Research On Incentive Mechanism Of D2D Communication And Computing

The exponential growth of wireless data services driven by mobile Internet and smart devices has accelerated the employment of the 5G cellular network.On the one hand,for the content transmission,users need to acquire high-speed and low-latency content transmission service.The demand of high-definition real-time video lead to the heavier load of cellular networks.On the other hand,in the period of rapid development of cloud computing and edge computing,many new time-sensitive and computation-intensive mobile services are more popular such as mobile interactive games,face recognition,natural language processing and augmented reality.With the popularity of computing services,the demand of users has been expended from content service to computing service.As a new communication technology to directly communicate between devices,D2D communication technology can help users access the content from nearby users to reduce the traffic load of cellular network.In the fog computing and IoT scenarios.D2D communication can help users make use of the idle computing resources around it to complete the time-sensitive and computation-intensive mobile applications,and avoid the high delay caused by the faraway cloud computing servers,which improves the user experience.Due to the energy consuming of D2D devices for content sharing and computing sharing,this thesis is devoted to the research of incentive mechanism design in the process of D2D content sharing and computing sharing in order to encourage users to participate in the sharing process to reduce the traffic offloading and computing task processing delay.In the D2D content sharing problem,we assume the process as a labor market and the Principal-Agent model is introduced based on contract theory in microeconomics.The signaling theory is employed to solve the Information Asymmetry problem in the Principal-Agent model.We evaluate the capacity types of user equipments according to their channel condition and residual power,and propose a signaling-based incentive mechanism to motivate them to participate.The optimal contract is designed for different types of content providers.And the simulation results show that the proposed mechanism can significantly incentive the high-type CP's participation in D2D content sharing.In the D2D computing sharing problem,the comprehensive ability of computing providers is evaluated by considering the transmission rate,computing capability,residual power and task delay.The Information Asymmetry problem is solved by signaling theory and the optimal contract is designed.The utility of computing providers and the system is optimized and computing providers are effectively motivated to participate in computing sharing.Based on the Kuhn-Munkres algorithm in bipartite graph,we design a polynomial complexity matching scheme and maximize the network utility by investigating the Many-to-Many computation offloading problem.And an improved algorithm to promote the fairness of matching scheme is further discussed.Through extensive simulations,it shows that the utility of computation providers is optimized and they are effectively motivated which contributes to the improvement of computing service in fog computing.