Research On Crowdsourcing Quality Of Service Based On Game Theory Under Blockchain Framework

Crowdsourcing platforms have been widely employed by online matching systems,such as Uber and Airbnb.They provide an efficient matching service and enable promising balance between service supply and demand.However,in traditional centralized systems,crowdsourcing tasks may suffer from malicious behaviors such as plagiarism and fraud,which results in low Quality of Service(QoS).Blockchain technology,also known as distributed ledger technology,has the characteristics of decentralization,openness and transparency,so that everyone can participate in database records.Therefore,many scholars proposed to introduce the blockchain technology into the crowdsource platform to effectively solve the problems brought about by the traditional centralized system,such as easy single point of failure,easy leakage of privacy and high cost.However,the consensus algorithm widely used in the existing blockchain technology has problems such as serious waste of social resources,easy forking,vulnerability to bribery attacks and the concentration of power in few agents,thus bringing new security problems to the crowdsource system.In this paper,a new consensus algorithm is designed in the blockchain-based crowdsourcing system,and incentive mechanism is designed on this basis,so as to achieve the purpose of improving the quality of service on the premise of ensuring security.First,we propose a new kind of blockchain-based crowdsourcing system(BCS).According to the existing problems of traditional consensus algorithm,we propose a new Proof of Strategy(PoST)algorithm in the blockchain-based crowd-sourcing system environment.The algorithm dynamically allocates the rights according to the user's own policy and finally produces the unique verifier.Therefore,problems such as bifurcation,serious waste of social resources,vulnerability to bribery and concentration of a few nodes can be effectively avoided.At the same time,we also give the game analysis among users in the consensus algorithm based on strategy proof,and prove the existence and uniqueness of Nash equilibrium.Secondly,based on the BCS model and the consensus algorithm based on strategy,we proposed the quality rating protocol and formed a new incentive mechanism.Moreover,in the consensus algorithm based on strategy proof and quality rating protocol,we give the game analysis of worker participation task.It is proved that Nash equilibrium exists and is unique,and Nash equilibrium is controllable,that means,the system designer can regulate the quality rating agreement to ensure that workers will not choose to free ride and other malicious behaviors.Finally,for the consensus agreement based on policy proof and the incentive mecha-nism based on quality rating agreement proposed by us,we put forward a specific imple-mentation plan.Taking Didi's data as an example,we simulated the crowdsourcing task from three scenarios representing different sizes,namely,Didi Agent Drive,Didi Special Car and Didi Express.The results show that when the maximum effort level of workers is as 1,the average effort level of workers in BCS is about 0.9,and the competitive pressure increases with the increase of the number of participants,so the average QoS will also improve.However,the general model can only maintain about 0.8.In BCS,the operation time of the algorithm varies linearly with the increase of the system size,so the time is controllable even when applied to a large-scale crowdsourcing scenario.In addition,the number of evenly distributed Reputation coin R coin owners tends to be normally distributed as the quest progresses and blocks increase.This means that the incentive of BCS to workers is always maintained at a high level,and will not decrease as the task goes on and the block increases.At the same time,it also avoids the possibility that a few nodes control the bookkeeping rights.