An Incentive Mechanism for Federated Learning:A Continuous Zero-Determinant Strategy Approach

As a representative emerging machine learning technique, federated learning(FL) has gained considerable popularity for its special feature of “making data available but not visible”. However, potential problems remain, including privacy breaches, imbalances in payment, and inequitable distribution.These shortcomings let devices reluctantly contribute relevant data to, or even refuse to participate in FL. Therefore, in the application of FL, an important but also challenging issue is to motivate as many participants as possible to provide high-quality data to FL. In this paper, we propose an incentive mechanism for FL based on the continuous zero-determinant(CZD) strategies from the perspective of game theory. We first model the interaction between the server and the devices during the FL process as a continuous iterative game. We then apply the CZD strategies for two players and then multiple players to optimize the social welfare of FL, for which we prove that the server can keep social welfare at a high and stable level. Subsequently, we design an incentive mechanism based on the CZD strategies to attract devices to contribute all of their high-accuracy data to FL.Finally, we perform simulations to demonstrate that our proposed CZD-based incentive mechanism can indeed generate high and stable social welfare in FL.

Carbon Abatement Cost-Sharing Strategy for Electric Power Sector Based on Incentive and Subsidy Mechanisms

The green and low carbon transition and development of the electricity industry is the most crucial task in realizing the“dual-carbon target”,and it is urgent to explore the incentive and subsidy mechanism to promote green electricity consumption and the cost-sharing strategy of carbon reduction,to alleviate the pressure of carbon abatement cost of each subject of the electricity supply chain.Against this background,this paper takes into account the low-carbon subsidies provided by the government and the incentive subsidies for users,and studies the optimal decision-making of each subject in the electricity supply chain,so that each of them can obtain the optimal profit and achieve carbon emission reduction at the same time.Firstly,taking into account the direct power purchase mode of large users and the electricity-selling companies emerging after the reform of the power sales side,we have established a cooperative mechanism for sharing the cost of carbon emission reduction in the electricity supply chain and clarified the relationship between the supply and demand of electricity among the main parties.Subsequently,considering government low-carbon subsidies and user incentive subsidies,the optimal decisionmaking model is established under two scenarios of decentralized and centralized cooperative games in the supply chain,respectively,with the objective of maximizing profits and carbon reduction rates.Solving for the optimal proportion of carbon abatement costs shared by each participant in the electricity supply chain in achieving game equilibrium.Finally,we analyze the role of the government’s low-carbon subsidies,users’incentive subsidies,and other factors on the profit and carbon reduction effect of the electricity industry through the example analysis and further analyze the impact of carbon abatement cost-sharing measures to provide recommendations for the electricity industry to realize low-carbon abatement and make decisions.

Research on the Improvement of Incentive Mechanism for Pharmaceutical Sales Personnel - Taking Company A as an Example

Objective To analyze the improvement of the incentive mechanism of sales personnel in pharmaceutical company A,and to promote the smooth operation and further development of the company in a long term.Methods Compensation incentive,performance appraisal,welfare benefit,training incentive,promotion motivation and enterprise cultural inspiration were explored through questionnaires,telephone interviews and in-person interviews.Results and Conclusion This company’s incentive mechanism has problems in two aspects:Material incentives and spiritual incentives.As to the company’s characteristics and strategic development,the optimization countermeasures of incentive mechanism are proposed from the following three aspects:constructing a reasonable incentive system,establishing an efficient spiritual incentive mechanism,and implementing the dynamic incentive and differentiated incentive simultaneously.

Incentive mechanism analysis of information security outsourcing based on principal-agent model

In order to solve principal-agent problems caused by interest inconformity and information asymmetry during information security outsourcing, it is necessary to design a reasonable incentive mechanism to promote client enterprises to complete outsourcing service actively. The incentive mechanism model of information security outsourcing is designed based on the principal-agent theory. Through analyzing the factors such as enterprise information assets value, invasion probability, information security environment, the agent cost coefficient and agency risk preference degree how to impact on the incentive mechanism, conclusions show that an enterprise information assets value and invasion probability have a positive influence on the fixed fee and the compensation coefficient; while information security environment, the agent cost coefficient and agency risk preference degree have a negative influence on the compensation coefficient. Therefore, the principal enterprises should reasonably design the fixed fee and the compensation coefficient to encourage information security outsourcing agency enterprises to the full extent.

