTE traffic to the WiFi network. Meanwhile, leveraging the emerging LTE in unlicensed spectrum (LTE-U) technology, some unlicensed spectrum resources may be allocated to the LTE system in compensation for handling more WiFi users. In this way, a win–win situation would be generated since LTE can generally achieve better performance than WiFi due to its capability of centralized co-ordination. To facilitate it, three important challenging issues are addressed in the paper: which WiFi users should be transferred; how many WiFi users need to be transferred; and how much unlicensed resources should be relinquished to the LTE-U network. We investigate three different user transfer schemes according to the availability of channel state information (CSI): the random transfer, the distance-based transfer, and the CSI-based transfer. In each scheme, the minimum required amount of unlicensed resources under a given transferred user number is analyzed. Furthermore, we utilize the Nash bargaining solution (NBS) to develop joint user transfer and unlicensed resource allocation strategy to fulfill the win–win situation for both networks, whose performance is demonstrated by numerical simulation. [ABSTRACT FROM PUBLISHER]

We study unanimity bargaining on the division of a surplus in the presence of monotonicity constraints. The monotonicity constraints specify a complete order on the players, which has to be respected by the shares in the surplus the players obtain in any bargaining outcome. A player higher in the order should not receive a lower share of the surplus. We analyze the resulting subgame perfect equilibria in stationary strategies and show that they are characterized by the simpler notion of bargaining equilibrium. Bargaining equilibria are shown to be unique and to have the property that players ranked strictly higher obtain strictly higher shares in the surplus. The key question is whether the bargaining advantage of a higher-ranked player persists when the probability of breakdown of bargaining tends to zero. We argue that such is not the case by showing that bargaining equilibria have a unique limit equal to an equal division of the surplus. It then follows that the limit also coincides with the Nash bargaining solution for this problem. [ABSTRACT FROM AUTHOR]