A Study on the Multi-Task Incentive Mechanism for the Service Provider

Both conflict and asymmetric information exist betweenthe telecom operators and the service provider,and result in illegal behaviors of the service provider.The relationship between the telecom operators andthe service provider is classical multi-task principalagentrelationship. The multi-task incentive for theservice provider is considered in the design of theprincipal-agent incentive contract, and it is necessaryto add the multi-task incentive to the serviceproviders through the analysis of the risk costs andthe agency costs of this problem.

Economy supervision mode of electricity market and its incentive mechanism

The analysis of a supervision environment is the first step for a company to enter the new electricity market. Transmission and distribution assets are the main investment targets of a company. The overseas power market belongs to the regulated industry;whether it is a stock M&A project or a green land bidding project, the regulatory environment determines the assets. The level of return and investment risk that guides the operation strategy of existing overseas assets, has a significant impact on the investment and operations of international companies. A comprehensive and rapid assessment of the regulatory environment can help the project teams of international companies understand the macroenvironment of the target electricity market within a short period, quickly identify investment risks, qualitatively analyze the return level of the underlying assets, shorten the decision time, capture investment opportunities, and enhance the team. Efficiency and quality of work are factors of great importance.

Study on the efficacy of the safety incentive mechanisms

Safety incentive mechanism and corresponding motivation avenues are helpful and important for the scientific safety management in coal mine. With the help of modern systematic analysis method, the efficacy of safety incentive mechanisms is discussed in detail. The research shows that more effective avenue to reduce accident is to differently use motivation measures in practice.

Incentive-compatible and budget balanced AGV mechanism for peer-to-peer energy trading in smart grids

Peer-to-peer(P2P)energy trading refers to a type of decentralized transaction,where the energy from distributed energy resources is directly traded between peers.A key challenge in peer-to-peer energy trading is designing a safe,efficient,and transparent trading model and operating mechanism.In this study,we consider a P2P trading environment based on blockchain technology,where prosumers can submit bids or offers without knowing the reports of others.We propose an Arrow-d’Aspremont-Gerard-Varet(AGV)-based mechanism to encourage prosumers to submit their real reserve price and determine the P2P transaction price.We demonstrate that the AGV mechanism can achieve Bayesian incentive compatibility and budget balance.Kernel density estimation(KDE)is used to derive the prior distribution from the historical bid/offer information of the agents.Case studies are carried out to analyze and evaluate the proposed mechanism.Simulation results verify the effectiveness of the proposed mechanism in guiding agents to report the true reserve price while maximizing social welfare.Moreover,we discuss the advantages of budget balance for decentralized trading by comparing the Vickrey-Clarke-Groves(VCG)and AGV mechanisms.

An Incentive Mechanism for Mobile Crowd Sensing in Vehicular Ad Hoc Networks

In the mobile crowdsensing of vehicular ad hoc networks (VANETs), in order to improve the amount of data collection, an effective method to attract a large number of vehicles is needed. Therefore, the incentive mechanism plays a dominant role in the mobile crowdsensing of vehicular ad hoc networks. In addition, the behavior of providing malicious data by vehicles as data collectors will have a huge negative impact on the whole collection process. Therefore, participants need to be encouraged to provide data honestly to obtain more available data. In order to increase data collection and improve the availability of collected data, this paper proposes an incentive mechanism for mobile crowdsensing in vehicular ad hoc networks named V-IMCS. Specifically, the Stackelberg game model, Lloyd’s clustering algorithm and reputation management mechanism are used to balance the competitive relationship between participants and process the data according to the priority order, so as to improve the amount of data collection and encourage participants to honestly provide data to obtain more available data. In addition, the effectiveness of the proposed mechanism is verified by a series of simulations. The simulation results show that the amount of available data is significantly higher than the existing incentive mechanism while improving the amount of data collection.

Incentive Mechanism Design for Public Goods Provision:Price Cap Regulation and Optimal Regulation

This paper studies the mechanism design that induces firms to provide public goods under two regulatory means： price cap regulation and optimal regulation, respectively. We first outline two models of monopoly regulation with unobservable marginal costs and effort, which can be regard as an optimal problem with dual restrictions. By solving this problem, we get the two optimal regulatory mechanisms to induce the provision of public goods. Further, by comparative statics, the conclusion is drawn that the welfare loss as sociated with price cap regulation, with respective to optimal regulation, increases more with increase of the expense of public goods.

Exploration on the Incentive Mechanism of Regional Ecological Capital Operation from the Perspective of Principal Agent

Ecological capital operation is a major means for innovation of ecological environment protection,and provides ecological security for sustainable economic and social development.In this paper,key factors for construction of incentive mechanism of ecological capital operation are explored from government cognition,enterprise attitude and public awareness.Via model building and parameter setting,incentive mechanism system of single objective is established effectively,to promote effective realization of regional ecological capital operation.

An Incentive Mechanism Model for Crowdsensing with Distributed Storage in Smart Cities

Crowdsensing,as a data collection method that uses the mobile sensing ability of many users to help the public collect and extract useful information,has received extensive attention in data collection.Since crowdsensing relies on user equipment to consume resources to obtain information,and the quality and distribution of user equipment are uneven,crowdsensing has problems such as low participation enthusiasm of participants and low quality of collected data,which affects the widespread use of crowdsensing.This paper proposes to apply the blockchain to crowdsensing and solve the above challenges by utilizing the characteristics of the blockchain,such as immutability and openness.An architecture for constructing a crowdsensing incentive mechanism under distributed incentives is proposed.A multi-attribute auction algorithm and a k-nearest neighbor-based sensing data quality determination algorithm are proposed to support the architecture.Participating users upload data,determine data quality according to the algorithm,update user reputation,and realize the selection of perceived data.The process of screening data and updating reputation value is realized by smart contracts,which ensures that the information cannot be tampered with,thereby encouraging more users to participate.Results of the simulation show that using two algorithms can well reflect data quality and screen out malicious data.With the help of blockchain performance,the architecture and algorithm can achieve decentralized storage and tamper-proof information,which helps to motivate more users to participate in perception tasks and improve data quality.

A dynamic incentive and reputation mechanism for energy-efficient federated learning in 6G

As 5G becomes commercial,researchers have turned attention toward the Sixth-Generation(6G)network with the vision of connecting intelligence in a green energy-efficient manner.Federated learning triggers an upsurge of green intelligent services such as resources orchestration of communication infrastructures while preserving privacy and increasing communication efficiency.However,designing effective incentives in federated learning is challenging due to the dynamic available clients and the correlation between clients'contributions during the learning process.In this paper,we propose a dynamic incentive and reputation mechanism to improve energy efficiency and training performance of federated learning.The proposed incentive based on the Stackelberg game can timely adjust optimal energy consumption with changes in available clients during federated learning.Meanwhile,clients’contributions in reputation management are formulated based on the cooperative game to capture the correlation between tasks,which satisfies availability,fairness,and additivity.The simulation results show that the proposed scheme can significantly motivate high-performance clients to participate in federated learning and improve the accuracy and energy efficiency of the federated learning model.

Contract theory based incentive mechanism design for buffer resource in wireless caching networks

Evidences indicate that,due to the limited caching capacity or inaccurate estimation on users’preferences,the requested files may not be fully cached in the network edge.The transmissions of the un-cached files will also lead to duplicated transmissions on backhaul channels.Buffer-aided relay has been proposed to improve the transmission performance of the un-cached files.Because of the limited buffer capacity and the information asymmetric environment,how to allocate the limited buffer capacity and how to incentivize users in participating buffer-aided relay have become critical issues.In this work,an incentive scheme based on the contract theory is proposed.Specifically,the backlog violation probability,i.e.,the buffer overflow probability,is provided based on the martingale theory.Next,based on the backlog violation probability,the utility functions of the relay node and users are constructed.With the purpose to maximize the utility of the relay node,the optimal contract problem is formulated.Then,the feasibility of the contract is also demonstrated,and the optimal solution can be obtained by the interior point method.Finally,numerical results are presented to demonstrate effectiveness of the proposed contract theory scheme.

Improvement of Incentive Mechanism on BitTorrent-like Peer-to-Peer File Sharing Systems

BitTorrent is a very popular Peer-to-Peer file sharing system, which adopts a set of incentive mechanisms to encourage contribution and prevent free-riding. However, we find that BitTorrent’s incentive mechanism can prevent free-riding effectively in a system with a relatively low number of seeds, but may fail in producing a disincentive for free-riding in a system with a high number of seeds. The reason is that BitTorrent does not provide effective mechanisms for seeds to guard against free-riding. Therefore, we propose a seed bandwidth allocation strategy for the BitTorrent system to reduce the effect of seeds on free-riding. Our target is that a downloader which provides more service to the system will be granted a higher benefit than downloaders which provide lower service when some downloaders ask for downloading file from a seed. Finally, simulation results are given, which validate the effectiveness of the proposed strategy.

Enhancing customers prevention efforts:An incentive feedback mechanism design

To improve the inefficient prevention caused by customers unwillingness to adopt prevention strategies in health management,an incentive feedback mechanism that is based on game theory and contract design theory is introduced.The conditions for making customers and health maintenance organizations(HMOs)willing to participate in the proposed mechanism are given.A dual nonlinear programming model is used to identify the optimal prevention effort of customers and the pricing strategy of HMOs.Results show that to generate increased benefits,HMOs need to consider cost sharing when customers are not familiar with the proposed health services.When health services are gradually accepted,the cost sharing factor can be gradually reduced.Simulation shows that under random circumstances in which the market reaches a certain size,the proposed method exhibits a positive network externality.Motivated by network externality,HMOs only need to make their customers understand that the larger the number of participants,the greater the utility of each person.Such customers may then spontaneously invite others to purchase insurance.

Optimization of Chinese power enterprises R&D staff incentive mechanism

With the deepening of electric power market reform in China,the monopoly edge of the state-owned electric power enterprises will lose.On the basis of the existing post performance salary mechanism,Chinese power enterprises need to optimize the incentive mechanism of R&D staff,to arouse the R&D staff's enthusiasm and creativity,to adapt to the new market competition and further improve market value.Whilst the incentive mechanism optimizing processing needs to consider not only the changing market environment but also the personal and working characteristics of R&D staff.This paper summarizes the characteristics of the current Chinese power enterprises' R&D staff:staff's theory quality is high,but insensitive to the market;they are confronted with heavy workload and diversified job choices;managers can observe their behavior choices or not;besides,the process of R&D is complex and the market reactions of R&D achievements are uncertain.Based on the premise of the above features,two incentive models are established in this paper from the point of view of enterprise managers.One is for the situation when staff's behavior choices can be observed;the other is for the situation when staff's behavior choices cannot be observed.Through solving the model,we analyze the optimization path of electric power enterprises R&D staff incentive mechanism under these conditions:(1) when staff's behavior choices can be observed,managers can pay more to the R&D staff who develop products with higher output value,in order to encourage them to work harder.(2) when staff's behavior choices cannot be observed,managers should take reasonable strategies according to the different situations:a.when R&D staff incentive totally depend on the market value of the R&D achievements,managers should allocate workload rationally according to their different technical levels;b.when the market reactions of R&D results become more precarious,managers need to reduce the incentive intensity which based on the market value and raise their fixed salary level;c.when R&D staff become more risk averse,managers should reduce the incentive intensity which based on the market value and raise their fixed salary level;on the contrary,managers should improve the incentive intensity and reduce the fixed salary level.

Research on Incentive Mechanism and Analysis of the Obstacles in the Application of Low-carbon Logistics Technology

Low-carbon logistics technology is a modem technology with green environmental protection concept as the core, which can effectively reduce the carbon emissions of all links in logistics activities, and thus achieve the goal of maximizing the use of resources and reducing environmental pollution. With the deepening of the concept of environmental protection, the application of low-carbon logistics technology is not only an inevitable choice for adapting to social development and responding to environmental protection slogans, but also an inevitable choice for the logistics industry to achieve sustainable development goals. Based on the brief introduction of low-carbon logistics technology, this paper analyzes the main obstacles of the application of the technology, and proposes corresponding incentive mechanism according to the obstacle factors, aiming at alleviating the resistance in the practical application of low-carbon logistics technology and promoting the realization of low-carbon logistics development.

The Incentive Mechanism Research of Knowledge Workers

＂Knowledge workers＂ is the carrier of enterprise knowledge and technology and is undoubtedly the most important resource and core competence. How to effectively motivate such people create greater wealth for the enterprise has become the key problem of the era of knowledge economy. Based on the concept and characteristics of knowledge workers, this paper uses classical analysis framework of incentive theory; through quantitative and qualitative analysis, it points out the existing problems and puts forward solutions on the basis of full analysis of the present incentive situation.

Research on Incentive Mechanism of Virtual Community Knowledge Sharing

With the continuous development of Internet technology, the network has become an important part of people＇s lives, the emergence of virtual communities is promoting the deep interaction oflntemet users, but it is found that the virtual community ＂diving party＂ is more and more through investigation and literature research, The quantity and quality of knowledge sharing are declining. Therefore, this paper summarizes the behavior and influencing factors of knowledge sharing in virtual community through literature research and investigation and research. At the same time, through the research of incentive theory, the author has obtained the incentive method and content of knowledge sharing, and established the incentive mechanism. The bright spot is to perfect the theory of knowledge sharing while transforming theory into practice, and to provide suggestions for the development of incentive mechanism of virtual community.